activity
20232026
most citedEvaluating Large Language Models: A Comprehensive Survey

63 citations · 73 across the 13 of their papers we have counts for

collaborators

13 papers

cs.CL2026

D2VBench: Benchmarking Large Language Models with Value Dilemmas in Daily Scenarios

Siyi Hao, Yidi Cao, Linhao Yu +2

With the wide application of large language models (LLMs) in real-world scenarios, the value implication of their outputs is crucial. However, existing evaluation benchmarks suffer…

cs.CL2026

Beyond Value Benchmarks: Measuring Value-Structure Alignment in Large Language Models via Symmetric Q-Sorts

Jingting Zheng, Yuqi Ren, Linhao Yu +2

Large Language Models (LLMs) are increasingly deployed in contexts requiring complex moral reasoning and value trade-offs. However, existing evaluations typically rely on item-leve…

cs.AI2026

KnowRL: Boosting LLM Reasoning via Reinforcement Learning with Minimal-Sufficient Knowledge Guidance

Linhao Yu, Tianmeng Yang, Siyu Ding +8

RLVR improves reasoning in large language models, but its effectiveness is often limited by severe reward sparsity on hard problems. Recent hint-based RL methods mitigate sparsity…

cs.CL2026

ATTNPO: Attention-Guided Process Supervision for Efficient Reasoning

Shuaiyi Nie, Siyu Ding, Wenyuan Zhang +7

Large reasoning models trained with reinforcement learning and verifiable rewards (RLVR) achieve strong performance on complex reasoning tasks, yet often overthink, generating redu…

cs.AI2024★ 3 cited

Large Language Model Safety: A Holistic Survey

Dan Shi, Tianhao Shen, Yufei Huang +10

The rapid development and deployment of large language models (LLMs) have introduced a new frontier in artificial intelligence, marked by unprecedented capabilities in natural lang…

cs.CL2024

Self-Pluralising Culture Alignment for Large Language Models

Shaoyang Xu, Yongqi Leng, Linhao Yu +1

As large language models (LLMs) become increasingly accessible in many countries, it is essential to align them to serve pluralistic human values across cultures. However, pluralis…

cs.CL2024

CMoralEval: A Moral Evaluation Benchmark for Chinese Large Language Models

Linhao Yu, Yongqi Leng, Yufei Huang +9

What a large language model (LLM) would respond in ethically relevant context? In this paper, we curate a large benchmark CMoralEval for morality evaluation of Chinese LLMs. The da…

cs.CL2024

FuxiTranyu: A Multilingual Large Language Model Trained with Balanced Data

Haoran Sun, Renren Jin, Shaoyang Xu +10

Large language models (LLMs) have demonstrated prowess in a wide range of tasks. However, many LLMs exhibit significant performance discrepancies between high- and low-resource lan…

cs.CL2024

LFED: A Literary Fiction Evaluation Dataset for Large Language Models

Linhao Yu, Qun Liu, Deyi Xiong

The rapid evolution of large language models (LLMs) has ushered in the need for comprehensive assessments of their performance across various dimensions. In this paper, we propose…

cs.CL2024

OpenEval: Benchmarking Chinese LLMs across Capability, Alignment and Safety

Chuang Liu, Linhao Yu, Jiaxuan Li +11

The rapid development of Chinese large language models (LLMs) poses big challenges for efficient LLM evaluation. While current initiatives have introduced new benchmarks or evaluat…

cs.CL2024

Identifying Multiple Personalities in Large Language Models with External Evaluation

Xiaoyang Song, Yuta Adachi, Jessie Feng +6

As Large Language Models (LLMs) are integrated with human daily applications rapidly, many societal and ethical concerns are raised regarding the behavior of LLMs. One of the ways…

cs.CL2023★ 63 cited

Evaluating Large Language Models: A Comprehensive Survey

Zishan Guo, Renren Jin, Chuang Liu +8

Large language models (LLMs) have demonstrated remarkable capabilities across a broad spectrum of tasks. They have attracted significant attention and been deployed in numerous dow…

cs.CL2023★ 7 cited

M3KE: A Massive Multi-Level Multi-Subject Knowledge Evaluation Benchmark for Chinese Large Language Models

Chuang Liu, Renren Jin, Yuqi Ren +10

Large language models have recently made tremendous progress in a variety of aspects, e.g., cross-task generalization, instruction following. Comprehensively evaluating the capabil…