<?xml version="1.0" encoding="UTF-8"?>
<urlset
  xmlns="http://www.sitemaps.org/schemas/sitemap/0.9"
  xmlns:image="http://www.google.com/schemas/sitemap-image/1.1"
  xmlns:news="http://www.google.com/schemas/sitemap-news/0.9">
  <url>
    <loc>https://aiunderstanding.org/news/systematic-review-of-55-studies-finds-autism-machine-learning-still-leans-on-super</loc>
    <image:image>
      <image:loc>https://aiunderstanding.org/api/news/image/systematic-review-of-55-studies-finds-autism-machine-learning-still-leans-on-super</image:loc>
      <image:title>An empty developmental assessment room in a university clinic, with wooden play materials on a low table and a one-way observation window</image:title>
    </image:image>
    <news:news>
      <news:publication>
        <news:name>AI Understanding</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-08-23T16:14:15.568Z</news:publication_date>
      <news:title>Systematic review of 55 studies finds autism machine learning still leans on supervised models</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://aiunderstanding.org/news/preprint-ties-model-uncertainty-to-the-label-tree-reporting-about-half-the-calibra</loc>
    <image:image>
      <image:loc>https://aiunderstanding.org/api/news/image/preprint-ties-model-uncertainty-to-the-label-tree-reporting-about-half-the-calibra</image:loc>
      <image:title>Primary-source image accompanying Preprint ties model uncertainty to the label tree, reporting about half the calibration error</image:title>
    </image:image>
    <news:news>
      <news:publication>
        <news:name>AI Understanding</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-08-23T15:55:03.992Z</news:publication_date>
      <news:title>Preprint ties model uncertainty to the label tree, reporting about half the calibration error</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://aiunderstanding.org/news/preprint-reports-steering-representation-geometry-makes-brain-model-alignment-more</loc>
    <image:image>
      <image:loc>https://aiunderstanding.org/api/news/image/preprint-reports-steering-representation-geometry-makes-brain-model-alignment-more</image:loc>
      <image:title>Rack-mounted computing servers in a university research machine room, with bundled cables and perforated steel doors under overhead lighting</image:title>
    </image:image>
    <news:news>
      <news:publication>
        <news:name>AI Understanding</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-08-23T15:44:44.259Z</news:publication_date>
      <news:title>Preprint reports steering representation geometry makes brain–model alignment more two-way</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://aiunderstanding.org/news/preprint-proposes-batched-parallel-decoding-to-cut-training-time-for-compact-image</loc>
    <image:image>
      <image:loc>https://aiunderstanding.org/api/news/image/preprint-proposes-batched-parallel-decoding-to-cut-training-time-for-compact-image</image:loc>
      <image:title>Primary-source image accompanying Preprint proposes batched parallel decoding to cut training time for compact image-generation models</image:title>
    </image:image>
    <news:news>
      <news:publication>
        <news:name>AI Understanding</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-08-23T03:26:21.386Z</news:publication_date>
      <news:title>Preprint proposes batched parallel decoding to cut training time for compact image-generation models</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://aiunderstanding.org/news/philosophy-paper-argues-machine-learning-should-borrow-its-standards-of-proof-from</loc>
    <image:image>
      <image:loc>https://aiunderstanding.org/api/news/image/philosophy-paper-argues-machine-learning-should-borrow-its-standards-of-proof-from</image:loc>
      <image:title>Empty seminar room at a medical school in late afternoon, with a bare oak table, a wiped chalkboard and a glass cabinet of old apothecary bottles</image:title>
    </image:image>
    <news:news>
      <news:publication>
        <news:name>AI Understanding</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-08-23T03:22:43.672Z</news:publication_date>
      <news:title>Philosophy paper argues machine learning should borrow its standards of proof from clinical translation</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://aiunderstanding.org/news/preprint-casts-interpretability-tools-as-one-measurement-problem-tests-it-on-gpt-2</loc>
