Christopher Potts

research

∙ 09/21/2023

ContextRef: Evaluating Referenceless Metrics For Image Description Generation

Referenceless metrics (e.g., CLIPScore) use pretrained vision–language m...

0 Elisa Kreiss, et al. ∙

research

∙ 09/19/2023

Rigorously Assessing Natural Language Explanations of Neurons

Natural language is an appealing medium for explaining how large languag...

0 Jing Huang, et al. ∙

research

∙ 07/28/2023

Context-VQA: Towards Context-Aware and Purposeful Visual Question Answering

Visual question answering (VQA) has the potential to make the Internet m...

0 Nandita Naik, et al. ∙

research

∙ 06/20/2023

GIO: Gradient Information Optimization for Training Dataset Selection

It is often advantageous to train models on a subset of the available tr...

0 Dante Everaert, et al. ∙

research

∙ 05/30/2023

ScoNe: Benchmarking Negation Reasoning in Language Models With Fine-Tuning and In-Context Learning

A number of recent benchmarks seek to assess how well models handle natu...

0 Jingyuan Selena She, et al. ∙

research

∙ 05/22/2023

BioDEX: Large-Scale Biomedical Adverse Drug Event Extraction for Real-World Pharmacovigilance

Timely and accurate extraction of Adverse Drug Events (ADE) from biomedi...

0 Karel D'Oosterlinck, et al. ∙

research

∙ 05/15/2023

Characterizing Image Accessibility on Wikipedia across Languages

We make a first attempt to characterize image accessibility on Wikipedia...

0 Elisa Kreiss, et al. ∙

research

∙ 05/15/2023

Interpretability at Scale: Identifying Causal Mechanisms in Alpaca

Obtaining human-interpretable explanations of large, general-purpose lan...

0 Zhengxuan Wu, et al. ∙

research

∙ 03/05/2023

Finding Alignments Between Interpretable Causal Variables and Distributed Neural Representations

Causal abstraction is a promising theoretical framework for explainable ...

0 Atticus Geiger, et al. ∙

research

∙ 03/01/2023

UDAPDR: Unsupervised Domain Adaptation via LLM Prompting and Distillation of Rerankers

Many information retrieval tasks require large labeled datasets for fine...

0 Jon Saad-Falcon, et al. ∙

research

∙ 12/28/2022

Demonstrate-Search-Predict: Composing retrieval and language models for knowledge-intensive NLP

Retrieval-augmented in-context learning has emerged as a powerful approa...

0 Omar Khattab, et al. ∙

research

∙ 12/19/2022

Inducing Character-level Structure in Subword-based Language Models with Type-level Interchange Intervention Training

Language tasks involving character-level manipulations (e.g., spelling c...

0 Jing Huang, et al. ∙

research

∙ 12/19/2022

Detecting Contradictory COVID-19 Drug Efficacy Claims from Biomedical Literature

The COVID-19 pandemic created a deluge of questionable and contradictory...

0 Daniel N. Sosa, et al. ∙

research

∙ 12/02/2022

Moving Beyond Downstream Task Accuracy for Information Retrieval Benchmarking

Neural information retrieval (IR) systems have progressed rapidly in rec...

0 Keshav Santhanam, et al. ∙

research

∙ 10/18/2022

Systematicity in GPT-3's Interpretation of Novel English Noun Compounds

Levin et al. (2019) show experimentally that the interpretations of nove...

0 Siyan Li, et al. ∙

research

∙ 09/28/2022

Causal Proxy Models for Concept-Based Model Explanations

Explainability methods for NLP systems encounter a version of the fundam...

19 Zhengxuan Wu, et al. ∙

research

∙ 05/27/2022

CEBaB: Estimating the Causal Effects of Real-World Concepts on NLP Model Behavior

The increasing size and complexity of modern ML systems has improved the...

4 Eldar David Abraham, et al. ∙

research

∙ 05/21/2022

Context Matters for Image Descriptions for Accessibility: Challenges for Referenceless Evaluation Metrics

Few images on the Web receive alt-text descriptions that would make them...

0 Elisa Kreiss, et al. ∙

research

∙ 05/19/2022

PLAID: An Efficient Engine for Late Interaction Retrieval

Pre-trained language models are increasingly important components across...

5 Keshav Santhanam, et al. ∙

research

∙ 05/18/2022

Color Overmodification Emerges from Data-Driven Learning and Pragmatic Reasoning

Speakers' referential expressions often depart from communicative ideals...

0 Fei Fang, et al. ∙

research

∙ 12/05/2021

Causal Distillation for Language Models

Distillation efforts have led to language models that are more compact a...

0 Zhengxuan Wu, et al. ∙

research

∙ 12/02/2021

ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction

Neural information retrieval (IR) has greatly advanced search and other ...

4 Keshav Santhanam, et al. ∙

research

∙ 12/01/2021

Inducing Causal Structure for Interpretable Neural Networks

In many areas, we have well-founded insights about causal structure that...

0 Atticus Geiger, et al. ∙

research

∙ 10/14/2021

Hindsight: Posterior-guided training of retrievers for improved open-ended generation

Many text generation systems benefit from using a retriever to retrieve ...

1 Ashwin Paranjape, et al. ∙

research

∙ 09/18/2021

ReaSCAN: Compositional Reasoning in Language Grounding

The ability to compositionally map language to referents, relations, and...

