Tracked topic
Large language models are machine learning models trained to predict and generate text and other language-based outputs.
…Improving LLM-Authored Agent Skills via Trace-Conditioned Skill Revision (2026) Skills on the Fly: Test-Time Adaptive Skill Synthesis for LLM Agents (2026) SkillX: Automatically Constructing Skill Knowledge Bases for Agents…
…Generated by Qwen/Qwen2.5-Coder-32B-Instruct Prior work has shown that instruction-tuned large language models (LLMs) are less well calibrated than their base pre-trained counterparts. However, little is…
…Stronger Search Architectures Can Substitute for Larger LLMs in Evolutionary Search (2026) Quality-Diversity Evolution for Discovering Diverse Vulnerabilities in LLM Safety (2026) TurboEvolve: Towards Fast and Robust LLM-Driven Program Evolution…
…Tz-Huan Hsu , Jheng-Hong Yang , Abstract Lexical retrievers remain effective for deep research tasks when paired with advanced LLMs, outperforming dense retrievers in answer accuracy and evidence recall. AI-generated summary…
…A Comprehensive Survey of Rollout Strategies for LLM Reinforcement Learning Published on Apr 8 Submitted by Rohan Surana on May 6 McAuley-Lab Authors: Rohan Surana , , , , Zhenwei Tang , , , , , , , , , , , , , , Kuan-Hao Huang , , , Abstract…
…AI-generated summary Self-distillation (SD) offers a promising path for adapting large language models (LLMs) without relying on stronger external teachers. However, SD in autoregressive LLMs remains challenging because self-generated…
…SpeechEditBench provides a rigorous diagnostic framework to identify bottlenecks in Speech LLMs, thereby facilitating the development of next-generation Speech LLMs with more robust and precise instruction-guided editing capabilities. Data and…
…Deployment-Time Layer Profiling for Memory-Constrained LLM Inference (2026) The Illusion of Power Capping in LLM Decode: A Phase-Aware Energy Characterisation Across Attention Architectures (2026) Blink: CPU-Free LLM Inference…
…Internal-Signal Detection of Skill Poisoning in LLM Agents (2026) ARGUS: Defending LLM Agents Against Context-Aware Prompt Injection (2026) Please give a thumbs up to this comment if you found it…
…Sparse Decoupled Attention for Efficient Long-Context LLM Inference Published on Jun 3 Submitted by Yaosheng Fu on Jun 11 NVIDIA Authors: Yaosheng Fu , , , , Abstract SparDA is a decoupled sparse attention architecture…