    <image:image>
      <image:loc>https://aiunderstanding.org/api/news/image/preprint-casts-interpretability-tools-as-one-measurement-problem-tests-it-on-gpt-2</image:loc>
      <image:title>Primary-source image accompanying Preprint casts interpretability tools as one measurement problem, tests it on GPT-2 and Qwen</image:title>
    </image:image>
    <news:news>
      <news:publication>
        <news:name>AI Understanding</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-08-23T02:48:24.089Z</news:publication_date>
      <news:title>Preprint casts interpretability tools as one measurement problem, tests it on GPT-2 and Qwen</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://aiunderstanding.org/news/preprint-proposes-a-continuous-alzheimer-s-severity-score-learned-from-repeated-br</loc>
    <image:image>
      <image:loc>https://aiunderstanding.org/api/news/image/preprint-proposes-a-continuous-alzheimer-s-severity-score-learned-from-repeated-br</image:loc>
      <image:title>Primary-source image accompanying Preprint proposes a continuous Alzheimer&apos;s severity score learned from repeated brain scans</image:title>
    </image:image>
    <news:news>
      <news:publication>
        <news:name>AI Understanding</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-08-23T02:35:34.604Z</news:publication_date>
      <news:title>Preprint proposes a continuous Alzheimer&apos;s severity score learned from repeated brain scans</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://aiunderstanding.org/news/preprint-reports-physics-informed-network-gains-came-from-one-pairing-broke-when-s</loc>
    <image:image>
      <image:loc>https://aiunderstanding.org/api/news/image/preprint-reports-physics-informed-network-gains-came-from-one-pairing-broke-when-s</image:loc>
      <image:title>Primary-source image accompanying Preprint reports physics-informed network gains came from one pairing, broke when stacked</image:title>
    </image:image>
    <news:news>
      <news:publication>
        <news:name>AI Understanding</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-08-23T02:15:43.904Z</news:publication_date>
      <news:title>Preprint reports physics-informed network gains came from one pairing, broke when stacked</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://aiunderstanding.org/news/paper-says-a-recommender-trained-only-on-synthetic-clickstreams-leads-zero-shot-be</loc>
    <image:image>
      <image:loc>https://aiunderstanding.org/api/news/image/paper-says-a-recommender-trained-only-on-synthetic-clickstreams-leads-zero-shot-be</image:loc>
      <image:title>Primary-source image accompanying Paper says a recommender trained only on synthetic clickstreams leads zero-shot benchmarks</image:title>
    </image:image>
    <news:news>
      <news:publication>
        <news:name>AI Understanding</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-08-23T02:09:20.146Z</news:publication_date>
      <news:title>Paper says a recommender trained only on synthetic clickstreams leads zero-shot benchmarks</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://aiunderstanding.org/news/deltaml-bench-finds-agent-scaffolding-changes-success-on-machine-learning-research</loc>
    <image:image>
      <image:loc>https://aiunderstanding.org/api/news/image/deltaml-bench-finds-agent-scaffolding-changes-success-on-machine-learning-research</image:loc>
      <image:title>Primary-source image accompanying DeltaML-Bench finds agent scaffolding changes success on machine-learning research tasks</image:title>
    </image:image>
    <news:news>
      <news:publication>
        <news:name>AI Understanding</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-08-23T01:36:16.880Z</news:publication_date>
      <news:title>DeltaML-Bench finds agent scaffolding changes success on machine-learning research tasks</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://aiunderstanding.org/news/preprint-proposes-answer-level-trust-checks-for-physical-vision-language-model-pre</loc>
    <image:image>
      <image:loc>https://aiunderstanding.org/api/news/image/preprint-proposes-answer-level-trust-checks-for-physical-vision-language-model-pre</image:loc>
      <image:title>Primary-source image accompanying Preprint proposes answer-level trust checks for physical vision-language model predictions</image:title>
    </image:image>
