conftrace_
← Core AI
Artificial Intelligence › Core AI ›

Interpretability

7,318 papers

Papers per year

Papers

Stochastic Concept Bottleneck Models NIPS 2024
ERBench: An Entity-Relationship based Automatically Verifiable Hallucination Benchmark for Large Language Models NIPS 2024
Uncertainty-aware Fine-tuning of Segmentation Foundation Models NIPS 2024
Denoising Diffusion Path: Attribution Noise Reduction with An Auxiliary Diffusion Model NIPS 2024
Transformer Doctor: Diagnosing and Treating Vision Transformers NIPS 2024
BrainBits: How Much of the Brain are Generative Reconstruction Methods Using? NIPS 2024
What Rotary Position Embedding Can Tell Us: Identifying Query and Key Weights Corresponding to Basic Syntactic or High-level Semantic Information NIPS 2024
Dissecting Query-Key Interaction in Vision Transformers NIPS 2024
Selective Explanations NIPS 2024
Do Counterfactually Fair Image Classifiers Satisfy Group Fairness? -- A Theoretical and Empirical Study NIPS 2024
Spectral Editing of Activations for Large Language Model Alignment NIPS 2024
Understanding Generalizability of Diffusion Models Requires Rethinking the Hidden Gaussian Structure NIPS 2024
A Cat Is A Cat (Not A Dog!): Unraveling Information Mix-ups in Text-to-Image Encoders through Causal Analysis and Embedding Optimization NIPS 2024
To Believe or Not to Believe Your LLM: Iterative Prompting for Estimating Epistemic Uncertainty NIPS 2024
Conformalized Multiple Testing after Data-dependent Selection NIPS 2024
CLAVE: An Adaptive Framework for Evaluating Values of LLM Generated Responses NIPS 2024
Talking Heads: Understanding Inter-Layer Communication in Transformer Language Models NIPS 2024
B-cosification: Transforming Deep Neural Networks to be Inherently Interpretable NIPS 2024
T2VSafetyBench: Evaluating the Safety of Text-to-Video Generative Models NIPS 2024
Me, Myself, and AI: The Situational Awareness Dataset (SAD) for LLMs NIPS 2024
Designs for Enabling Collaboration in Human-Machine Teaming via Interactive and Explainable Systems NIPS 2024
Listenable Maps for Zero-Shot Audio Classifiers NIPS 2024
Chain-of-Thought Reasoning Without Prompting NIPS 2024
Training Data Attribution via Approximate Unrolling NIPS 2024
Interpretable Concept Bottlenecks to Align Reinforcement Learning Agents NIPS 2024