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Interpretability

173 directly classified papers

Papers per year

Papers

AUTOSUMM: A Comprehensive Framework for LLM-Based Conversation Summarization ACL 2025
Towards Fine-Grained Interpretability: Counterfactual Explanations for Misclassification with Saliency Partition CVPR 2025
LLaMAs Have Feelings Too: Unveiling Sentiment and Emotion Representations in LLaMA Models Through Probing ACL 2025
ICR Probe: Tracking Hidden State Dynamics for Reliable Hallucination Detection in LLMs ACL 2025
Serial Position Effects of Large Language Models ACL 2025
Natural Language Counterfactual Explanations in Financial Text Classification: A Comparison of Generators and Evaluation Metrics ACL 2025
Position-aware Automatic Circuit Discovery ACL 2025
Are the Hidden States Hiding Something? Testing the Limits of Factuality-Encoding Capabilities in LLMs ACL 2025
Tuning-Free Accountable Intervention for LLM Deployment – a Metacognitive Approach AAAI 2025
Attributive Reasoning for Hallucination Diagnosis of Large Language Models AAAI 2025
Towards Trustable SHAP Scores AAAI 2025
Conditional Feature Importance with Generative Modeling Using Adversarial Random Forests AAAI 2025
Prompt-CAM: Making Vision Transformers Interpretable for Fine-Grained Analysis CVPR 2025
Improving Large Language Model Confidence Estimates using Extractive Rationales for Classification ACL 2025
Identifying Pre-training Data in LLMs: A Neuron Activation-Based Detection Framework EMNLP 2025
Even-if Explanations: Formal Foundations, Priorities and Complexity AAAI 2025
How Your Location Relates to Health: Variable Importance and Interpretable Machine Learning for Environmental and Sociodemographic Data AAAI 2025
Interpretable DNFs IJCAI 2025
Intervening in Black Box: Concept Bottleneck Model for Enhancing Human Neural Network Mutual Understanding ICCV 2025
Walking the Web of Concept-Class Relationships in Incrementally Trained Interpretable Models AAAI 2025
GeoPro-Net: Learning Interpretable Spatiotemporal Prediction Models Through Statistically-Guided Geo-Prototyping AAAI 2025
BEE: Metric-Adapted Explanations via Baseline Exploration-Exploitation AAAI 2025
Interpretable Image Classification via Non-parametric Part Prototype Learning CVPR 2025
Accurate Estimation of Feature Importance Faithfulness for Tree Models AAAI 2025
Unsupervised Hallucination Detection by Inspecting Reasoning Processes EMNLP 2025