Tracked topic
Large language models are machine learning models trained to predict and generate text and other language-based outputs.
Papers arxiv:2605.11458 Adaptive Teacher Exposure for Self-Distillation in LLM Reasoning Published on May 12 Submitted by hanhan3344 on May 15 ByteDance Authors: Zihao Han , Tiangang Zhang , , Abstract Adaptive Teacher…
…https://mobisoftinfotech.com/resources/blog/ai‑development/llm‑api‑pricing‑guide — which gives practical advice on LLM API usage, token‑based pricing, and how to plan costs when working with LLMs. Putting…
…Generated by Qwen/Qwen2.5-Coder-32B-Instruct Large language models (LLMs) offer a promising approach to machine translation (MT) for extremely low-resource languages by incorporating linguistic resources through in-context…
…Adaptive Reasoning Effort Selection for Efficient LLM Agents (2026) From Soliloquy to Agora: Memory-Enhanced LLM Agents with Decentralized Debate for Optimization Modeling (2026) Please give a thumbs up to this comment…
…Boosting LLM Reasoning via Negative Sample Projection Residual Reinforcement Learning Published on May 1 Submitted by zihan on May 7 Chinese Academic of Science Institute of Automation Authors: Zihan Lin , , , , , , , , Abstract ResRL…
…View arXiv page View PDF GitHub 2 Add to collection Community MergePipe is the first parameter management and execution system for large-scale LLM merging. It reframes LLM merging as a data…
…AI-generated summary In-context learning (ICL) adapts large language models (LLMs) to new tasks by conditioning on demonstrations in the prompt without parameter updates. With long-context models, many-shot ICL…
…Generated by Qwen/Qwen2.5-Coder-32B-Instruct Large language models (LLMs) are increasingly proposed as clinical agents , yet static, single-turn benchmarks cannot capture how a model dynamically delivers care across…
…As a first step, we introduce CreativityBench , a benchmark for evaluating affordance-based creativity in LLMs. To this end, we build a large-scale affordance knowledge base (KB) with 4K entities and…
…Model-Agnostic Experience Learning with Graph-Structured Memory for LLM Agents (2026) ARIADNE: Agentic Reward-Informed Adaptive Decision Exploration via Blackboard-Driven MCTS for Competitive Program Generation (2026) LLM as a Tool…