Tracked topic
Large language models are machine learning models trained to predict and generate text and other language-based outputs.
…Behavioral Side Effects and Mechanistic Divergence Across LLM Jailbreaks (2026) LLUMI: Improving LLM Writing Assistance for Mental Health Support with Online Community Feedback (2026) Inform, Coach, Relate, Listen: Auditing LLM Caregiving Support…
…Mixture of Indexer Sparse Attention for Long-Context LLM Inference Published on May 8 Submitted by mengfanxu on May 11 Peking University Authors: , , , , , , Abstract MISA replaces the dense token-wise indexing in…
…AI-generated summary Self-evolving LLMs excel in verifiable domains but struggle in open-ended tasks, where reliance on proxy LLM judges introduces capability bottlenecks and reward hacking . To overcome this, we…
…Yet, recent progress in LLM coding has focused on well-defined tasks such as feature implementation, bug fixing, and competitive programming . Open-ended coding remains a weak spot for LLMs, largely because…
…We introduce a unified taxonomy of annotation-reporting practices and validate an LLM-assisted extraction pipeline against Annotated-gold , a human-adjudicated gold standard of 41 papers and 72 annotation tasks, where…
Papers arxiv:2606.03965 Agentic Chain-of-Thought Steering for Efficient and Controllable LLM Reasoning Published on Jun 2 Submitted by Yu Xia on Jun 4 University of California at San Diego…
…On the Human Alignment and Gameability of LLM Reviews,” we examine 1k real ACL 2025 submissions with real scores and reviews to test whether LLMs align with them. We find in our…
Great! I raised this issue with Qwen models a while ago :) https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard/discussions/942 Yep, it's now fixed :) 📻 🎙️ Hey, I made…
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