conftrace_

hallucination detection

530 papers

Explore in graph

Co-occurring keywords

large language model (13587) retrieval-augmented generation (1592) text generation (2913) text classification (6793) uncertainty quantification (1393) natural language inference (1287) language model (4599) question answering (2963) benchmark evaluation (1556) fact verification (257)

Papers

BlueToad at SemEval-2025 Task 3: Using Question-Answering-Based Language Models to Extract Hallucinations from Machine-Generated Text SEMEVAL 2025
UMUTeam at SemEval-2025 Task 3: Detecting Hallucinations in Multilingual Texts Using Encoder-only Models Guided by Large Language Models SEMEVAL 2025
HalluRAG-RUG at SemEval-2025 Task 3: Using Retrieval-Augmented Generation for Hallucination Detection in Model Outputs SEMEVAL 2025
SmurfCat at SemEval-2025 Task 3: Bridging External Knowledge and Model Uncertainty for Enhanced Hallucination Detection SEMEVAL 2025
AILS-NTUA at SemEval-2025 Task 3: Leveraging Large Language Models and Translation Strategies for Multilingual Hallucination Detection SEMEVAL 2025
MALTO at SemEval-2025 Task 3: Detecting Hallucinations in LLMs via Uncertainty Quantification and Larger Model Validation SEMEVAL 2025
FunghiFunghi at SemEval-2025 Task 3: Mu-SHROOM, the Multilingual Shared-task on Hallucinations and Related Observable Overgeneration Mistakes SEMEVAL 2025
NLP_CIMAT at SemEval-2025 Task 3: Just Ask GPT or look Inside. A prompt and Neural Networks Approach to Hallucination Detection SEMEVAL 2025
Team Cantharellus at SemEval-2025 Task 3: Hallucination Span Detection with Fine Tuning on Weakly Supervised Synthetic Data SEMEVAL 2025
HausaNLP at SemEval-2025 Task 3: Towards a Fine-Grained Model-Aware Hallucination Detection SEMEVAL 2025
Swushroomsia at SemEval-2025 Task 3: Probing LLMs’ Collective Intelligence for Multilingual Hallucination Detection SEMEVAL 2025
UCSC at SemEval-2025 Task 3: Context, Models and Prompt Optimization for Automated Hallucination Detection in LLM Output SEMEVAL 2025
DUTJBD at SemEval-2025 Task 3: A Range of Approaches for Predicting Hallucination Generation in Models ACL 2025
YNU-HPCC at SemEval-2025 Task3: Leveraging Zero-Shot Learning for Halluciantion Detection SEMEVAL 2025
VerbaNexAI at SemEval-2025 Task 3: Fact Retrieval with Google Snippets for LLM Context Filtering to identify Hallucinations SEMEVAL 2025
TUM-MiKaNi at SemEval-2025 Task 3: Towards Multilingual and Knowledge-Aware Non-factual Hallucination Identification SEMEVAL 2025
GIL-IIMAS UNAM at SemEval-2025 Task 3: MeSSI: A Multilmodule System to detect hallucinated Segments in trivia-like Inquiries. SEMEVAL 2025
Howard University - AI4PC at SemEval-2025 Task 3: Logit-based Supervised Token Classification for Multilingual Hallucination Span Identification Using XGBOD ACL 2025
Consistency Is the Key: Detecting Hallucinations in LLM Generated Text By Checking Inconsistencies About Key Facts IJCNLP 2025
E-Verify: A Paradigm Shift to Scalable Embedding-based Factuality Verification EMNLP 2025
Token Knowledge: A New Perspective For Knowledge in Large Language Models EMNLP 2025
Evaluating Evaluation Metrics – The Mirage of Hallucination Detection EMNLP 2025
AdvERSEM: Adversarial Robustness Testing and Training of LLM-based Groundedness Evaluators via Semantic Structure Manipulation EMNLP 2025
LLMs Do Not See Age: Assessing Demographic Bias in Automated Systematic Review Synthesis IJCNLP 2025
Zero-resource Hallucination Detection for Text Generation via Graph-based Contextual Knowledge Triples Modeling AAAI 2025