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07/31/2023
Generative Models as a Complex Systems Science: How can we make sense of large language model behavior?
Coaxing out desired behavior from pretrained models, while avoiding unde...
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05/23/2023
QLoRA: Efficient Finetuning of Quantized LLMs
We present QLoRA, an efficient finetuning approach that reduces memory u...
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12/20/2022
Toward Human Readable Prompt Tuning: Kubrick's The Shining is a good movie, and a good prompt too?
Large language models can perform new tasks in a zero-shot fashion, give...
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10/27/2022
Contrastive Decoding: Open-ended Text Generation as Optimization
Likelihood, although useful as a training loss, is a poor search objecti...
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08/26/2022
What Do NLP Researchers Believe? Results of the NLP Community Metasurvey
We present the results of the NLP Community Metasurvey. Run from May to ...
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02/25/2022
Rethinking the Role of Demonstrations: What Makes In-Context Learning Work?
Large language models (LMs) are able to in-context learn – perform a new...
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08/11/2021
DEMix Layers: Disentangling Domains for Modular Language Modeling
We introduce a new domain expert mixture (DEMix) layer that enables cond...
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06/01/2021
PIGLeT: Language Grounding Through Neuro-Symbolic Interaction in a 3D World
We propose PIGLeT: a model that learns physical commonsense knowledge th...
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04/18/2021
CLIPScore: A Reference-free Evaluation Metric for Image Captioning
Image captioning has conventionally relied on reference-based automatic ...
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04/16/2021
Surface Form Competition: Why the Highest Probability Answer Isn't Always Right
Large language models have shown promising results in zero-shot settings...
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02/02/2021
MultiTalk: A Highly-Branching Dialog Testbed for Diverse Conversations
We study conversational dialog in which there are many possible response...
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10/16/2020
Reflective Decoding: Unsupervised Paraphrasing and Abductive Reasoning
Pretrained Language Models (LMs) generate text with remarkable quality, ...
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04/21/2020
Experience Grounds Language
Successful linguistic communication relies on a shared experience of the...
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04/07/2020
Evaluating Machines by their Real-World Language Use
There is a fundamental gap between how humans understand and use languag...
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09/16/2019
BottleSum: Unsupervised and Self-supervised Sentence Summarization using the Information Bottleneck Principle
The principle of the Information Bottleneck (Tishby et al. 1999) is to p...
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09/09/2019
Counterfactual Story Reasoning and Generation
Counterfactual reasoning requires predicting how alternative events, con...
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08/15/2019
Abductive Commonsense Reasoning
Abductive reasoning is inference to the most plausible explanation. For ...
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08/08/2019
Do Neural Language Representations Learn Physical Commonsense?
Humans understand language based on the rich background knowledge about ...
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07/02/2019
Cooperative Generator-Discriminator Networks for Abstractive Summarization with Narrative Flow
We introduce Cooperative Generator-Discriminator Networks (Co-opNet), a ...
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05/29/2019
Defending Against Neural Fake News
Recent progress in natural language generation has raised dual-use conce...
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05/19/2019
HellaSwag: Can a Machine Really Finish Your Sentence?
Recent work by Zellers et al. (2018) introduced a new task of commonsens...
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04/22/2019
The Curious Case of Neural Text Degeneration
Despite considerable advancements with deep neural language models, the ...
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03/06/2019
Tactical Rewind: Self-Correction via Backtracking in Vision-and-Language Navigation
We present FAST NAVIGATOR, a general framework for action decoding, whic...
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05/16/2018
Learning to Write with Cooperative Discriminators
Recurrent Neural Networks (RNNs) are powerful autoregressive sequence mo...
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04/26/2018
Sounding Board: A User-Centric and Content-Driven Social Chatbot
We present Sounding Board, a social chatbot that won the 2017 Amazon Ale...
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11/14/2017
