Factual Knowledge in Language Models

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Overview

This field studies which facts language models learn from training data, when they can retrieve them, and whether their answers match reliable evidence. Researchers use closed-book question-answering benchmarks such as SimpleQA and TruthfulQA, alongside multilingual, temporal, and long-tail tests; probing and causal tracing help investigate how knowledge is represented and accessed. Common interventions include retrieval-augmented generation, reinforcement learning, fine-tuning, and targeted knowledge editing. These methods can improve recall or update answers, but a central challenge is doing so without introducing hallucinations, losing other knowledge, or leaving gaps in unfamiliar languages, domains, and multi-step reasoning.

Latest papers

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195 papers36 papers in the last four weeks, up 57% on the four weeks before. 0.2% of all new papers.

  1. Relational Linearity is a Predictor of Hallucinations

    Jan 16, 2026Yuetian Lu, Yihong Liu, Sebastian Gerstner +3LLM InterpretabilityHallucination in Language Models

    Center for Information and Language Processing (CIS), LMU Munich · Ubiquitous Knowledge Processing Lab (UKP Lab), Technical University of Darmstadt · Munich Center for Machine Learning (MCML)

  2. Reinforcement Learning Improves Traversal of Parametric Knowledge in LLMs

    Nov 8, 2025Renfei Zhang, Manasa Kaniselvan, Rylan Schaeffer abd Niloofar MireshghallahRL for Language Model ReasoningFactual Knowledge in Language Models

    Carnegie Mellon University · MIT · Stanford University

  3. Multi-Step Knowledge Interaction Analysis via Rank-2 Subspace Disentanglement

    Nov 3, 2025Sekh Mainul Islam, Pepa Atanasova, Isabelle AugensteinDisentangled Representation LearningLLM Grounding

    University of Copenhagen

  4. KoSimpleQA: A Korean Factuality Benchmark with an Analysis of Reasoning LLMs

    Oct 21, 2025Donghyeon Ko, Kyubyung Chae, Yeguk Jin +6Multilingual Language Model EvaluationLLM Evaluation

    Naver Cloud · Graduate School of Data Science, Seoul National University

  5. Zoom In Disparities in Healthcare LLM Q&A

    Oct 20, 2025Ipek Baris Schlicht, Burcu Sayin, Zhixue Zhao +5Multilingual Language Model EvaluationKnowledge Augmentation for Language Models

    Universitat Politècnica de València, Valencia, Spain · University of Trento, Trento, Italy · University of Sheffield, Sheffield, UK +5

  6. Auditing a KB Elicitation of Frontier LLM Knowledge: A Multi-dimensional Analysis of GPTKB v1.5

    Oct 8, 2025Shrestha Ghosh, Luca Giordano, Yujia Hu +2Factual Knowledge in Language ModelsLLM Auditing

    University of Tübingen · ScaDS.AI & TU Dresden · VNU University of Engineering and Technology

  7. What and Whose Knowledge? Measuring Epistemic Diversity in Large Language Models

    Oct 5, 2025Dustin Wright, Sarah Masud, Jared Moore +5LLM EvaluationCultural Bias in Language Models

    University of Copenhagen · Stanford University · University of Colorado Boulder +1

  8. Sample, Align, Synthesize: Graph-Based Response Synthesis with ConGrs

    Oct 3, 2025Sayan Ghosh, Shahzaib Saqib Warraich, Dhruv Tarsadiya +2Text GenerationSelf-Consistency in Language Models

    Thomas Lord Department of Computer Science, University of Southern California

  9. KnowMT-Bench: Benchmarking Knowledge-Intensive Long-Form Question Answering in Multi-Turn Dialogues

    Sep 26, 2025Junhao Chen, Yu Huang, Siyuan Li +7Knowledge-Intensive QAFactual Knowledge in Language Models

    Hong Kong University of Science and Technology (Guangzhou) · The University of Osaka · Hong Kong University of Science and Technology

  10. LMEnt: A Suite for Analyzing Knowledge in Language Models from Pretraining Data to Representations

    Sep 3, 2025Daniela Gottesman, Alon Gilae-Dotan, Ido Cohen +4Language Model PretrainingKnowledge Editing

    Tel Aviv University · Mila – Quebec AI Institute & McGill University

  11. GPTKB v1.5: A Massive Knowledge Base for Exploring Factual LLM Knowledge

    Jul 8, 2025Yujia Hu, Tuan-Phong Nguyen, Shrestha Ghosh +2KG ConstructionLLM Information Extraction

    ScaDS.AI Dresden/Leipzig & TU Dresden, Germany · VNU University of Engineering and Technology, Hanoi, Vietnam · University of Tübingen, Germany

  12. Language Specific Knowledge: Do Models Know Better in X than in English?

    May 21, 2025Ishika Agarwal, Nimet Beyza Bozdag, Dilek Hakkani-TürMultilingual Language ModelsMultilingual QA

    Department of Computer Science University of Illinois, Urbana-Champaign

  13. Atomic Consistency Preference Optimization for Long-Form Question Answering

    May 14, 2025Jingfeng Chen, Raghuveer Thirukovalluru, Junlin Wang +2LLM Hallucination MitigationLLM Alignment

  14. Continual Memorization of Factoids in Language Models

    Nov 11, 2024Howard Chen, Jiayi Geng, Adithya Bhaskar +2Continual Learning for LLMsMemorization in Language Models

    Princeton Language and Intelligence (PLI), Princeton University

  15. All Entities are Not Created Equal: Examining the Long Tail for Ultra-Fine Entity Typing

    Oct 22, 2024Advait Deshmukh, Ashwin Umadi, Dananjay Srinivas +1Language Model PretrainingLong-Tail Learning

    University of Colorado Boulder