    <news:news>
      <news:publication>
        <news:name>AI Understanding</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-08-23T01:34:19.394Z</news:publication_date>
      <news:title>Preprint proposes answer-level trust checks for physical vision-language model predictions</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://aiunderstanding.org/news/preprint-audit-finds-common-credit-signals-fail-to-identify-causally-important-ste</loc>
    <image:image>
      <image:loc>https://aiunderstanding.org/api/news/image/preprint-audit-finds-common-credit-signals-fail-to-identify-causally-important-ste</image:loc>
      <image:title>Blank index cards arranged in branching rows on a wooden table in an empty university laboratory.</image:title>
    </image:image>
    <news:news>
      <news:publication>
        <news:name>AI Understanding</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-08-23T01:28:34.492Z</news:publication_date>
      <news:title>Preprint audit finds common credit signals fail to identify causally important steps in LLM agents</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://aiunderstanding.org/news/preprint-proposes-adaptive-safety-shields-for-reinforcement-learning-agents</loc>
    <image:image>
      <image:loc>https://aiunderstanding.org/api/news/image/preprint-proposes-adaptive-safety-shields-for-reinforcement-learning-agents</image:loc>
      <image:title>Primary-source image accompanying Preprint proposes adaptive safety shields for reinforcement-learning agents</image:title>
    </image:image>
    <news:news>
      <news:publication>
        <news:name>AI Understanding</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-08-23T01:26:23.148Z</news:publication_date>
      <news:title>Preprint proposes adaptive safety shields for reinforcement-learning agents</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://aiunderstanding.org/news/paper-outlines-assurance-path-for-an-onboard-ml-helicopter-weight-estimator</loc>
    <image:image>
      <image:loc>https://aiunderstanding.org/api/news/image/paper-outlines-assurance-path-for-an-onboard-ml-helicopter-weight-estimator</image:loc>
      <image:title>An unmarked helicopter resting on industrial weighing platforms inside a maintenance hangar.</image:title>
    </image:image>
    <news:news>
      <news:publication>
        <news:name>AI Understanding</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-08-23T01:25:08.315Z</news:publication_date>
      <news:title>Paper outlines assurance path for an onboard ML helicopter-weight estimator</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://aiunderstanding.org/news/deltamomentum-paper-proposes-direction-aware-optimizer-updates-for-neural-network</loc>
    <image:image>
      <image:loc>https://aiunderstanding.org/api/news/image/deltamomentum-paper-proposes-direction-aware-optimizer-updates-for-neural-network</image:loc>
      <image:title>Unbranded GPU servers and cooling hardware in an academic machine-learning lab equipment room</image:title>
    </image:image>
    <news:news>
      <news:publication>
        <news:name>AI Understanding</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-08-23T01:23:03.334Z</news:publication_date>
      <news:title>DeltaMomentum paper proposes direction-aware optimizer updates for neural-network training</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://aiunderstanding.org/news/transformer-study-estimates-days-before-severe-copd-flare-ups-from-home-ventilator</loc>
    <image:image>
      <image:loc>https://aiunderstanding.org/api/news/image/transformer-study-estimates-days-before-severe-copd-flare-ups-from-home-ventilator</image:loc>
      <image:title>Primary-source image accompanying Transformer study estimates days before severe COPD flare-ups from home-ventilator data</image:title>
    </image:image>
    <news:news>
      <news:publication>
        <news:name>AI Understanding</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-08-23T01:20:45.909Z</news:publication_date>
      <news:title>Transformer study estimates days before severe COPD flare-ups from home-ventilator data</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://aiunderstanding.org/news/preprint-proposes-a-two-hemisphere-architecture-for-continual-learning</loc>
    <image:image>
      <image:loc>https://aiunderstanding.org/api/news/image/preprint-proposes-a-two-hemisphere-architecture-for-continual-learning</image:loc>
