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10/14/2022
COFFEE: Counterfactual Fairness for Personalized Text Generation in Explainable Recommendation
Personalized text generation has broad industrial applications, such as ...
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10/12/2022
AD-DROP: Attribution-Driven Dropout for Robust Language Model Fine-Tuning
Fine-tuning large pre-trained language models on downstream tasks is apt...
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07/02/2022
FRAME: Evaluating Simulatability Metrics for Free-Text Rationales
Free-text rationales aim to explain neural language model (LM) behavior ...
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05/25/2022
ER-TEST: Evaluating Explanation Regularization Methods for NLP Models
Neural language models' (NLMs') reasoning processes are notoriously hard...
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04/12/2022
Detection, Disambiguation, Re-ranking: Autoregressive Entity Linking as a Multi-Task Problem
We propose an autoregressive entity linking model, that is trained with ...
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12/31/2021
BARACK: Partially Supervised Group Robustness With Guarantees
While neural networks have shown remarkable success on classification ta...
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12/16/2021
UniREx: A Unified Learning Framework for Language Model Rationale Extraction
An extractive rationale explains a language model's (LM's) prediction on...
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01/06/2021
Modality-specific Distillation
Large neural networks are impractical to deploy on mobile devices due to...
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01/23/2018