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Interpretability

7,318 papers

Papers per year

Papers

MedThink: A Rationale-Guided Framework for Explaining Medical Visual Question Answering NAACL 2025
Features that Make a Difference: Leveraging Gradients for Improved Dictionary Learning NAACL 2025
LLM-Microscope: Uncovering the Hidden Role of Punctuation in Context Memory of Transformers NAACL 2025
Gradient-guided Attention Map Editing: Towards Efficient Contextual Hallucination Mitigation NAACL 2025
Explainability for NLP in Pharmacovigilance: A Study on Adverse Event Report Triage in Swedish NAACL 2025
Explainable ICD Coding via Entity Linking NAACL 2025
Who We Are, Where We Are: Mental Health at the Intersection of Person, Situation, and Large Language Models NAACL 2025
Bridging the Faithfulness Gap in Prototypical Models NAACL 2025
Error Reflection Prompting: Can Large Language Models Successfully Understand Errors? NAACL 2025
Interpretable Models for Detecting Linguistic Variation in Russian Media: Towards Unveiling Propagandistic Strategies during the Russo-Ukrainian War NAACL 2025
Probing Internal Representations of Multi-Word Verbs in Large Language Models NAACL 2025
The AI Co-Ethnographer: How Far Can Automation Take Qualitative Research? NAACL 2025
VLG-BERT: Towards Better Interpretability in LLMs through Visual and Linguistic Grounding NAACL 2025
Ambiguity Detection and Uncertainty Calibration for Question Answering with Large Language Models NAACL 2025
Smaller Large Language Models Can Do Moral Self-Correction NAACL 2025
Error Detection for Multimodal Classification NAACL 2025
Know What You do Not Know: Verbalized Uncertainty Estimation Robustness on Corrupted Images in Vision-Language Models NAACL 2025
Bias A-head? Analyzing Bias in Transformer-Based Language Model Attention Heads NAACL 2025
A Calibrated Reflection Approach for Enhancing Confidence Estimation in LLMs NAACL 2025
Evaluating Design Choices in Verifiable Generation with Open-source Models NAACL 2025
Disentangling Linguistic Features with Dimension-Wise Analysis of Vector Embeddings NAACL 2025
Investigating and Addressing Hallucinations of LLMs in Tasks Involving Negation NAACL 2025
Holmes: Localizing Irregularities in LLM Training with Mega-scale GPU Clusters NSDI 2025
Learning Interpretable Features from Interventions RSS 2025
REFIND at SemEval-2025 Task 3: Retrieval-Augmented Factuality Hallucination Detection in Large Language Models SEMEVAL 2025