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09/07/2023
DoLa: Decoding by Contrasting Layers Improves Factuality in Large Language Models
Despite their impressive capabilities, large language models (LLMs) are ...
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05/26/2023
Entailment as Robust Self-Learner
Entailment has been recognized as an important metric for evaluating nat...
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04/16/2023
Chain of Thought Prompt Tuning in Vision Language Models
Language-Image Pre-training has demonstrated promising results on zero-s...
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04/07/2023
Interpretable Unified Language Checking
Despite recent concerns about undesirable behaviors generated by large l...
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03/10/2023
Logic Against Bias: Textual Entailment Mitigates Stereotypical Sentence Reasoning
Due to their similarity-based learning objectives, pretrained sentence e...
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06/14/2021
Mitigating Biases in Toxic Language Detection through Invariant Rationalization
Automatic detection of toxic language plays an essential role in protect...
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06/06/2021
Meta-learning for downstream aware and agnostic pretraining
Neural network pretraining is gaining attention due to its outstanding p...
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03/12/2021
Cooperative Learning of Zero-Shot Machine Reading Comprehension
Pretrained language models have significantly improved the performance o...
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01/24/2021
Knowledge Grounded Conversational Symptom Detection with Graph Memory Networks
In this work, we propose a novel goal-oriented dialog task, automatic sy...
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05/19/2020
Prototypical Q Networks for Automatic Conversational Diagnosis and Few-Shot New Disease Adaption
Spoken dialog systems have seen applications in many domains, including ...
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06/04/2019
Improving Neural Language Models by Segmenting, Attending, and Predicting the Future
Common language models typically predict the next word given the context...
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02/23/2017
Bidirectional Backpropagation: Towards Biologically Plausible Error Signal Transmission in Neural Networks
The back-propagation (BP) algorithm has been considered the de-facto met...
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01/05/2016
