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20242026
most citedA Survey on Large Language Model Benchmarks

2 citations · 2 across the 10 of their papers we have counts for

collaborators

10 papers

cs.SE2026

VibeMemBench: Evaluating Memory Systems for Coding Agents on Real Repository Coding Tasks

Liyang Fan, Yingcheng Shi, Yongbin Li +7

Coding agents operate on real repository coding tasks, and persistent memory systems promise to reuse experience across tasks. Yet existing evaluations do not show whether those sy…

cs.CL2026

SrDetection: A Self-Referential Framework for Data Leakage Detection in Code Large Language Models

Shuaimin Li, Liyang Fan, Zeyang Li +9

Evaluating code large language models (Code LLMs) requires reliable detection of data leakage, where benchmark performance is artificially inflated by exposure to benchmark data du…

cs.CL2025

DoPE: Denoising Rotary Position Embedding

Jing Xiong, Liyang Fan, Hui Shen +4

Positional encoding is essential for large language models (LLMs) to represent sequence order, yet recent studies show that Rotary Position Embedding (RoPE) can induce massive acti…

cs.CL2025

Automatic Paper Reviewing with Heterogeneous Graph Reasoning over LLM-Simulated Reviewer-Author Debates

Shuaimin Li, Liyang Fan, Yufang Lin +5

Existing paper review methods often rely on superficial manuscript features or directly on large language models (LLMs), which are prone to hallucinations, biased scoring, and limi…

cs.CL2025★ 2 cited

A Survey on Large Language Model Benchmarks

Shiwen Ni, Guhong Chen, Shuaimin Li +11

In recent years, with the rapid development of the depth and breadth of large language models' capabilities, various corresponding evaluation benchmarks have been emerging in incre…

cs.MA2025

Modeling Earth-Scale Human-Like Societies with One Billion Agents

Haoxiang Guan, Jiyan He, Liyang Fan +10

Understanding the dynamic evolution of complex social phenomena requires both high-fidelity modeling of human behavior and large-scale simulations. Traditional agent-based models (…

cs.CL2025

IPBench: Benchmarking the Knowledge of Large Language Models in Intellectual Property

Qiyao Wang, Guhong Chen, Hongbo Wang +20

Intellectual Property (IP) is a highly specialized domain that integrates technical and legal knowledge, making it inherently complex and knowledge-intensive. Recent advancements i…

cs.CL2025

xJailbreak: Representation Space Guided Reinforcement Learning for Interpretable LLM Jailbreaking

Sunbowen Lee, Shiwen Ni, Chi Wei +7

Safety alignment mechanism are essential for preventing large language models (LLMs) from generating harmful information or unethical content. However, cleverly crafted prompts can…

cs.CL2024

AgentCourt: Simulating Court with Adversarial Evolvable Lawyer Agents

Guhong Chen, Liyang Fan, Zihan Gong +8

Current research in LLM-based simulation systems lacks comprehensive solutions for modeling real-world court proceedings, while existing legal language models struggle with dynamic…

cs.CL2024

II-Bench: An Image Implication Understanding Benchmark for Multimodal Large Language Models

Ziqiang Liu, Feiteng Fang, Xi Feng +23

The rapid advancements in the development of multimodal large language models (MLLMs) have consistently led to new breakthroughs on various benchmarks. In response, numerous challe…