Cover Image

Comprehensive Reassessment of Large-Scale Evaluation Outcomes in LLMs: A Multifaceted Statistical Approach

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Sun, Kun, Wang, Rong, Søgaard, Anders
Format:	Preprint
Published:	2024
Subjects:	Computation and Language Artificial Intelligence Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Understanding Subword Compositionality of Large Language Models
by: Peng, Qiwei, et al.
Published: (2025)

Debiasing Multilingual LLMs in Cross-lingual Latent Space
by: Peng, Qiwei, et al.
Published: (2025)

From Words to Worlds: Compositionality for Cognitive Architectures
by: Dhar, Ruchira, et al.
Published: (2024)

CliBench: A Multifaceted and Multigranular Evaluation of Large Language Models for Clinical Decision Making
by: Ma, Mingyu Derek, et al.
Published: (2024)

MEG: Medical Knowledge-Augmented Large Language Models for Question Answering
by: Cabello, Laura, et al.
Published: (2024)

A Comprehensive Evaluation framework of Alignment Techniques for LLMs
by: Azmat, Muneeza, et al.
Published: (2025)

TIMIT Speaker Profiling: A Comparison of Multi-task learning and Single-task learning Approaches
by: Wang, Rong, et al.
Published: (2024)

Automatically Labeling Clinical Trial Outcomes: A Large-Scale Benchmark for Drug Development
by: Gao, Chufan, et al.
Published: (2024)

Position: Uncertainty Quantification Needs Reassessment for Large-language Model Agents
by: Kirchhof, Michael, et al.
Published: (2025)

Evaluating Adjective-Noun Compositionality in LLMs: Functional vs Representational Perspectives
by: Dhar, Ruchira, et al.
Published: (2026)

LLMs Are Not Intelligent Thinkers: Introducing Mathematical Topic Tree Benchmark for Comprehensive Evaluation of LLMs
by: Davoodi, Arash Gholami, et al.
Published: (2024)

Do Vision and Language Models Share Concepts? A Vector Space Alignment Study
by: Li, Jiaang, et al.
Published: (2023)

Retrieval Augmented Generation or Long-Context LLMs? A Comprehensive Study and Hybrid Approach
by: Li, Zhuowan, et al.
Published: (2024)

Towards a Comprehensive Scaling Law of Mixture-of-Experts
by: Zhao, Guoliang, et al.
Published: (2025)

Can LLMs Help Uncover Insights about LLMs? A Large-Scale, Evolving Literature Analysis of Frontier LLMs
by: Park, Jungsoo, et al.
Published: (2025)

Large Language Models Are Bad Dice Players: LLMs Struggle to Generate Random Numbers from Statistical Distributions
by: Zhao, Minda, et al.
Published: (2026)

Certifying Knowledge Comprehension in LLMs
by: Chaudhary, Isha, et al.
Published: (2024)

Evaluating the Factuality of Large Language Models using Large-Scale Knowledge Graphs
by: Liu, Xiaoze, et al.
Published: (2024)

CORE: Comprehensive Ontological Relation Evaluation for Large Language Models
by: Dwivedi, Satyam, et al.
Published: (2026)

Mission Impossible: A Statistical Perspective on Jailbreaking LLMs
by: Su, Jingtong, et al.
Published: (2024)

AutoScale: Scale-Aware Data Mixing for Pre-Training LLMs
by: Kang, Feiyang, et al.
Published: (2024)

Continual Learning of Large Language Models: A Comprehensive Survey
by: Shi, Haizhou, et al.
Published: (2024)

Empirical Evaluation of Progressive Coding for Sparse Autoencoders
by: Peter, Hans, et al.
Published: (2025)

Rethinking Scale: The Efficacy of Fine-Tuned Open-Source LLMs in Large-Scale Reproducible Social Science Research
by: Carammia, Marcello, et al.
Published: (2024)

A Large-Scale Benchmark for Evaluating Large Language Models on Medical Question Answering in Romanian
by: Rogoz, Ana-Cristina, et al.
Published: (2025)

Advancing Graph Representation Learning with Large Language Models: A Comprehensive Survey of Techniques
by: Mao, Qiheng, et al.
Published: (2024)

Scaling Laws for Predicting Downstream Performance in LLMs
by: Chen, Yangyi, et al.
Published: (2024)

Code Comprehension then Auditing for Unsupervised LLM Evaluation
by: Patel, Bhrij, et al.
Published: (2024)

A Comprehensive Survey of Electronic Health Record Modeling: From Deep Learning Approaches to Large Language Models
by: Ren, Weijieying, et al.
Published: (2025)

FBI-LLM: Scaling Up Fully Binarized LLMs from Scratch via Autoregressive Distillation
by: Ma, Liqun, et al.
Published: (2024)

A Simple and Effective Pruning Approach for Large Language Models
by: Sun, Mingjie, et al.
Published: (2023)

Time-R1: Towards Comprehensive Temporal Reasoning in LLMs
by: Liu, Zijia, et al.
Published: (2025)

AgentBench: Evaluating LLMs as Agents
by: Liu, Xiao, et al.
Published: (2023)

Model-GLUE: Democratized LLM Scaling for A Large Model Zoo in the Wild
by: Zhao, Xinyu, et al.
Published: (2024)

Self-Evaluating LLMs for Multi-Step Tasks: Stepwise Confidence Estimation for Failure Detection
by: Mavi, Vaibhav, et al.
Published: (2025)

Evaluating Large Language Models Using Contrast Sets: An Experimental Approach
by: Sanwal, Manish
Published: (2024)

IMAS: A Comprehensive Agentic Approach to Rural Healthcare Delivery
by: Gangavarapu, Agasthya, et al.
Published: (2024)

A Comprehensive Approach to Misspelling Correction with BERT and Levenshtein Distance
by: Naziri, Amirreza, et al.
Published: (2024)

On Evaluating LLM Alignment by Evaluating LLMs as Judges
by: Liu, Yixin, et al.
Published: (2025)

Evaluating Multimodal Language Models as Visual Assistants for Visually Impaired Users
by: Karamolegkou, Antonia, et al.
Published: (2025)