Diperbarui setiap hari3593 cerita terverifikasi
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9 ceritaInovasi
Researchers add a quantization layer to AI-based radio interference suppression
A new arXiv paper describes an AI system that combines an autoregressive transformer with a Finite Scalar Quantization tokenizer to suppress structured radio-frequency interference. The authors report lower latency and stronger interference rejection than traditional and earlier AI-based approaches, but provide no…arxiv.orgInovasi
Paper proposes lower-cost pruning for Transformer models during fine-tuning
REP-LIE estimates which Transformer weights to remove using gradients from LoRA low-rank matrices, aiming to reduce the resources required for model pruning and subsequent fine-tuning.arxiv.orgInovasi
Study identifies when neural-network surrogates improve optimization
A new arXiv preprint argues that neural-network surrogates help optimization only when they assist candidate selection within a bounded neighborhood and leave the underlying acceptance mechanism intact.arxiv.orgInovasi
AFDBench tests whether AI can write National Weather Service forecast discussions from weather data
A new preprint introduces AFDBench, a benchmark for testing whether language models can turn structured AI weather forecasts into accurate, professionally written National Weather Service discussions.arxiv.orgInovasi
Pracetak menjelaskan perubahan pembelajaran penguatan dalam model bahasa
Pracetak baru menguraikan pembelajaran penguatan pasca-pelatihan untuk model bahasa, memeriksa bagaimana penghargaan, petunjuk, skala model, dan perilaku sebelumnya membentuk hasil.arxiv.orgInovasi
MacroAgent uses LLM-designed heuristics to improve chip macro legalization
An arXiv preprint describes MacroAgent, a four-stage framework that uses large language models to discover contour algorithms for arranging large circuit components. The authors report improved layout regularity, shorter routed wirelength and better end-to-end results on TILOS, Chipyard and Cadence Innovus evaluations.arxiv.orgInovasi
Paper proposes adaptive graph-or-language handoffs for multi-agent LLMs
Routed Graph Handoff uses a lightweight language-model router to choose between structured dependency graphs and natural-language messages when AI agents delegate tasks.arxiv.orgInovasi
DataKernelBench tests whether LLMs can optimize GPU database queries
A new benchmark evaluates whether language models can generate and improve GPU code for database-style queries, with the paper reporting speedups of up to 2.11× on one H100 GPU and 2.54× across four H100 GPUs.arxiv.orgKeamanan
Paper reports bit-flip attack that can drive mixture-of-experts LLMs into long generation loops
A paper accepted at EMNLP 2026 reports that flipping routing-layer bits in mixture-of-experts language models can sharply inflate output length, potentially creating an availability and inference-cost risk.arxiv.org
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