Cover Image

FreeEval: A Modular Framework for Trustworthy and Efficient Evaluation of Large Language Models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Yu, Zhuohao, Gao, Chang, Yao, Wenjin, Wang, Yidong, Zeng, Zhengran, Ye, Wei, Wang, Jindong, Zhang, Yue, Zhang, Shikun
Format:	Preprint
Published:	2024
Subjects:	Computation and Language Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

KIEval: A Knowledge-grounded Interactive Evaluation Framework for Large Language Models
by: Yu, Zhuohao, et al.
Published: (2024)

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation
by: Yu, Zhuohao, et al.
Published: (2024)

CodeShell Technical Report
by: Xie, Rui, et al.
Published: (2024)

CoderUJB: An Executable and Unified Java Benchmark for Practical Programming Scenarios
by: Zeng, Zhengran, et al.
Published: (2024)

A Survey on Evaluating Large Language Models in Code Generation Tasks
by: Chen, Liguo, et al.
Published: (2024)

PandaLM: An Automatic Evaluation Benchmark for LLM Instruction Tuning Optimization
by: Wang, Yidong, et al.
Published: (2023)

RewardAnything: Generalizable Principle-Following Reward Models
by: Yu, Zhuohao, et al.
Published: (2025)

RAGLAB: A Modular and Research-Oriented Unified Framework for Retrieval-Augmented Generation
by: Zhang, Xuanwang, et al.
Published: (2024)

Benchmarking and Studying the LLM-based Code Review
by: Zeng, Zhengran, et al.
Published: (2025)

ISC4DGF: Enhancing Directed Grey-box Fuzzing with LLM-Driven Initial Seed Corpus Generation
by: Xu, Yijiang, et al.
Published: (2024)

An Empirical Study on Influence-Based Pretraining Data Selection for Code Large Language Models
by: Xing, Chengli, et al.
Published: (2026)

Seed&Steer: Guiding Large Language Models with Compilable Prefix and Branch Signals for Unit Test Generation
by: Zhou, Shuaiyu, et al.
Published: (2025)

SparseEval: Efficient Evaluation of Large Language Models by Sparse Optimization
by: Zhang, Taolin, et al.
Published: (2026)

Supervised Knowledge Makes Large Language Models Better In-context Learners
by: Yang, Linyi, et al.
Published: (2023)

Benchmarking and Studying the LLM-based Agent System in End-to-End Software Development
by: Zeng, Zhengran, et al.
Published: (2025)

Hal-Eval: A Universal and Fine-grained Hallucination Evaluation Framework for Large Vision Language Models
by: Jiang, Chaoya, et al.
Published: (2024)

SAEMark: Steering Personalized Multilingual LLM Watermarks with Sparse Autoencoders
by: Yu, Zhuohao, et al.
Published: (2025)

AutoSurvey: Large Language Models Can Automatically Write Surveys
by: Wang, Yidong, et al.
Published: (2024)

A Survey on Evaluation of Large Language Models
by: Chang, Yupeng, et al.
Published: (2023)

PromptRobust: Towards Evaluating the Robustness of Large Language Models on Adversarial Prompts
by: Zhu, Kaijie, et al.
Published: (2023)

GALA: Multimodal Graph Alignment for Bug Localization in Automated Program Repair
by: Liu, Zhuoyao, et al.
Published: (2026)

SteerRM: Debiasing Reward Models via Sparse Autoencoders
by: Sun, Mengyuan, et al.
Published: (2026)

Mitigating Visual Context Degradation in Large Multimodal Models: A Training-Free Decoupled Agentic Framework
by: Jia, Hongrui, et al.
Published: (2025)

An Empirical Analysis of Uncertainty in Large Language Model Evaluations
by: Xie, Qiujie, et al.
Published: (2025)

AdaptEval: A Benchmark for Evaluating Large Language Models on Code Snippet Adaptation
by: Zhang, Tanghaoran, et al.
Published: (2026)

Claw-Eval: Towards Trustworthy Evaluation of Autonomous Agents
by: Ye, Bowen, et al.
Published: (2026)

TrustJudge: Inconsistencies of LLM-as-a-Judge and How to Alleviate Them
by: Wang, Yidong, et al.
Published: (2025)

Decoupling Safety into Orthogonal Subspace: Cost-Efficient and Performance-Preserving Alignment for Large Language Models
by: Mou, Yutao, et al.
Published: (2025)

OmniEvalKit: A Modular, Lightweight Toolbox for Evaluating Large Language Model and its Omni-Extensions
by: Zhang, Yi-Kai, et al.
Published: (2024)

VulnRepairEval: An Exploit-Based Evaluation Framework for Assessing Large Language Model Vulnerability Repair Capabilities
by: Wang, Weizhe, et al.
Published: (2025)

NPHardEval4V: Dynamic Evaluation of Large Vision-Language Models with Effects of Vision
by: Li, Xiang, et al.
Published: (2024)

Can You Really Trust Code Copilots? Evaluating Large Language Models from a Code Security Perspective
by: Mou, Yutao, et al.
Published: (2025)

TrustLLM: Trustworthiness in Large Language Models
by: Huang, Yue, et al.
Published: (2024)

DeepResearchEval: An Automated Framework for Deep Research Task Construction and Agentic Evaluation
by: Wang, Yibo, et al.
Published: (2026)

OpenHuEval: Evaluating Large Language Model on Hungarian Specifics
by: Yang, Haote, et al.
Published: (2025)

SG-Bench: Evaluating LLM Safety Generalization Across Diverse Tasks and Prompt Types
by: Mou, Yutao, et al.
Published: (2024)

Temporal Self-Rewarding Language Models: Decoupling Chosen-Rejected via Past-Future
by: Wang, Yidong, et al.
Published: (2025)

Conv-Adapter: Exploring Parameter Efficient Transfer Learning for ConvNets
by: Chen, Hao, et al.
Published: (2022)

MMEvalPro: Calibrating Multimodal Benchmarks Towards Trustworthy and Efficient Evaluation
by: Huang, Jinsheng, et al.
Published: (2024)

What Do Agents Learn from Trajectory-SFT: Semantics or Interfaces?
by: Gu, Weizheng, et al.
Published: (2026)