0 Zhengxuan Wu, et al. ∙

research

∙ 06/06/2021

Causal Abstractions of Neural Networks

Structural analysis methods (e.g., probing and feature attribution) are ...

0 Atticus Geiger, et al. ∙

research

∙ 04/17/2021

Decrypting Cryptic Crosswords: Semantically Complex Wordplay Puzzles as a Target for NLP

Cryptic crosswords, the dominant English-language crossword variety in t...

0 Josh Rozner, et al. ∙

research

∙ 04/17/2021

Identifying the Limits of Cross-Domain Knowledge Transfer for Pretrained Models

There is growing evidence that pretrained language models improve task-s...

2 Zhengxuan Wu, et al. ∙

research

∙ 04/16/2021

Concadia: Tackling image accessibility with context

Images have become an integral part of online media. This has enhanced s...

0 Elisa Kreiss, et al. ∙

research

∙ 01/02/2021

Baleen: Robust Multi-Hop Reasoning at Scale via Condensed Retrieval

Multi-hop reasoning (i.e., reasoning across two or more documents) at sc...

0 Omar Khattab, et al. ∙

research

∙ 12/30/2020

DynaSent: A Dynamic Benchmark for Sentiment Analysis

We introduce DynaSent ('Dynamic Sentiment'), a new English-language benc...

5 Christopher Potts, et al. ∙

research

∙ 12/07/2020

Learning Compositional Negation in Populations of Roth-Erev and Neural Agents

Agent-based models and signalling games are useful tools with which to s...

0 Graham Todd, et al. ∙

research

∙ 07/01/2020

Relevance-guided Supervision for OpenQA with ColBERT

Systems for Open-Domain Question Answering (OpenQA) generally depend on ...

0 Omar Khattab, et al. ∙

research

∙ 06/17/2020

Modeling subjective assessments of guilt in newspaper crime narratives

Crime reporting is a prevalent form of journalism with the power to shap...

0 Elisa Kreiss, et al. ∙

research

∙ 06/14/2020

Relational reasoning and generalization using non-symbolic neural networks

Humans have a remarkable capacity to reason about abstract relational st...

0 Atticus Geiger, et al. ∙

research

∙ 04/30/2020

Use of Machine Translation to Obtain Labeled Datasets for Resource-Constrained Languages

The large annotated datasets in NLP are overwhelmingly in English. This ...

0 Emrah Budur, et al. ∙

research

∙ 04/30/2020

Modular Representation Underlies Systematic Generalization in Neural Natural Language Inference Models

In adversarial (challenge) testing, we pose hard generalization tasks in...

0 Atticus Geiger, et al. ∙

research

∙ 04/29/2020

Pragmatic Issue-Sensitive Image Captioning

Image captioning systems have recently improved dramatically, but they s...

5 Allen Nie, et al. ∙

research

∙ 09/25/2019

TalkDown: A Corpus for Condescension Detection in Context

Condescending language use is caustic; it can bring dialogues to an end ...

0 Zijian Wang, et al. ∙

research

∙ 09/16/2019

Communication-based Evaluation for Natural Language Generation

Natural language generation (NLG) systems are commonly evaluated using n...

0 Benjamin Newman, et al. ∙

research

∙ 03/31/2019

Modeling Drug-Disease Relations with Linguistic and Knowledge Graph Constraints

FDA drug labels are rich sources of information about drugs and drug-dis...

0 Bruno Godefroy, et al. ∙

research

∙ 10/31/2018

Effective Feature Representation for Clinical Text Concept Extraction

Crucial information about the practice of healthcare is recorded only in...

0 Yifeng Tao, et al. ∙

research

∙ 10/30/2018

Stress-Testing Neural Models of Natural Language Inference with Multiply-Quantified Sentences

Standard evaluations of deep learning models for semantics using natural...

0 Atticus Geiger, et al. ∙

research

∙ 09/30/2018

An Incremental Iterated Response Model of Pragmatics

Recent Iterated Response (IR) models of pragmatics conceptualize languag...

0 Reuben Cohn-Gordon, et al. ∙

research

∙ 09/10/2018

A case for deep learning in semantics

Pater's target article builds a persuasive case for establishing stronge...

0 Christopher Potts, et al. ∙

research

∙ 08/25/2018

Representing Social Media Users for Sarcasm Detection

We explore two methods for representing authors in the context of textua...

0 Y. Alex Kolchinski, et al. ∙

research

∙ 03/27/2018

Mittens: An Extension of GloVe for Learning Domain-Specialized Representations

We present a simple extension of the GloVe representation learning model...

0 Nicholas Dingwall, et al. ∙

research

∙ 03/11/2018

Generating Bilingual Pragmatic Color References

Contextual influences on language exhibit substantial language-independe...

0 Will Monroe, et al. ∙

research

∙ 10/05/2017

On the Effective Use of Pretraining for Natural Language Inference

Neural networks have excelled at many NLP tasks, but there remain open q...

0 Ignacio Cases, et al. ∙

research

∙ 08/01/2017

Retrofitting Distributional Embeddings to Knowledge Graphs with Functional Relations

Knowledge graphs are a versatile framework to encode richly structured d...

0 Benjamin J. Lengerich, et al. ∙

Christopher Potts

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