6 papers
LDC: Learning to Generate Research Idea with Dynamic Control
Ruochen Li, Liqiang Jing, Chi Han +2
Recent advancements in large language models (LLMs) have demonstrated their potential in automating the scientific research ideation. Existing approaches primarily focus on prompti…
MLR-Copilot: Autonomous Machine Learning Research based on Large Language Models Agents
Ruochen Li, Teerth Patel, Qingyun Wang +1
Autonomous machine learning research has gained significant attention recently. We present MLR-COPILOT, an autonomous Machine Learning Research framework powered by large language…
AALC: Large Language Model Efficient Reasoning via Adaptive Accuracy-Length Control
Ruosen Li, Ziming Luo, Quan Zhang +4
Large reasoning models (LRMs) achieve impressive reasoning capabilities by generating lengthy chain-of-thoughts, but this "overthinking" incurs high latency and cost without commen…
LMR-BENCH: Evaluating LLM Agent's Ability on Reproducing Language Modeling Research
Shuo Yan, Ruochen Li, Ziming Luo +11
Large language model (LLM) agents have demonstrated remarkable potential in advancing scientific discovery. However, their capability in the fundamental yet crucial task of reprodu…
LLM4SR: A Survey on Large Language Models for Scientific Research
Ziming Luo, Zonglin Yang, Zexin Xu +2
In recent years, the rapid advancement of Large Language Models (LLMs) has transformed the landscape of scientific research, offering unprecedented support across various stages of…
IQA-EVAL: Automatic Evaluation of Human-Model Interactive Question Answering
Ruosen Li, Ruochen Li, Barry Wang +1
To evaluate Large Language Models (LLMs) for question answering (QA), traditional methods typically focus on assessing single-turn responses to given questions. However, this appro…