10 papers · 1 filter
Enhancing Multilingual Reasoning via Steerable Model Merging
Zhuoran Li, Rui Xu, Jian Yang +8
Model merging is an effective technique for composing the capabilities of a multilingual model and a reasoning model. It has achieved promising generalization in multilingual reaso…
OpenCompass: A Universal Evaluation Platform for Large Language Models
Maosong Cao, Kai Chen, Haodong Duan +27
In recent years, the field of artificial intelligence has undergone a paradigm shift from task-specific small-scale models to general-purpose large language models (LLMs). With the…
Rectifying LLM Thought from Lens of Optimization
Junnan Liu, Hongwei Liu, Songyang Zhang +1
Recent advancements in large language models (LLMs) have been driven by their emergent reasoning capabilities, particularly through long chain-of-thought (CoT) prompting, which ena…
ATLAS: A High-Difficulty, Multidisciplinary Benchmark for Frontier Scientific Reasoning
Hongwei Liu, Junnan Liu, Shudong Liu +33
The rapid advancement of Large Language Models (LLMs) has led to performance saturation on many established benchmarks, questioning their ability to distinguish frontier models. Co…
Dissecting Tool-Integrated Reasoning: An Empirical Study and Analysis
Yufeng Zhao, Junnan Liu, Hongwei Liu +4
Large Language Models (LLMs) have made significant strides in reasoning tasks through methods like chain-of-thought (CoT) reasoning. However, they often fall short in tasks requiri…
CompassVerifier: A Unified and Robust Verifier for LLMs Evaluation and Outcome Reward
Shudong Liu, Hongwei Liu, Junnan Liu +8
Answer verification is crucial not only for evaluating large language models (LLMs) by matching their unstructured outputs against standard answers, but also serves as the reward m…