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Papers
How to Compute the Probability of a Word
EMNLP 2024
Knowledge Distillation Based on Transformed Teacher Matching
ICLR 2024
Language Models can Evaluate Themselves via Probability Discrepancy
ACL 2024
Learning Large DAGs is Harder than you Think: Many Losses are Minimal for the Wrong DAG
ICLR 2024
Learning to Embed Distributions via Maximum Kernel Entropy
NeurIPS 2024
Light Schrödinger Bridge
ICLR 2024
Mutual Information Estimation via Normalizing Flows
NeurIPS 2024
On the Expressive Power of Tree-Structured Probabilistic Circuits
NeurIPS 2024
Open Problem: Tight Characterization of Instance-Optimal Identity Testing
COLT 2024
Optimal score estimation via empirical Bayes smoothing
COLT 2024
Optimising Distributions with Natural Gradient Surrogates
AISTATS 2024
Outdated Issue Aware Decoding for Factual Knowledge Editing
ACL 2024
Preferential Normalizing Flows
NeurIPS 2024
Pre-trained Language Models Return Distinguishable Probability Distributions to Unfaithfully Hallucinated Texts
EMNLP 2024
Probabilistic Contrastive Learning for Domain Adaptation
IJCAI 2024
Probability-Polarized Optimal Transport for Unsupervised Domain Adaptation
AAAI 2024
Second-Order Uncertainty Quantification: A Distance-Based Approach
ICML 2024
SH2: Self-Highlighted Hesitation Helps You Decode More Truthfully
EMNLP 2024
Statistical and Geometrical properties of the Kernel Kullback-Leibler divergence
NeurIPS 2024
TaD: A Plug-and-Play Task-Aware Decoding Method to Better Adapt LLMs on Downstream Tasks
IJCAI 2024
Transformers Can Represent n-gram Language Models
NAACL 2024
Transport-based Counterfactual Models
JMLR 2024
Unsupervised Tree Boosting for Learning Probability Distributions
JMLR 2024
Validating Climate Models with Spherical Convolutional Wasserstein Distance
NeurIPS 2024
Wasserstein Distance Rivals Kullback-Leibler Divergence for Knowledge Distillation
NeurIPS 2024