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09/14/2023
Safety-Tuned LLaMAs: Lessons From Improving the Safety of Large Language Models that Follow Instructions
Training large language models to follow instructions makes them perform...
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08/16/2023
Learning the meanings of function words from grounded language using a visual question answering model
Interpreting a seemingly-simple function word like "or", "behind", or "m...
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07/14/2023
Othering and low prestige framing of immigrant cuisines in US restaurant reviews and large language models
Identifying and understanding implicit attitudes toward food can help ef...
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07/12/2023
Ecosystem-level Analysis of Deployed Machine Learning Reveals Homogeneous Outcomes
Machine learning is traditionally studied at the model level: researcher...
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06/09/2023
Developing Speech Processing Pipelines for Police Accountability
Police body-worn cameras have the potential to improve accountability an...
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05/29/2023
Marked Personas: Using Natural Language Prompts to Measure Stereotypes in Language Models
To recognize and mitigate harms from large language models (LLMs), we ne...
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05/18/2023
Making More of Little Data: Improving Low-Resource Automatic Speech Recognition Using Data Augmentation
The performance of automatic speech recognition (ASR) systems has advanc...
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04/27/2023
string2string: A Modern Python Library for String-to-String Algorithms
We introduce string2string, an open-source library that offers a compreh...
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04/25/2023
Pretrain on just structure: Understanding linguistic inductive biases using transfer learning
Both humans and transformer language models are able to learn language w...
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03/28/2023
Foundation Models and Fair Use
Existing foundation models are trained on copyrighted material. Deployin...
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02/26/2023
Navigating the Grey Area: Expressions of Overconfidence and Uncertainty in Language Models
Despite increasingly fluent, relevant, and coherent language generation,...
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02/09/2023
Leveraging supplementary text data to kick-start automatic speech recognition system development with limited transcriptions
Recent research using pre-trained transformer models suggests that just ...
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11/27/2022
Self-Destructing Models: Increasing the Costs of Harmful Dual Uses in Foundation Models
A growing ecosystem of large, open-source foundation models has reduced ...
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11/25/2022
Picking on the Same Person: Does Algorithmic Monoculture lead to Outcome Homogenization?
As the scope of machine learning broadens, we observe a recurring theme ...
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11/14/2022
Follow the Wisdom of the Crowd: Effective Text Generation via Minimum Bayes Risk Decoding
In open-ended natural-language generation, existing text decoding method...
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11/07/2022
Easily Accessible Text-to-Image Generation Amplifies Demographic Stereotypes at Large Scale
Machine learning models are now able to convert user-written text descri...
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10/11/2022
Multilingual BERT has an accent: Evaluating English influences on fluency in multilingual models
While multilingual language models can improve NLP performance on low-re...
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10/04/2022
When and why vision-language models behave like bags-of-words, and what to do about it?
Despite the success of large vision and language models (VLMs) in many d...
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07/08/2022
Computationally Identifying Funneling and Focusing Questions in Classroom Discourse
Responsive teaching is a highly effective strategy that promotes student...
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07/01/2022
Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset
One concern with the rise of large language models lies with their poten...
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05/24/2022
How Human is Human Evaluation? Improving the Gold Standard for NLG with Utility Theory
Human ratings are treated as the gold standard in NLG evaluation. The st...
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05/23/2022
Prompt-and-Rerank: A Method for Zero-Shot and Few-Shot Arbitrary Textual Style Transfer with Small Language Models
We propose a method for arbitrary textual style transfer (TST)–the task ...
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05/10/2022
Richer Countries and Richer Representations
We examine whether some countries are more richly represented in embeddi...
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05/10/2022
Problems with Cosine as a Measure of Embedding Similarity for High Frequency Words
Cosine similarity of contextual embeddings is used in many NLP tasks (e....
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04/26/2022
Modular Domain Adaptation
Off-the-shelf models are widely used by computational social science res...
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04/15/2022
Automated speech tools for helping communities process restricted-access corpora for language revival efforts
Many archival recordings of speech from endangered languages remain unan...
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10/11/2021
Focus on what matters: Applying Discourse Coherence Theory to Cross Document Coreference
Performing event and entity coreference resolution across documents vast...
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09/13/2021
The Emergence of the Shape Bias Results from Communicative Efficiency
By the age of two, children tend to assume that new word categories are ...
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06/07/2021
Measuring Conversational Uptake: A Case Study on Student-Teacher Interactions
In conversation, uptake happens when a speaker builds on the contributio...
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05/31/2021
Attention Flows are Shapley Value Explanations
Shapley Values, a solution to the credit assignment problem in cooperati...
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04/21/2021
Sensitivity as a Complexity Measure for Sequence Classification Tasks
We introduce a theoretical framework for understanding and predicting th...
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04/17/2021
Frequency-based Distortions in Contextualized Word Embeddings
How does word frequency in pre-training data affect the behavior of simi...
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03/26/2021
Leveraging neural representations for facilitating access to untranscribed speech from endangered languages
For languages with insufficient resources to train speech recognition sy...
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11/09/2020
Language Through a Prism: A Spectral Approach for Multiscale Language Representations
Language exhibits structure at different scales, ranging from subwords t...
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10/28/2020
DeSMOG: Detecting Stance in Media On Global Warming
Citing opinions is a powerful yet understudied strategy in argumentation...
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10/24/2020
Causal Effects of Linguistic Properties
We consider the problem of estimating the causal effects of linguistic p...
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10/20/2020
Improving Factual Completeness and Consistency of Image-to-Text Radiology Report Generation
Neural image-to-text radiology report generation systems offer the poten...
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10/13/2020
With Little Power Comes Great Responsibility
Despite its importance to experimental design, statistical power (the pr...
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10/01/2020
Nearest Neighbor Machine Translation
We introduce k-nearest-neighbor machine translation (kNN-MT), which pred...
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09/29/2020
Utility is in the Eye of the User: A Critique of NLP Leaderboards
Benchmarks such as GLUE have helped drive advances in NLP by incentivizi...
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06/16/2020
The Role of Verb Semantics in Hungarian Verb-Object Order
Hungarian is often referred to as a discourse-configurational language, ...
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05/20/2020
Pretraining with Contrastive Sentence Objectives Improves Discourse Performance of Language Models
Recent models for unsupervised representation learning of text have empl...
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04/30/2020
Pretraining on Non-linguistic Structure as a Tool for Analyzing Learning Bias in Language Models
We propose a novel methodology for analyzing the encoding of grammatical...
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03/06/2020
A Framework for the Computational Linguistic Analysis of Dehumanization
Dehumanization is a pernicious psychological process that often leads to...
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01/31/2020
Towards the Systematic Reporting of the Energy and Carbon Footprints of Machine Learning
Accurate reporting of energy and carbon usage is essential for understan...
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11/21/2019
Automatically Neutralizing Subjective Bias in Text
Texts like news, encyclopedias, and some social media strive for objecti...
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11/10/2019
Social Bias Frames: Reasoning about Social and Power Implications of Language
Language has the power to reinforce stereotypes and project social biase...
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11/01/2019
Generalization through Memorization: Nearest Neighbor Language Models
We introduce kNN-LMs, which extend a pre-trained neural language model (...
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05/21/2019
Sample Efficient Text Summarization Using a Single Pre-Trained Transformer
Language model (LM) pre-training has resulted in impressive performance ...
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04/19/2019
