:: Library Catalog

Image de couverture de livre

Enregistré dans:

Détails bibliographiques
Auteur principal:	Kumar, Keshav
Format:	Preprint
Publié:	2025
Sujets:	Computation and Language Machine Learning
Accès en ligne:	https://arxiv.org/abs/2507.04137
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Scalable Token-Level Hallucination Detection in Large Language Models
par: Min, Rui, et autres
Publié: (2026)

Language Modeling with Learned Meta-Tokens
par: Shah, Alok N., et autres
Publié: (2025)

Detecting Hallucinations in Large Language Model Generation: A Token Probability Approach
par: Quevedo, Ernesto, et autres
Publié: (2024)

Towards Token-Level Text Anomaly Detection
par: Cao, Yang, et autres
Publié: (2026)

Attention Sinks as Internal Signals for Hallucination Detection in Large Language Models
par: Binkowski, Jakub, et autres
Publié: (2026)

MetaToken: Detecting Hallucination in Image Descriptions by Meta Classification
par: Fieback, Laura, et autres
Publié: (2024)

A Graph Signal Processing Framework for Hallucination Detection in Large Language Models
par: Noël, Valentin
Publié: (2025)

ANHALTEN: Cross-Lingual Transfer for German Token-Level Reference-Free Hallucination Detection
par: Herrlein, Janek, et autres
Publié: (2024)

HalluWorld: A Controlled Benchmark for Hallucination via Reference World Models
par: Liu, Emmy, et autres
Publié: (2026)

Detection Without Correction: A Robust Asymmetry in Activation-Based Hallucination Probing
par: Roy, Dip, et autres
Publié: (2026)

Token-Level Adversarial Prompt Detection Based on Perplexity Measures and Contextual Information
par: Hu, Zhengmian, et autres
Publié: (2023)

TokenShapley: Token Level Context Attribution with Shapley Value
par: Xiao, Yingtai, et autres
Publié: (2025)

FactSelfCheck: Fact-Level Black-Box Hallucination Detection for LLMs
par: Sawczyn, Albert, et autres
Publié: (2025)

Hallucination Detection in LLMs Using Spectral Features of Attention Maps
par: Binkowski, Jakub, et autres
Publié: (2025)

Mid-Think: Training-Free Intermediate-Budget Reasoning via Token-Level Triggers
par: Yang, Wang, et autres
Publié: (2026)

Adversarial Attacks on AI-Generated Text Detection Models: A Token Probability-Based Approach Using Embeddings
par: Kadhim, Ahmed K., et autres
Publié: (2025)

References Indeed Matter? Reference-Free Preference Optimization for Conversational Query Reformulation
par: Kim, Doyoung, et autres
Publié: (2025)

Variance Control via Weight Rescaling in LLM Pre-training
par: Owen, Louis, et autres
Publié: (2025)

Detecting AI Hallucinations in Finance: An Information-Theoretic Method Cuts Hallucination Rate by 92%
par: Singha, Mainak
Publié: (2025)

Detecting Hallucinations in SpeechLLMs at Inference Time Using Attention Maps
par: Waldendorf, Jonas, et autres
Publié: (2026)

SlideSpawn: An Automatic Slides Generation System for Research Publications
par: Kumar, Keshav, et autres
Publié: (2024)

The HalluRAG Dataset: Detecting Closed-Domain Hallucinations in RAG Applications Using an LLM's Internal States
par: Ridder, Fabian, et autres
Publié: (2024)

Harmonic Token Projection (HTP): A Vocabulary-Free, Training-Free, Deterministic, and Reversible Embedding Methodology
par: Schmitz, Tcharlies
Publié: (2025)

Cmprsr: Abstractive Token-Level Question-Agnostic Prompt Compressor
par: Zakazov, Ivan, et autres
Publié: (2025)

TLDR: Token-Level Detective Reward Model for Large Vision Language Models
par: Fu, Deqing, et autres
Publié: (2024)

MMD-Flagger: Leveraging Maximum Mean Discrepancy to Detect Hallucinations
par: Mitsuzawa, Kensuke, et autres
Publié: (2025)

HaloScope: Harnessing Unlabeled LLM Generations for Hallucination Detection
par: Du, Xuefeng, et autres
Publié: (2024)

Leveraging Graph Structures to Detect Hallucinations in Large Language Models
par: Nonkes, Noa, et autres
Publié: (2024)

Temporal Graph Network: Hallucination Detection in Multi-Turn Conversation
par: Rathore, Vidhi, et autres
Publié: (2026)

Pairwise Reference Alignment as a Model-Level Ordinal Observable
par: Li, Mujing
Publié: (2026)

Just on Time: Token-Level Early Stopping for Diffusion Language Models
par: Kohut, Zahar, et autres
Publié: (2026)

Learning to Reason for Hallucination Span Detection
par: Su, Hsuan, et autres
Publié: (2025)

Steer LLM Latents for Hallucination Detection
par: Park, Seongheon, et autres
Publié: (2025)

Cost-Effective Hallucination Detection for LLMs
par: Valentin, Simon, et autres
Publié: (2024)

Beyond ROUGE: N-Gram Subspace Features for LLM Hallucination Detection
par: Li, Jerry, et autres
Publié: (2025)

RAGognizer: Hallucination-Aware Fine-Tuning via Detection Head Integration
par: Ridder, Fabian, et autres
Publié: (2026)

InterrogateLLM: Zero-Resource Hallucination Detection in LLM-Generated Answers
par: Yehuda, Yakir, et autres
Publié: (2024)

Mixture-of-Recursions: Learning Dynamic Recursive Depths for Adaptive Token-Level Computation
par: Bae, Sangmin, et autres
Publié: (2025)

Critical Tokens Matter: Token-Level Contrastive Estimation Enhances LLM's Reasoning Capability
par: Lin, Zicheng, et autres
Publié: (2024)

Evaluating Evaluation Metrics -- The Mirage of Hallucination Detection
par: Kulkarni, Atharva, et autres
Publié: (2025)