      <image:title>Primary-source image accompanying Preprint proposes a two-hemisphere architecture for continual learning</image:title>
    </image:image>
    <news:news>
      <news:publication>
        <news:name>AI Understanding</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-08-23T01:03:10.278Z</news:publication_date>
      <news:title>Preprint proposes a two-hemisphere architecture for continual learning</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://aiunderstanding.org/news/paper-proposes-using-an-llm-to-generate-tabular-anomaly-detectors-from-normal-data</loc>
    <image:image>
      <image:loc>https://aiunderstanding.org/api/news/image/paper-proposes-using-an-llm-to-generate-tabular-anomaly-detectors-from-normal-data</image:loc>
      <image:title>Primary-source image accompanying Paper proposes using an LLM to generate tabular anomaly detectors from normal data</image:title>
    </image:image>
    <news:news>
      <news:publication>
        <news:name>AI Understanding</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-08-23T00:53:47.511Z</news:publication_date>
      <news:title>Paper proposes using an LLM to generate tabular anomaly detectors from normal data</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://aiunderstanding.org/news/eventtime-paper-proposes-ai-method-to-estimate-market-losses-after-cybersecurity-d</loc>
    <image:image>
      <image:loc>https://aiunderstanding.org/api/news/image/eventtime-paper-proposes-ai-method-to-estimate-market-losses-after-cybersecurity-d</image:loc>
      <image:title>Primary-source image accompanying EventTime paper proposes AI method to estimate market losses after cybersecurity disclosures</image:title>
    </image:image>
    <news:news>
      <news:publication>
        <news:name>AI Understanding</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-08-23T00:48:56.749Z</news:publication_date>
      <news:title>EventTime paper proposes AI method to estimate market losses after cybersecurity disclosures</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://aiunderstanding.org/news/preprint-proposes-a-low-cost-way-to-improve-confidence-estimates-for-black-box-llm</loc>
    <image:image>
      <image:loc>https://aiunderstanding.org/api/news/image/preprint-proposes-a-low-cost-way-to-improve-confidence-estimates-for-black-box-llm</image:loc>
      <image:title>Unbranded server cabinets and fiber-optic cables in a university AI research data-center room.</image:title>
    </image:image>
    <news:news>
      <news:publication>
        <news:name>AI Understanding</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-08-23T00:46:08.030Z</news:publication_date>
      <news:title>Preprint proposes a low-cost way to improve confidence estimates for black-box LLMs</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://aiunderstanding.org/news/fleetsieve-paper-proposes-targeted-profiling-for-slo-aware-llm-fleets</loc>
    <image:image>
      <image:loc>https://aiunderstanding.org/api/news/image/fleetsieve-paper-proposes-targeted-profiling-for-slo-aware-llm-fleets</image:loc>
      <image:title>Unbranded GPU server racks in a data-center aisle, illustrating LLM serving-fleet profiling</image:title>
    </image:image>
    <news:news>
      <news:publication>
        <news:name>AI Understanding</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-08-23T00:42:30.897Z</news:publication_date>
      <news:title>FleetSieve paper proposes targeted profiling for SLO-aware LLM fleets</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://aiunderstanding.org/news/sage-xgboost-paper-reports-stronger-landslide-and-wildfire-mapping-with-scarce-dat</loc>
    <image:image>
      <image:loc>https://aiunderstanding.org/api/news/image/sage-xgboost-paper-reports-stronger-landslide-and-wildfire-mapping-with-scarce-dat</image:loc>
      <image:title>Steep forested hillside above a dry valley, with exposed soil, rocks and a narrow drainage channel.</image:title>
    </image:image>
    <news:news>
      <news:publication>
        <news:name>AI Understanding</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-08-23T00:40:07.426Z</news:publication_date>
      <news:title>SAGE-XGBoost paper reports stronger landslide and wildfire mapping with scarce data</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://aiunderstanding.org/news/flashprefill-v2-paper-reports-large-long-context-serving-speedups-with-block-spars</loc>
