Data Provenance in Language Models

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48 papers26 papers in the last four weeks, up 767% on the four weeks before. 0.2% of all new papers.

SadaqahStories: A Verified English-Arabic Corpus of Charity Stories for Children, with an Audit of Errors in AI-Drafted Religious Narratives
Nov 9, 2026Wajdi Zaghouani, Spencer StrikerHallucination in Language Models Corpus Linguistics
Northwestern University in Qatar, Doha, Qatar
Building and Auditing Chemical Datasets with LLMs: A General LLM-as-a-Judge Framework Applied to Homogeneous Catalytic PET Depolymerisation
Nov 8, 2026Muhammad bin Javaid, Karim K. Ben Hicham, Enkhnyam Battulga +2LLM Information Extraction LLM Auditing
RWTH Aachen University, Chair of Logic and Theory of Discrete Systems, Aachen, Germany. · RWTH Aachen University, Process Systems Engineering (AVT.SVT), Aachen, Germany. · JARA-CSD, Aachen, Germany. +1
Audit Before You Merge: Provenance, Probing, and Continual LoRA Composition
Nov 7, 2026Lenny Aharon, Neta Glazer, Lior AharonLanguage Model Merging Catastrophic Forgetting
Columbia University, New York, NY, USA · Bar-Ilan University, Ramat Gan, Israel · MIT, Cambridge, MA, USA
AI in the Clinical Documentation Loop: Effects of LLM-Induced Note Bloat and Diagnostic Overcall on Downstream LLMs
Nov 7, 2026Jinghui Liu, Anthony Nguyen, Taylan GurgenciMedical LLMs LLM Reliability
Australian e-Health Research Centre, CSIRO · Mater Research Institute – University of Queensland · School of Medicine and Dentistry, Griffith University
Analyzing Code Provenance in LLMs for Programming Education
Nov 6, 2026Subhankar Maity, Faiza Belbachir, Omar Boucelma +1Data Provenance in Language Models Generative AI in Education
LyRIDS, ECE Research Center, Paris, France · Aix Marseille Univ, Université de Toulon, CNRS, LIS, Marseille, France
Reconstructing LLM Lineage Trees via Fine-Tuning Path Inference
Nov 6, 2026Sota Ogawa, Shojiro Yamabe, Daiki Nishiyama +1Data Provenance in Language Models LLM Auditing
Institute of Science Tokyo Tokyo, Japan · RIKEN
KeHoSu: Keyed Homoglyph Substitution for Authenticated Text Provenance over Copy-Paste Channels
Nov 5, 2026Andrei Alexandru Drăghici, Sediola Ruko, Briland Hitaj +1Text Watermarking Data Provenance in Language Models
Faculty of Mathematics and Informatics, University of Bucharest · Department of Computer Science, Sapienza University of Rome · Confidencial Inc
Embedding-Space Fingerprinting of LoRA Fine-Tunes: Recovering the Training-Data Domain from the Model Artifact Alone
Nov 5, 2026Shivesh RaneLanguage Model Fingerprinting Data Provenance in Language Models
Goa College of Engineering, Farmagudi, Ponda, Goa, India
Source-balanced Capped Fisher: Bounded Evidence Aggregation for User Inference in Language Models
Nov 4, 2026Yang Liu, Ran Zou, Wanrong ZhuLanguage Model Auditing Data Provenance in Language Models
Department of Statistics and Operations Research, University of North Carolina at Chapel Hill · Department of Statistics, University of California, Irvine
Reconciling Privacy with Provenance for Language Model Watermarks
Nov 4, 2026Elise L. Han, Tatsunori HashimotoLLM Watermarking Data Provenance in Language Models
Department of Computer Science Stanford University
FindLink: Learning to Assess Scientific Connections from Source-Grounded Premises
Nov 2, 2026Jingxuan Wei, Song Tan, Xiaohan Liu +6Scientific Reasoning in Language Models Evidence-Grounded QA
Qilu University of Technology · Shandong Computer Science Center · University of the Chinese Academy of Sciences +1
DuSE-Bench: Benchmarking Joint Reasoning over Evolving Dialogue and Documents
Oct 31, 2026Guanjie Cheng, Jianfeng Gao, Yufei Tong +2Evidence-Grounded QA Multi-Turn Dialogue Evaluation
Ningbo Global Innovation Center, Zhejiang University · School of Software Technology, Zhejiang University · College of Computer Science and Technology, Zhejiang University
The Knowledge Layer Model (KLM): Evidence-Visible AI Output, Routing Diagnostics, and Negative Results
Oct 30, 2026Omer Asim Ozturk, Cihan AydinerData Provenance in Language Models LLM Auditing
From Training Exposure to Membership Evidence: A Controlled Study of OLMo 2
Oct 30, 2026Ali Banaei, Muhammad Shahab Shahzad, Gerald Q. Maguire +2Privacy Leakage in Language Models Data Provenance in Language Models
KTH Royal Institute of Technology, Stockholm, Sweden
Elucidating the Design Space of LM Data Attribution
Oct 29, 2026Steven Yu, Sheng-Yu Wang, Kimia Hamidieh +2Training Data Attribution Gradient-Based Attribution
Northeastern University · MIT
Surprise Alone Learns Lies: Evidence-Gated Continual Learning for LLMs from Streaming Claims
Oct 29, 2026Abdelkader Metales, Miriam GrabenheinrichContinual Learning for LLMs LLM Reliability
caaise GmbH
Tracing the Influence of Retrieved Literature on Scientific Ideation in LLMs
Oct 28, 2026Zhipin Wang, Koel Dutta Chowdhury, Christoph Leiter +1Research Idea Generation Large Language Model-Guided Scientific Discovery
Beyond fabrication: Misattributed numbers in papers written by AI research agents
Oct 28, 2026Mosab Alfaqeeh, Omar Mohammed Horani, Mou'th Hourani +1Claim Verification AI Agent Auditing
Al-Ahliyya Amman University, Amman, Jordan · Binghamton University, State University of New York, Binghamton, NY, USA
What Carries Forward? Pretraining Disclosure Across Language Model Releases
Oct 27, 2026Md Sakib Ul Islam, S M Mehedi ZamanLLM Auditing Language Model Pretraining
Victorian Institute of Technology, Australia · Rutgers University, USA
Did the Model Use That? Counterfactual Training Boosts Self-Attribution in Language Models
Oct 26, 2026Zikai Zhou, Jiacheng Sang, Yilin Xu +2Data Provenance in Language Models Counterfactual Learning
Stanford University · Duke University · Emory University +1
Context or Knowledge: How LLMs Attribute Their Own Answers
Oct 23, 2026Kirill Afendulev, Alexey Dontsov, Alla Chepurova +2Claim Attribution in Language Models Data Provenance in Language Models
AgentTrace: Execution-Level Fingerprinting of Black-Box LLM Agents
Oct 23, 2026Gejian Zhao, Hanzhou Wu, Xinpeng ZhangLanguage Model Fingerprinting AI Agent Security
Shanghai University
Inherited, Not Invented: Tracing the Provenance of Wait in Reasoning Models
Oct 22, 2026Zhizhuo Kou, Sizai Hou, Long Chen +6RL for Language Model Reasoning Data Provenance in Language Models
The Hong Kong University of Science and Technology · Huawei Noah’s Ark Lab · Peking University
Conflicted Records: Typed Adversarial Contracts for Auditable LLM Output Quality Enforcement
Oct 21, 2026Kardelen Subasi, Jarosław A. ChudziakLLM Auditing LLM Hallucination Mitigation
Warsaw University of Technology, Warsaw, Poland
The World as Viewed by 136 Countries: An Open, Curated, Annotated, and Multilingual Dataset of 118 Million State Media Articles
Oct 18, 2026Bryan Li, Samar Haider, Grace Kim +6Political Bias in Language Models Data Provenance in Language Models
Google · Northwestern University · University of Pennsylvania +2
Recognizing Study Lineage Is Not Enough: Over-Crediting Same-Trial Evidence in LLM-Based Medical Verification
Oct 16, 2026Mukand Krishna, Anoushka Harit, Chenghao Xiao +1LLM Reliability LLM Answer Verification
School of Computing, University of Kent, UK · Cancer Research UK Cambridge Institute, University of Cambridge, UK · Shanghai University of Finance and Economics, China
Self-Reflective Chain-of-Thought (SRCoT): Evidence-Based Text Generation via a Closed-Loop Retrieve--Reflect--Revise Pipeline on Edge LLMs
Oct 16, 2026Fabian Broszio, Michael Hoffmann, Adrian PaschkeEvidence-Grounded Generation Self-Reflection in Language Model Agents
Department of Mathematics and Computer Science, Freie Universität Berlin, Arnimallee 14, Berlin, 14195, Germany.
Provenance-Aware Belief Updating in Human-AI Feedback Loops
Oct 9, 2026Tianyi Huang, Eric Liu, Jay Chong +2Data Provenance in Language Models Belief Updating in LLMs
Ryquo · App-In Club
Mine or Yours? Self-Other Confusion in Latent LLM Communication
Oct 8, 2026Yunlong XuClaim Attribution in Language Models Data Provenance in Language Models
University of Chicago
GraphEcho: Structural Redundancy and Evidence Provenance in LLM Graph Agents
Sep 15, 2026Sikun Wang, Yixi Zhou, Lei Fan +1Data Provenance in Language Models LLM Reasoning with Graphs
Tokyo University of Science · Hong Kong Baptist University · University of Michigan +1

