most citedMindStar: Enhancing Math Reasoning in Pre-trained LLMs at Inference Time

1 citations · 1 across the 4 of their papers we have counts for

collaborators

6 papers

cs.AI2026

From Memory to Guide: Spatio-Temporal Composer for Procedural Coding Memory

Zhixuan Tan, Pengjie Gu, Zhao Li +4

Memory-augmented agents typically integrate procedural knowledge by injecting retrieved skills directly into text prompts. This approach dangerously equates readable text with reli…

cs.SE2026

EngramBench: A Capability-Grounded Benchmark for Skill-Evolution Harnesses

Zhixuan Tan, Pengjie Gu, Zhao Li +4

While large language models have achieved remarkable success in isolated code generation, authentic software engineering requires sustained reasoning, complex state management, and…

cs.CL2026

Unveiling the Entropy Dynamics of Chain-of-Thought Reasoning

Ting Xu, Xu He, Yupu Lu +4

This paper investigates the entropy dynamics of Chain-of-Thought (CoT) and uncovers a consistent two-phase structure: an Uncertainty Region of exploration transitioning sharply to…

cs.MM2026

TimeLogic Challenge @ CVPR 2026: Strong MLLMs Meet Evidence-Seeking Agents for Temporal-Logic Video Question Answering

Zhaoyang Xu, Xusheng He, Wei Liu +2

Temporal-logic video question answering requires a model to reason about when actions occur relative to one another, such as before, after, until, since, overlap, and multi-event c…

stat.ML2024

Resultant: Incremental Effectiveness on Likelihood for Unsupervised Out-of-Distribution Detection

Yewen Li, Chaojie Wang, Xiaobo Xia +6

Unsupervised out-of-distribution (U-OOD) detection is to identify OOD data samples with a detector trained solely on unlabeled in-distribution (ID) data. The likelihood function es…

cs.LG2024★ 1 cited

MindStar: Enhancing Math Reasoning in Pre-trained LLMs at Inference Time

Jikun Kang, Xin Zhe Li, Xi Chen +9

Although Large Language Models (LLMs) achieve remarkable performance across various tasks, they often struggle with complex reasoning tasks, such as answering mathematical question…