    <image:image>
      <image:loc>https://aiunderstanding.org/api/news/image/flashprefill-v2-paper-reports-large-long-context-serving-speedups-with-block-spars</image:loc>
      <image:title>An empty server aisle with dense accelerator racks and organized cooling and network cabling in a large inference data center.</image:title>
    </image:image>
    <news:news>
      <news:publication>
        <news:name>AI Understanding</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-08-23T00:36:52.086Z</news:publication_date>
      <news:title>FlashPrefill V2 paper reports large long-context serving speedups with block-sparse attention</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://aiunderstanding.org/news/swe-bench-science-benchmark-finds-coding-agents-struggle-with-scientific-software</loc>
    <image:image>
      <image:loc>https://aiunderstanding.org/api/news/image/swe-bench-science-benchmark-finds-coding-agents-struggle-with-scientific-software</image:loc>
      <image:title>An empty university computational-science laboratory with unbranded computing and scientific equipment on a stainless-steel bench</image:title>
    </image:image>
    <news:news>
      <news:publication>
        <news:name>AI Understanding</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-08-23T00:25:45.366Z</news:publication_date>
      <news:title>SWE-bench Science benchmark finds coding agents struggle with scientific software</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://aiunderstanding.org/news/arxiv-paper-proposes-milestone-based-training-for-long-horizon-llm-agents</loc>
    <image:image>
      <image:loc>https://aiunderstanding.org/api/news/image/arxiv-paper-proposes-milestone-based-training-for-long-horizon-llm-agents</image:loc>
      <image:title>Primary-source image accompanying ArXiv paper proposes milestone-based training for long-horizon LLM agents</image:title>
    </image:image>
    <news:news>
      <news:publication>
        <news:name>AI Understanding</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-08-23T00:22:55.799Z</news:publication_date>
      <news:title>ArXiv paper proposes milestone-based training for long-horizon LLM agents</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://aiunderstanding.org/news/preprint-tests-whether-llm-agents-know-when-to-remember-verify-or-ask</loc>
    <image:image>
      <image:loc>https://aiunderstanding.org/api/news/image/preprint-tests-whether-llm-agents-know-when-to-remember-verify-or-ask</image:loc>
      <image:title>An empty university AI evaluation laboratory with an unbranded server rack and transparent trays of blank test cards on a stainless-steel workbench</image:title>
    </image:image>
    <news:news>
      <news:publication>
        <news:name>AI Understanding</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-08-23T00:20:34.047Z</news:publication_date>
      <news:title>Preprint tests whether LLM agents know when to remember, verify or ask</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://aiunderstanding.org/news/auditing-cross-lingual-fairness-in-language-model-watermarking</loc>
    <image:image>
      <image:loc>https://aiunderstanding.org/api/news/image/auditing-cross-lingual-fairness-in-language-model-watermarking</image:loc>
      <image:title>Primary-source image accompanying Auditing Cross-Lingual Fairness in Language Model Watermarking</image:title>
    </image:image>
    <news:news>
      <news:publication>
        <news:name>AI Understanding</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-08-23T00:18:50.899Z</news:publication_date>
      <news:title>Auditing Cross-Lingual Fairness in Language Model Watermarking</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://aiunderstanding.org/news/stanford-ai-index-finds-ai-policy-expanding-as-sovereignty-and-investment-diverge</loc>
    <image:image>
      <image:loc>https://aiunderstanding.org/api/news/image/stanford-ai-index-finds-ai-policy-expanding-as-sovereignty-and-investment-diverge</image:loc>
      <image:title>Primary-source image accompanying Stanford AI Index finds AI policy expanding as sovereignty and investment diverge</image:title>
    </image:image>
    <news:news>
      <news:publication>
        <news:name>AI Understanding</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-08-22T18:33:42.692Z</news:publication_date>
