8 papers
MathMixup: Boosting LLM Mathematical Reasoning with Difficulty-Controllable Data Synthesis and Curriculum Learning
Xuchen Li, Jing Chen, Xuzhao Li +4
In mathematical reasoning tasks, the advancement of Large Language Models (LLMs) relies heavily on high-quality training data with clearly defined and well-graded difficulty levels…
SciAgent: A Unified Multi-Agent System for Generalistic Scientific Reasoning
Xuchen Li, Ruitao Wu, Xuanbo Liu +17
Recent advances in large language models have enabled AI systems to achieve expert-level performance on domain-specific scientific tasks, yet these systems remain narrow and handcr…
MorphoBench: A Benchmark with Difficulty Adaptive to Model Reasoning
Xukai Wang, Xuanbo Liu, Mingrui Chen +16
With the advancement of powerful large-scale reasoning models, effectively evaluating the reasoning capabilities of these models has become increasingly important. However, existin…
CapGeo: A Caption-Assisted Approach to Geometric Reasoning
Yuying Li, Siyi Qian, Hao Liang +4
Geometric reasoning remains a core challenge for Multimodal Large Language Models (MLLMs). Even the most advanced closed-source systems, such as GPT-O3 and Gemini-2.5-Pro, still st…
DARO: Difficulty-Aware Reweighting Policy Optimization
Jingyu Zhou, Lu Ma, Hao Liang +3
Recent advances in large language models (LLMs) have shown that reasoning ability can be significantly enhanced through Reinforcement Learning with Verifiable Rewards (RLVR). Group…
Multimodal Reasoning for Science: Technical Report and 1st Place Solution to the ICML 2025 SeePhys Challenge
Hao Liang, Ruitao Wu, Bohan Zeng +3
Multimodal reasoning remains a fundamental challenge in artificial intelligence. Despite substantial advances in text-based reasoning, even state-of-the-art models such as GPT-o3 s…