activity
20232026
most citedA Survey on Large Language Model (LLM) Security and Privacy: The Good, the Bad, and the Ugly

1k citations · 1k across the 14 of their papers we have counts for

collaborators

17 papers

cs.AI2026

Socratic Skill Learning: Interleaving Teaching and Practice for Transferable Agent Skills

Letian Zhu, Han Li, Yifan Yao +9

Agent Skills improve LLM agents by making task knowledge reusable across sessions. Learning transferable Skills requires evidence about a procedure and its conditions of use, which…

cs.SE2026

GameLogicBench: Evaluating Coding Agents on Runtime Game Logic with Tick-Level State Assertions

Xinyu Che, Yunfei Ge, Shihao Li +9

Coding agents can modify and test code across large software projects. Game development is a domain where agents must implement gameplay rules. A game can end in a valid state even…

cs.AI2026

CLI-Universe: Towards Verifiable Task Synthesis Engine for Terminal Agents

Zhanbo Hua, Yifan Yao, Weihao Xie +14

While recent LLM-based terminal agents have demonstrated promising capabilities, the scarcity of high-quality, executable training data remains a critical bottleneck. Existing synt…

cs.AI2026

Knowledge Index of Noah's Ark

Sheng Jin, Minghao Liu, Yunze Xiao +24

Knowledge benchmarks for LLMs face three issues: scaling-driven designs that do not operationalize disciplinary representativeness; flat-payment annotation that permits lazy consen…

cs.AI2026

Solvita: Enhancing Large Language Models for Competitive Programming via Agentic Evolution

Han Li, Jinyu Tian, Rili Feng +10

Large language models (LLMs) still struggle with the rigorous reasoning demands of hard competitive programming. While recent multi-agent frameworks attempt to bridge this reliabil…

cs.SE2026

WebCompass: Towards Multimodal Web Coding Evaluation for Code Language Models

Xinping Lei, Xinyu Che, Junqi Xiong +16

Large language models are rapidly evolving into interactive coding agents capable of end-to-end web coding, yet existing benchmarks evaluate only narrow slices of this capability,…

cs.SE2026

CodeTracer: Towards Traceable Agent States

Han Li, Yifan Yao, Letian Zhu +13

Code agents are advancing rapidly, but debugging them is becoming increasingly difficult. As frameworks orchestrate parallel tool calls and multi-stage workflows over complex tasks…

cs.SE2025

SWE-Compass: Towards Unified Evaluation of Agentic Coding Abilities for Large Language Models

Jingxuan Xu, Ken Deng, Weihao Li +36

Evaluating large language models (LLMs) for software engineering has been limited by narrow task coverage, language bias, and insufficient alignment with real-world developer workf…

cs.CL2025

KAT-Coder Technical Report

Zizheng Zhan, Ken Deng, Jinghui Wang +37

Recent advances in large language models (LLMs) have enabled progress in agentic coding, where models autonomously reason, plan, and act within interactive software development wor…

cs.CL2025

Falcon: A Comprehensive Chinese Text-to-SQL Benchmark for Enterprise-Grade Evaluation

Wenzhen Luo, Wei Guan, Yifan Yao +6

We introduce Falcon, a cross-domain Chinese text-to-SQL benchmark grounded in an enterprise-compatible dialect (MaxCompute/Hive). It contains 600 Chinese questions over 28 database…

cs.CV2025

IF-VidCap: Can Video Caption Models Follow Instructions?

Shihao Li, Yuanxing Zhang, Jiangtao Wu +20

Although Multimodal Large Language Models (MLLMs) have demonstrated proficiency in video captioning, practical applications require captions that follow specific user instructions…

cs.CL2025

HiPO: Hybrid Policy Optimization for Dynamic Reasoning in LLMs

Ken Deng, Zizheng Zhan, Wen Xiang +25

Large Language Models (LLMs) increasingly rely on Chain-of-Thought (CoT) reasoning to improve accuracy on complex tasks. However, always generating lengthy reasoning traces is inef…

cs.CL2025

CriticLean: Critic-Guided Reinforcement Learning for Mathematical Formalization

Zhongyuan Peng, Yifan Yao, Kaijing Ma +16

Translating natural language mathematical statements into formal, executable code is a fundamental challenge in automated theorem proving. While prior work has focused on generatio…

cs.CL2025

KORGym: A Dynamic Game Platform for LLM Reasoning Evaluation

Jiajun Shi, Jian Yang, Jiaheng Liu +26

Recent advancements in large language models (LLMs) underscore the need for more comprehensive evaluation methods to accurately assess their reasoning capabilities. Existing benchm…

cs.CV2025

IV-Bench: A Benchmark for Image-Grounded Video Perception and Reasoning in Multimodal LLMs

David Ma, Yuanxing Zhang, Jincheng Ren +17

Existing evaluation frameworks for Multimodal Large Language Models (MLLMs) primarily focus on image reasoning or general video understanding tasks, largely overlooking the signifi…

cs.CL2025★ 4 cited

SuperGPQA: Scaling LLM Evaluation across 285 Graduate Disciplines

P Team, Xinrun Du, Yifan Yao +94

Large language models (LLMs) have demonstrated remarkable proficiency in mainstream academic disciplines such as mathematics, physics, and computer science. However, human knowledg…

cs.CR2023★ 1k cited

A Survey on Large Language Model (LLM) Security and Privacy: The Good, the Bad, and the Ugly

Yifan Yao, Jinhao Duan, Kaidi Xu +3

Large Language Models (LLMs), such as ChatGPT and Bard, have revolutionized natural language understanding and generation. They possess deep language comprehension, human-like text…