      <news:title>Stanford AI Index finds AI policy expanding as sovereignty and investment diverge</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://aiunderstanding.org/news/together-ai-benchmark-glm-5-3-trails-gpt-5-6-sol-on-the-first-try-wins-on-retries</loc>
    <image:image>
      <image:loc>https://aiunderstanding.org/api/news/image/together-ai-benchmark-glm-5-3-trails-gpt-5-6-sol-on-the-first-try-wins-on-retries</image:loc>
      <image:title>Rows of dark server cabinets filled with accelerator chassis in a data-hall aisle, with fiber cables running up to overhead ladder trays.</image:title>
    </image:image>
    <news:news>
      <news:publication>
        <news:name>AI Understanding</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-08-22T05:53:24.418Z</news:publication_date>
      <news:title>Together AI benchmark: GLM-5.3 trails GPT-5.6 Sol on the first try, wins on retries at half the price</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://aiunderstanding.org/news/preprint-proposes-a-locally-tokenized-ai-model-for-robust-time-series-watermarking</loc>
    <image:image>
      <image:loc>https://aiunderstanding.org/api/news/image/preprint-proposes-a-locally-tokenized-ai-model-for-robust-time-series-watermarking</image:loc>
      <image:title>Primary-source image accompanying Preprint proposes a locally tokenized AI model for robust time-series watermarking</image:title>
    </image:image>
    <news:news>
      <news:publication>
        <news:name>AI Understanding</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-08-22T00:59:12.480Z</news:publication_date>
      <news:title>Preprint proposes a locally tokenized AI model for robust time-series watermarking</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://aiunderstanding.org/news/natural-language-code-retrieval-for-1c-enterprise-an-open-benchmark-and-efficient</loc>
    <image:image>
      <image:loc>https://aiunderstanding.org/api/news/image/natural-language-code-retrieval-for-1c-enterprise-an-open-benchmark-and-efficient</image:loc>
      <image:title>A photograph of a computer screen displaying the 1C:Enterprise ecosystem, with code snippets and query-code pairs visible.</image:title>
    </image:image>
    <news:news>
      <news:publication>
        <news:name>AI Understanding</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-08-22T00:41:43.223Z</news:publication_date>
      <news:title>Natural Language Code Retrieval for 1C:Enterprise: An Open Benchmark and Efficient Bi-Encoder</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://aiunderstanding.org/news/time-series-retrieval-for-grounding-multimodal-language-models-in-remaining-useful</loc>
    <image:image>
      <image:loc>https://aiunderstanding.org/api/news/image/time-series-retrieval-for-grounding-multimodal-language-models-in-remaining-useful</image:loc>
      <image:title>Primary-source image accompanying Time-Series Retrieval for Grounding Multimodal Language Models in Remaining Useful Life</image:title>
    </image:image>
    <news:news>
      <news:publication>
        <news:name>AI Understanding</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-08-22T00:27:06.251Z</news:publication_date>
      <news:title>Time-Series Retrieval for Grounding Multimodal Language Models in Remaining Useful Life</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://aiunderstanding.org/news/nepali-english-preprint-text-only-ai-matched-multimodal-model-on-out-of-context-mi</loc>
    <image:image>
      <image:loc>https://aiunderstanding.org/api/news/image/nepali-english-preprint-text-only-ai-matched-multimodal-model-on-out-of-context-mi</image:loc>
      <image:title>Primary-source image accompanying Nepali-English preprint: text-only AI matched multimodal model on out-of-context misinformation benchmark</image:title>
    </image:image>
    <news:news>
      <news:publication>
        <news:name>AI Understanding</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-08-22T00:22:07.217Z</news:publication_date>
      <news:title>Nepali-English preprint: text-only AI matched multimodal model on out-of-context misinformation benchmark</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://aiunderstanding.org/news/preprint-finds-financial-ai-confidence-can-fail-when-text-changes</loc>
    <image:image>
      <image:loc>https://aiunderstanding.org/api/news/image/preprint-finds-financial-ai-confidence-can-fail-when-text-changes</image:loc>
