activity
20242026
most citedBEATS: Optimizing LLM Mathematical Capabilities with BackVerify and Adaptive Disambiguate based Efficient Tree Search

2 citations · 5 across the 12 of their papers we have counts for

collaborators

12 papers

cs.AI2026

Repo2Skill-Evo: Repository Skills Go Stale in Silence

Chenyuan Duan, Ge Shi, Zineng Mao +10

Large language model (LLM) agents increasingly operate over evolving software repositories, where success depends on repository-specific procedural knowledge: which APIs to call, w…

cs.CL2026

WorkSurface-Bench: Benchmarking Enterprise Agents on Multi-Surface Knowledge Routing

Hao Liang, Meiyi Qiang, Sizhe Qiu +2

Enterprise agents often need to integrate heterogeneous knowledge sources: documents for narrative facts, tables for computation, and dependency graphs for file relationships. Exis…

cs.LG2026

DataPrep-Bench: Benchmarking LLMs as Training Data Preparators

Hao Liang, Qifeng Cai, Yibo Lin +11

The quality of training data fundamentally determines the capabilities of large language models (LLMs), yet no unified benchmark exists to measure how well LLMs, agents, and data-c…

cs.CL2026

K12-KGraph: A Curriculum-Aligned Knowledge Graph for Benchmarking and Training Educational LLMs

Hao Liang, Qihan Lin, Zhaoyang Han +5

Large language models are increasingly used in K-12 education, but existing benchmarks mainly test exam question answering rather than understanding how curriculum knowledge is str…

cs.SD2025

BRACE: A Benchmark for Robust Audio Caption Quality Evaluation

Tianyu Guo, Hongyu Chen, Hao Liang +5

Automatic audio captioning is essential for audio understanding, enabling applications such as accessibility and content indexing. However, evaluating the quality of audio captions…

cs.DB2025

Rethinking Text-to-SQL: Dynamic Multi-turn SQL Interaction for Real-world Database Exploration

Linzhuang Sun, Tianyu Guo, Hao Liang +6

Recent advances in Text-to-SQL have achieved strong results in static, single-turn tasks, where models generate SQL queries from natural language questions. However, these systems…