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SadaqahStories: A Verified English-Arabic Corpus of Charity Stories for Children, with an Audit of Errors in AI-Drafted Religious Narratives

Wajdi Zaghouani, Spencer Striker

Northwestern University in Qatar, Doha, Qatar

Hallucination in Language Models Corpus Linguistics Data Provenance in Language Models

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We present SadaqahStories, a parallel English-Arabic corpus of 41 illustrated four-page stories about charitable giving in Islam (Sadaqah, Zakat and Waqf), written for readers aged 7 to 18. The stories were first drafted with large language model (LLM) assistance, then audited against hadith collections, Qur'an references and historical sources, and finally rewritten for children and signed off by an Islamic scholar. Every story carries an evidence label and links to its sources. We release all three versions of each story (AI-assisted draft, audited text, final child-oriented text) together with the correction log, so the corpus can be used to study how AI drafts of religious and historical content go wrong. The audit found substantive errors in 39 of the 41 drafts. The most frequent were unsupported specific details (dates, figures, prices, names), invented quotations, institutions or anecdotes, and conflation of separate events or people; six drafts contained errors in the wording, grading or ruling of a religious text. Rewriting cut the estimated Flesch-Kincaid grade of the English text from 14.0 to 6.1. We also release an 81-entry charity lexicon covering Modern Standard Arabic and Qatari Arabic, and describe the free, account-free website that serves the corpus (https://sadaqahjourney.com).