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Showing 1–50 of 80 papers

TitleStatusHype
RLHF Workflow: From Reward Modeling to Online RLHFCode5
Inference-Time Intervention: Eliciting Truthful Answers from a Language ModelCode2
Tuning Language Models by ProxyCode2
DoLa: Decoding by Contrasting Layers Improves Factuality in Large Language ModelsCode2
TruthX: Alleviating Hallucinations by Editing Large Language Models in Truthful SpaceCode2
In-Context Sharpness as Alerts: An Inner Representation Perspective for Hallucination MitigationCode2
Integrative Decoding: Improve Factuality via Implicit Self-consistencyCode1
Alleviating Hallucinations of Large Language Models through Induced HallucinationsCode1
Machine Unlearning in Large Language ModelsCode1
Truth Forest: Toward Multi-Scale Truthfulness in Large Language Models through Intervention without TuningCode1
Non-Linear Inference Time Intervention: Improving LLM TruthfulnessCode1
Red-Teaming Large Language Models using Chain of Utterances for Safety-AlignmentCode1
RAIN: Your Language Models Can Align Themselves without FinetuningCode1
Tool-Augmented Reward ModelingCode1
Sight Beyond Text: Multi-Modal Training Enhances LLMs in Truthfulness and EthicsCode1
TruthfulQA: Measuring How Models Mimic Human FalsehoodsCode1
Instruction Tuning With Loss Over InstructionsCode1
Lower Layer Matters: Alleviating Hallucination via Multi-Layer Fusion Contrastive Decoding with Truthfulness Refocused—0
Maintaining Informative Coherence: Migrating Hallucinations in Large Language Models via Absorbing Markov Chains—0
Mitigating Adversarial Attacks in LLMs through Defensive Suffix Generation—0
Model Unlearning via Sparse Autoencoder Subspace Guided Projections—0
Monty Hall and Optimized Conformal Prediction to Improve Decision-Making with LLMs—0
More is Less: The Pitfalls of Multi-Model Synthetic Preference Data in DPO Safety Alignment—0
Multi-Reference Preference Optimization for Large Language Models—0
Obliviate: Efficient Unmemorization for Protecting Intellectual Property in Large Language Models—0
On The Truthfulness of 'Surprisingly Likely' Responses of Large Language Models—0
PRobELM: Plausibility Ranking Evaluation for Language Models—0
Teuken-7B-Base & Teuken-7B-Instruct: Towards European LLMs—0
Efficiently Deploying LLMs with Controlled Risk—0
Benchmark Inflation: Revealing LLM Performance Gaps Using Retro-Holdouts—0
Cost-Saving LLM Cascades with Early Abstention—0
LLMAuditor: A Framework for Auditing Large Language Models Using Human-in-the-Loop—0
DYNAMAX: Dynamic computing for Transformers and Mamba based architectures—0
A Debate-Driven Experiment on LLM Hallucinations and Accuracy—0
Efficient MAP Estimation of LLM Judgment Performance with Prior Transfer—0
Elastic Weight Consolidation for Full-Parameter Continual Pre-Training of Gemma2—0
Evaluating Consistencies in LLM responses through a Semantic Clustering of Question Answering—0
GRATH: Gradual Self-Truthifying for Large Language Models—0
Harmonic LLMs are Trustworthy—0
Instruction Tuning with Human Curriculum—0
Investigating Data Contamination in Modern Benchmarks for Large Language Models—0
Iter-AHMCL: Alleviate Hallucination for Large Language Model via Iterative Model-level Contrastive Learning—0
Just Ask for Calibration: Strategies for Eliciting Calibrated Confidence Scores from Language Models Fine-Tuned with Human Feedback—0
Layer Importance and Hallucination Analysis in Large Language Models via Enhanced Activation Variance-Sparsity—0
LokiLM: Technical Report—0
Student Data Paradox and Curious Case of Single Student-Tutor Model: Regressive Side Effects of Training LLMs for Personalized Learning—0
Sample, Don't Search: Rethinking Test-Time Alignment for Language Models—0
Selective Self-Rehearsal: A Fine-Tuning Approach to Improve Generalization in Large Language Models—0
Selective Self-to-Supervised Fine-Tuning for Generalization in Large Language Models—0
Self-Alignment for Factuality: Mitigating Hallucinations in LLMs via Self-Evaluation—0
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