Papers Fact Checking
“Fact Checking” 태그가 달린 논문 693편 · 필터 해제
Agentic systems for breast cancer treatment recommendations
Large language models (LLMs) are increasingly being explored for clinical decision support, but their reliability in complex oncology treatment planning remains unclear. We evaluated agentic LLM systems for breast cancer…
Fact CheckingChecking Fact with Better Retrieval: Dynamic Contrastive Learning for Evidence Retrieval
In the field of multimodal fact checking, the accuracy of retrieving evidence from different modalities has a significant impact on the downstream claim verification process. Existing general multimodal retrieval methods…
Contrastive LearningSemantic RetrievalFact CheckingWhen AI reviews science: Can we trust the referee?
The volume of scientific submissions continues to climb, outpacing the capacity of qualified human referees and stretching editorial timelines. At the same time, modern large language models (LLMs) offer impressive capab…
Fact CheckingAfrIFact: Cultural Information Retrieval, Evidence Extraction and Fact Checking for African Languages
Assessing the veracity of a claim made online is a complex and important task with real-world implications. When these claims are directed at communities with limited access to information and the content concerns issues…
Information RetrievalFact CheckingLeveraging LLM Parametric Knowledge for Fact Checking without Retrieval
Trustworthiness is a core research challenge for agentic AI systems built on Large Language Models (LLMs). To enhance trust, natural language claims from diverse sources, including human-written text, web content, and mo…
Fact CheckingMarkovian ODE-guided scoring can assess the quality of offline reasoning traces in language models
Reasoning traces produced by generative language models are increasingly used for tasks ranging from mathematical problem solving to automated fact checking. However, existing evaluation methods remain largely mechanical…
Fact CheckingAnalyzing LLM Instruction Optimization for Tabular Fact Verification
Instruction optimization provides a lightweight, model-agnostic approach to enhancing the reasoning performance of large language models (LLMs). This paper presents the first systematic comparison of instruction optimiza…
Fact VerificationFact CheckingAIC CTU@AVerImaTeC: dual-retriever RAG for image-text fact checking
In this paper, we present our 3rd place system in the AVerImaTeC shared task, which combines our last year's retrieval-augmented generation (RAG) pipeline with a reverse image search (RIS) module. Despite its simplicity,…
Image RetrievalFact CheckingMeetBench-XL: Calibrated Multi-Dimensional Evaluation and Learned Dual-Policy Agents for Real-Time Meetings
Enterprise meeting environments require AI assistants that handle diverse operational tasks, from rapid fact checking during live discussions to cross meeting analysis for strategic planning, under strict latency, cost, …
Question AnsweringFact CheckingFactNet: A Billion-Scale Knowledge Graph for Multilingual Factual Grounding
Large language models hallucinate factual claims and struggle to ground their outputs in retrievable evidence, particularly in non-English languages. Existing resources impose a trade-off: structured knowledge bases lack…
Knowledge Graph CompletionQuestion AnsweringFact CheckingDR Tulu: Reinforcement Learning with Evolving Rubrics for Deep Research
Deep research agents perform multi-step research to produce long-form, well-attributed answers. However, most open deep research agents are trained on easily verifiable short-form QA tasks via reinforcement learning with…
Reinforcement LearningFact CheckingZoFia: Zero-Shot Fake News Detection with Entity-Guided Retrieval and Multi-LLM Interaction
The rapid spread of fake news threatens social stability and public trust, highlighting the urgent need for its effective detection. Although large language models (LLMs) show potential in fake news detection, they are l…
Fake News DetectionFact CheckingADMIT: Few-shot Knowledge Poisoning Attacks on RAG-based Fact Checking
Knowledge poisoning poses a critical threat to Retrieval-Augmented Generation (RAG) systems by injecting adversarial content into knowledge bases, tricking Large Language Models (LLMs) into producing attacker-controlled …
Fact CheckingAn Annotation Scheme for Factuality and its Application to Parliamentary Proceedings
Factuality assesses the extent to which a language utterance relates to real-world information; it determines whether utterances correspond to facts, possibilities, or imaginary situations, and as such, it is instrumenta…
Fact CheckingKnowledge Homophily in Large Language Models
Large Language Models (LLMs) have been increasingly studied as neural knowledge bases for supporting knowledge-intensive applications such as question answering and fact checking. However, the structural organization of …
Graph Neural NetworkQuestion AnsweringFact CheckingTableZoomer: A Collaborative Agent Framework for Large-scale Table Question Answering
While large language models (LLMs) have shown promise in the table question answering (TQA) task through prompt engineering, they face challenges in industrial applications, including structural heterogeneity, difficulti…
Prompt EngineeringQuestion AnsweringEntity LinkingFact CheckingEnhancing Health Fact-Checking with LLM-Generated Synthetic Data
Fact-checking for health-related content is challenging due to the limited availability of annotated training data. In this study, we propose a synthetic data generation pipeline that leverages large language models (LLM…
Synthetic Data GenerationData AugmentationFact CheckingDac-Fake: A Divide and Conquer Framework for Detecting Fake News on Social Media
With the rapid evolution of technology and the Internet, the proliferation of fake news on social media has become a critical issue, leading to widespread misinformation that can cause societal harm. Traditional fact che…
Fake News DetectionFact Checking+VeriRel: Verification Feedback to Enhance Document Retrieval for Scientific Fact Checking
Identification of appropriate supporting evidence is critical to the success of scientific fact checking. However, existing approaches rely on off-the-shelf Information Retrieval algorithms that rank documents based on r…
Information RetrievalDocument RankingFact CheckingMCP-Orchestrated Multi-Agent System for Automated Disinformation Detection
The large spread of disinformation across digital platforms creates significant challenges to information integrity. This paper presents a multi-agent system that uses relation extraction to detect disinformation in news…
Relation ExtractionPrompt EngineeringFact Checking