      <image:title>An empty records-processing room with three separate stacks of unmarked paper on metal trays, representing financial filings, news material and social-media text being handled under different data conditions.</image:title>
    </image:image>
    <news:news>
      <news:publication>
        <news:name>AI Understanding</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-08-22T00:18:25.916Z</news:publication_date>
      <news:title>Preprint finds financial AI confidence can fail when text changes</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://aiunderstanding.org/news/can-conversational-ai-loosen-us-versus-them-boundaries</loc>
    <image:image>
      <image:loc>https://aiunderstanding.org/api/news/image/can-conversational-ai-loosen-us-versus-them-boundaries</image:loc>
      <image:title>A photograph of a person sitting in a room with a computer screen displaying a conversation with a large language model.</image:title>
    </image:image>
    <news:news>
      <news:publication>
        <news:name>AI Understanding</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-08-22T00:16:21.844Z</news:publication_date>
      <news:title>Can Conversational AI loosen Us-Versus-Them Boundaries?</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://aiunderstanding.org/news/preprint-finds-periodic-subject-changes-raise-judged-surprise-in-base-language-mod</loc>
    <image:image>
      <image:loc>https://aiunderstanding.org/api/news/image/preprint-finds-periodic-subject-changes-raise-judged-surprise-in-base-language-mod</image:loc>
      <image:title>Unbranded server cabinets and repeating groups of blank cards in an empty machine-learning laboratory</image:title>
    </image:image>
    <news:news>
      <news:publication>
        <news:name>AI Understanding</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-08-22T00:15:40.937Z</news:publication_date>
      <news:title>Preprint finds periodic subject changes raise judged surprise in base language models</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://aiunderstanding.org/news/preprint-reports-declining-diversity-in-llm-creative-outputs-over-three-years</loc>
    <image:image>
      <image:loc>https://aiunderstanding.org/api/news/image/preprint-reports-declining-diversity-in-llm-creative-outputs-over-three-years</image:loc>
      <image:title>Primary-source image accompanying Preprint reports declining diversity in LLM creative outputs over three years</image:title>
    </image:image>
    <news:news>
      <news:publication>
        <news:name>AI Understanding</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-08-22T00:11:42.314Z</news:publication_date>
      <news:title>Preprint reports declining diversity in LLM creative outputs over three years</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://aiunderstanding.org/news/paper-reports-a-fine-tuning-method-for-long-context-ai-with-sparse-attention</loc>
    <image:image>
      <image:loc>https://aiunderstanding.org/api/news/image/paper-reports-a-fine-tuning-method-for-long-context-ai-with-sparse-attention</image:loc>
      <image:title>An unbranded GPU server in a university research-computing lab, with exposed cooling hardware and coiled cables under cool dawn light.</image:title>
    </image:image>
    <news:news>
      <news:publication>
        <news:name>AI Understanding</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-08-22T00:09:16.651Z</news:publication_date>
      <news:title>Paper reports a fine-tuning method for long-context AI with sparse attention</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://aiunderstanding.org/news/google-cloud-details-codemender-ai-agent-for-code-vulnerability-remediation</loc>
    <image:image>
      <image:loc>https://aiunderstanding.org/api/news/image/google-cloud-details-codemender-ai-agent-for-code-vulnerability-remediation</image:loc>
      <image:title>Primary-source image accompanying Google Cloud Details CodeMender AI Agent for Code Vulnerability Remediation</image:title>
    </image:image>
    <news:news>
      <news:publication>
        <news:name>AI Understanding</news:name>
        <news:language>en</news:language>
      </news:publication>
      <news:publication_date>2026-08-21T21:58:16.651Z</news:publication_date>
      <news:title>Google Cloud Details CodeMender AI Agent for Code Vulnerability Remediation</news:title>
    </news:news>
  </url>
</urlset>