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From the 1 of 37 linked papers with an AI index.

collaborators

37 papers

cs.HC2026

Can Coding Agents Solve Repository-Level Issues with Rendered Code? An Exploratory Study of Visual Representations

Weijie Liang, Yuanfeng Song, Xing Chen +3

Visual modality has recently been explored as a way to compress textual tokens, including rendering code as images for static code understanding. We study whether this representati…

cs.AI2026

SkillProx: Self-Evolving Agent Skills via Proximal Textual Gradient Descent

Mingxuan Zheng, Yujin Zhou, Chuxue Cao +6

LLM agents increasingly adapt to recurring tasks by accumulating procedural knowledge in skills. These skills are lightweight, reusable textual artifacts that are loaded into the a…

cs.LG2026

Entropy-Preserving Supervised Fine-Tuning via Adaptive Self-Distillation for Large Reasoning Models

Hao Wang, Hao Gu, Hongming Piao +6

The paper introduces CurioSFT, an entropy-preserving supervised fine-tuning approach that uses adaptive self-distillation to keep exploration abilities in large reasoning models, l…

cs.LG2026

Pushing the Boundaries of Natural Reasoning: Interleaved Bonus from Formal-Logic Verification

Chuxue Cao, Jinluan Yang, Haoran Li +8

Large Language Models (LLMs) show remarkable capabilities, yet their stochastic next-token prediction creates logical inconsistencies and reward hacking that formal symbolic system…

cs.AI2026

Towards Advanced Mathematical Reasoning for LLMs via First-Order Logic Theorem Proving

Chuxue Cao, Mengze Li, Juntao Dai +7

Large language models (LLMs) have shown promising first-order logic (FOL) reasoning capabilities with applications in various areas. However, their effectiveness in complex mathema…

cs.AI2026

InsightEval: An Expert-Curated Benchmark for Assessing Insight Discovery in LLM-Driven Data Agents

Zhenghao Zhu, Yuanfeng Song, Xin Chen +5

Data analysis has become an indispensable part of scientific research. To discover the latent knowledge and insights hidden within massive datasets, we need to perform deep explora…