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08/03/2023
Reasoning in Large Language Models Through Symbolic Math Word Problems
Large language models (LLMs) have revolutionized NLP by solving downstre...
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02/13/2023
Task-Specific Skill Localization in Fine-tuned Language Models
Pre-trained language models can be fine-tuned to solve diverse NLP tasks...
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11/05/2022
New Definitions and Evaluations for Saliency Methods: Staying Intrinsic, Complete and Sound
Saliency methods compute heat maps that highlight portions of an input t...
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10/03/2022
Understanding Influence Functions and Datamodels via Harmonic Analysis
Influence functions estimate effect of individual data points on predict...
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02/28/2022
Understanding Contrastive Learning Requires Incorporating Inductive Biases
Contrastive learning is a popular form of self-supervised learning that ...
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11/28/2021
On Predicting Generalization using GANs
Research on generalization bounds for deep networks seeks to give ways t...
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10/07/2020
A Mathematical Exploration of Why Language Models Help Solve Downstream Tasks
Autoregressive language models pretrained on large corpora have been suc...
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08/03/2020
Predicting What You Already Know Helps: Provable Self-Supervised Learning
Self-supervised representation learning solves auxiliary prediction task...
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02/25/2020
A Sample Complexity Separation between Non-Convex and Convex Meta-Learning
One popular trend in meta-learning is to learn from many training tasks ...
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02/24/2020
Provable Representation Learning for Imitation Learning via Bi-level Optimization
A common strategy in modern learning systems is to learn a representatio...
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02/25/2019
A Theoretical Analysis of Contrastive Unsupervised Representation Learning
Recent empirical works have successfully used unlabeled data to learn fe...
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05/14/2018
A La Carte Embedding: Cheap but Effective Induction of Semantic Feature Vectors
Motivations like domain adaptation, transfer learning, and feature learn...
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04/19/2017