8 papers
Beyond representational alignment with brain-guided language models for robust reasoning
Mingqing Xiao, Kai Du, Zhouchen Lin
The correspondence between large language models (LLMs) and the neural mechanisms underlying human higher-order cognition remains insufficiently characterized. Given that language…
ComBench: A Benchmark for Rigorous Proof Reasoning and Constructive Realization in Olympiad-Level Combinatorics
Shunkai Zhang, Haoran Zhang, Yun Luo +15
Combinatorics is central to Olympiad-level mathematical problem solving, requiring deep discrete reasoning, creative constructions, and rigorous structural insight. Recent evidence…
Achieving Gold-Medal-Level Olympiad Reasoning via Simple and Unified Scaling
Yafu Li, Runzhe Zhan, Haoran Zhang +25
Recent progress in reasoning models has substantially advanced long-horizon mathematical and scientific problem solving, with several systems now reaching gold-medal-level performa…
Proof-RM: A Scalable and Generalizable Reward Model for Math Proof
Haotong Yang, Zitong Wang, Shijia Kang +7
While Large Language Models (LLMs) have demonstrated strong math reasoning abilities through Reinforcement Learning with *Verifiable Rewards* (RLVR), many advanced mathematical pro…
LiteToken: Removing Intermediate Merge Residues From BPE Tokenizers
Yike Sun, Haotong Yang, Zhouchen Lin +1
Tokenization is fundamental to how language models represent and process text, yet the behavior of widely used BPE tokenizers has received far less study than model architectures a…
VACT: A Video Automatic Causal Testing System and a Benchmark
Haotong Yang, Qingyuan Zheng, Yunjian Gao +4
With the rapid advancement of text-conditioned Video Generation Models (VGMs), the quality of generated videos has significantly improved, bringing these models closer to functioni…