Cover Image

From Data to Knowledge: Evaluating How Efficiently Language Models Learn Facts

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Christoph, Daniel, Ploner, Max, Haller, Patrick, Akbik, Alan
Format:	Preprint
Published:	2025
Subjects:	Computation and Language Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

BEAR: A Unified Framework for Evaluating Relational Knowledge in Causal and Masked Language Models
by: Wiland, Jacek, et al.
Published: (2024)

Towards a Principled Evaluation of Knowledge Editors
by: Pohl, Sebastian, et al.
Published: (2025)

TransformerRanker: A Tool for Efficiently Finding the Best-Suited Language Models for Downstream Classification Tasks
by: Garbas, Lukas, et al.
Published: (2024)

LM-PUB-QUIZ: A Comprehensive Framework for Zero-Shot Evaluation of Relational Knowledge in Language Models
by: Ploner, Max, et al.
Published: (2024)

Familiarity: Better Evaluation of Zero-Shot Named Entity Recognition by Quantifying Label Shifts in Synthetic Training Data
by: Golde, Jonas, et al.
Published: (2024)

Repetition over Diversity: High-Signal Data Filtering for Sample-Efficient German Language Modeling
by: Aynetdinov, Ansar, et al.
Published: (2026)

BabyHGRN: Exploring RNNs for Sample-Efficient Training of Language Models
by: Haller, Patrick, et al.
Published: (2024)

Sample-Efficient Language Modeling with Linear Attention and Lightweight Enhancements
by: Haller, Patrick, et al.
Published: (2025)

Less is More: Parameter-Efficient Selection of Intermediate Tasks for Transfer Learning
by: Schulte, David, et al.
Published: (2024)

What Matters in Linearizing Language Models? A Comparative Study of Architecture, Scale, and Task Adaptation
by: Haller, Patrick, et al.
Published: (2025)

What Matters When Building Universal Multilingual Named Entity Recognition Models?
by: Golde, Jonas, et al.
Published: (2026)

FiNERweb: Datasets and Artifacts for Scalable Multilingual Named Entity Recognition
by: Golde, Jonas, et al.
Published: (2025)

From Facts to Folklore: Evaluating Large Language Models on Bengali Cultural Knowledge
by: Chowdhury, Nafis, et al.
Published: (2025)

Fact or Guesswork? Evaluating Large Language Models' Medical Knowledge with Structured One-Hop Judgments
by: Li, Jiaxi, et al.
Published: (2025)

NoiseBench: Benchmarking the Impact of Real Label Noise on Named Entity Recognition
by: Merdjanovska, Elena, et al.
Published: (2024)

Self-Aware Knowledge Probing: Evaluating Language Models' Relational Knowledge through Confidence Calibration
by: Kissling, Christopher, et al.
Published: (2026)

Medical Coding with Biomedical Transformer Ensembles and Zero/Few-shot Learning
by: Ziletti, Angelo, et al.
Published: (2022)

MastermindEval: A Simple But Scalable Reasoning Benchmark
by: Golde, Jonas, et al.
Published: (2025)

From Style to Facts: Mapping the Boundaries of Knowledge Injection with Finetuning
by: Zhao, Eric, et al.
Published: (2025)

On the Generalizability of "Competition of Mechanisms: Tracing How Language Models Handle Facts and Counterfactuals"
by: Dotsinski, Asen, et al.
Published: (2025)

LLM Knowledge is Brittle: Truthfulness Representations Rely on Superficial Resemblance
by: Haller, Patrick, et al.
Published: (2025)

Fabricator: An Open Source Toolkit for Generating Labeled Training Data with Teacher LLMs
by: Golde, Jonas, et al.
Published: (2023)

On Large Language Models' Hallucination with Regard to Known Facts
by: Jiang, Che, et al.
Published: (2024)

Unsupervised Pretraining for Fact Verification by Language Model Distillation
by: Bazaga, Adrián, et al.
Published: (2023)

Facts in Stats: Impacts of Pretraining Diversity on Language Model Generalization
by: Behnia, Tina, et al.
Published: (2025)

Summing Up the Facts: Additive Mechanisms Behind Factual Recall in LLMs
by: Chughtai, Bilal, et al.
Published: (2024)

Paying Attention to Facts: Quantifying the Knowledge Capacity of Attention Layers
by: Wong, Liang Ze
Published: (2025)

Data Efficient Evaluation of Large Language Models and Text-to-Image Models via Adaptive Sampling
by: Xu, Cong, et al.
Published: (2024)

Language Model-Driven Data Pruning Enables Efficient Active Learning
by: Azeemi, Abdul Hameed, et al.
Published: (2024)

Hallucination to Truth: A Review of Fact-Checking and Factuality Evaluation in Large Language Models
by: Rahman, Subhey Sadi, et al.
Published: (2025)

Language Model Knowledge Distillation for Efficient Question Answering in Spanish
by: Bazaga, Adrián, et al.
Published: (2023)

Fact or Fiction? Improving Fact Verification with Knowledge Graphs through Simplified Subgraph Retrievals
by: Opsahl, Tobias A.
Published: (2024)

Generative Frontiers: Why Evaluation Matters for Diffusion Language Models
by: Pynadath, Patrick, et al.
Published: (2026)

Automating Evaluation of Diffusion Model Unlearning with (Vision-) Language Model World Knowledge
by: Yeats, Eric, et al.
Published: (2025)

Procedural Knowledge in Pretraining Drives Reasoning in Large Language Models
by: Ruis, Laura, et al.
Published: (2024)

How to Leverage Demonstration Data in Alignment for Large Language Model? A Self-Imitation Learning Perspective
by: Xiao, Teng, et al.
Published: (2024)

Pre-Training Curriculum for Multi-Token Prediction in Language Models
by: Aynetdinov, Ansar, et al.
Published: (2025)

Are Large Language Models Table-based Fact-Checkers?
by: Zhang, Hanwen, et al.
Published: (2024)

Dataless Knowledge Fusion by Merging Weights of Language Models
by: Jin, Xisen, et al.
Published: (2022)

Evaluating Design Decisions for Dual Encoder-based Entity Disambiguation
by: Rücker, Susanna, et al.
Published: (2025)