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TruthfulQA

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Showing 1–50 of 80 papers

TitleStatusHype
RLHF Workflow: From Reward Modeling to Online RLHFCode5
In-Context Sharpness as Alerts: An Inner Representation Perspective for Hallucination MitigationCode2
TruthX: Alleviating Hallucinations by Editing Large Language Models in Truthful SpaceCode2
Tuning Language Models by ProxyCode2
DoLa: Decoding by Contrasting Layers Improves Factuality in Large Language ModelsCode2
Inference-Time Intervention: Eliciting Truthful Answers from a Language ModelCode2
Integrative Decoding: Improve Factuality via Implicit Self-consistencyCode1
Machine Unlearning in Large Language ModelsCode1
Instruction Tuning With Loss Over InstructionsCode1
Non-Linear Inference Time Intervention: Improving LLM TruthfulnessCode1
Truth Forest: Toward Multi-Scale Truthfulness in Large Language Models through Intervention without TuningCode1
Alleviating Hallucinations of Large Language Models through Induced HallucinationsCode1
Tool-Augmented Reward ModelingCode1
RAIN: Your Language Models Can Align Themselves without FinetuningCode1
Sight Beyond Text: Multi-Modal Training Enhances LLMs in Truthfulness and EthicsCode1
Red-Teaming Large Language Models using Chain of Utterances for Safety-AlignmentCode1
TruthfulQA: Measuring How Models Mimic Human FalsehoodsCode1
Unsupervised Elicitation of Language ModelsCode0
Model Unlearning via Sparse Autoencoder Subspace Guided Projections—0
Shadows in the Attention: Contextual Perturbation and Representation Drift in the Dynamics of Hallucination in LLMs—0
Truth NeuronsCode0
Elastic Weight Consolidation for Full-Parameter Continual Pre-Training of Gemma2—0
DYNAMAX: Dynamic computing for Transformers and Mamba based architectures—0
Efficient MAP Estimation of LLM Judgment Performance with Prior Transfer—0
Sample, Don't Search: Rethinking Test-Time Alignment for Language Models—0
Sustainable LLM Inference for Edge AI: Evaluating Quantized LLMs for Energy Efficiency, Output Accuracy, and Inference Latency—0
More is Less: The Pitfalls of Multi-Model Synthetic Preference Data in DPO Safety Alignment—0
When Persuasion Overrides Truth in Multi-Agent LLM Debates: Introducing a Confidence-Weighted Persuasion Override Rate (CW-POR)—0
DeLTa: A Decoding Strategy based on Logit Trajectory Prediction Improves Factuality and Reasoning AbilityCode0
Obliviate: Efficient Unmemorization for Protecting Intellectual Property in Large Language Models—0
Truth Knows No Language: Evaluating Truthfulness Beyond EnglishCode0
Cost-Saving LLM Cascades with Early Abstention—0
Selective Self-to-Supervised Fine-Tuning for Generalization in Large Language Models—0
Multi-Agent Reinforcement Learning with Focal Diversity OptimizationCode0
TruthFlow: Truthful LLM Generation via Representation Flow Correction—0
CHAIR -- Classifier of Hallucination as ImproverCode0
(WhyPHI) Fine-Tuning PHI-3 for Multiple-Choice Question Answering: Methodology, Results, and ChallengesCode0
Monty Hall and Optimized Conformal Prediction to Improve Decision-Making with LLMs—0
Mitigating Adversarial Attacks in LLMs through Defensive Suffix Generation—0
Uhura: A Benchmark for Evaluating Scientific Question Answering and Truthfulness in Low-Resource African Languages—0
Layer Importance and Hallucination Analysis in Large Language Models via Enhanced Activation Variance-Sparsity—0
Maintaining Informative Coherence: Migrating Hallucinations in Large Language Models via Absorbing Markov Chains—0
A Debate-Driven Experiment on LLM Hallucinations and Accuracy—0
Evaluating Consistencies in LLM responses through a Semantic Clustering of Question Answering—0
Iter-AHMCL: Alleviate Hallucination for Large Language Model via Iterative Model-level Contrastive Learning—0
SkillAggregation: Reference-free LLM-Dependent Aggregation—0
NoVo: Norm Voting off Hallucinations with Attention Heads in Large Language ModelsCode0
Towards Multilingual LLM Evaluation for European Languages—0
Benchmark Inflation: Revealing LLM Performance Gaps Using Retro-Holdouts—0
A test suite of prompt injection attacks for LLM-based machine translationCode0
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