research
∙
09/21/2023
ContextRef: Evaluating Referenceless Metrics For Image Description Generation
Referenceless metrics (e.g., CLIPScore) use pretrained vision–language m...
share
research
∙
09/19/2023
Rigorously Assessing Natural Language Explanations of Neurons
Natural language is an appealing medium for explaining how large languag...
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...
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...
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...
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...
research
∙
05/15/2023
Characterizing Image Accessibility on Wikipedia across Languages
We make a first attempt to characterize image accessibility on Wikipedia...
research
∙
05/15/2023
Interpretability at Scale: Identifying Causal Mechanisms in Alpaca
Obtaining human-interpretable explanations of large, general-purpose lan...
research
∙
03/05/2023
Finding Alignments Between Interpretable Causal Variables and Distributed Neural Representations
Causal abstraction is a promising theoretical framework for explainable ...
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...
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...
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...
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...
research
∙
12/02/2022
Moving Beyond Downstream Task Accuracy for Information Retrieval Benchmarking
Neural information retrieval (IR) systems have progressed rapidly in rec...
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...
research
∙
09/28/2022
Causal Proxy Models for Concept-Based Model Explanations
Explainability methods for NLP systems encounter a version of the fundam...
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...
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...
research
∙
05/19/2022
PLAID: An Efficient Engine for Late Interaction Retrieval
Pre-trained language models are increasingly important components across...
research
∙
05/18/2022
Color Overmodification Emerges from Data-Driven Learning and Pragmatic Reasoning
Speakers' referential expressions often depart from communicative ideals...
research
∙
12/05/2021
Causal Distillation for Language Models
Distillation efforts have led to language models that are more compact a...
research
∙
12/02/2021
ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction
Neural information retrieval (IR) has greatly advanced search and other ...
research
∙
12/01/2021
Inducing Causal Structure for Interpretable Neural Networks
In many areas, we have well-founded insights about causal structure that...
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 ...
research
∙
09/18/2021
ReaSCAN: Compositional Reasoning in Language Grounding
The ability to compositionally map language to referents, relations, and...
research
∙
06/06/2021
Causal Abstractions of Neural Networks
Structural analysis methods (e.g., probing and feature attribution) are ...
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...
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...
research
∙
04/16/2021
Concadia: Tackling image accessibility with context
Images have become an integral part of online media. This has enhanced s...
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...
research
∙
12/30/2020
DynaSent: A Dynamic Benchmark for Sentiment Analysis
We introduce DynaSent ('Dynamic Sentiment'), a new English-language benc...
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...
research
∙
07/01/2020
Relevance-guided Supervision for OpenQA with ColBERT
Systems for Open-Domain Question Answering (OpenQA) generally depend on ...
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...
research
∙
06/14/2020
Relational reasoning and generalization using non-symbolic neural networks
Humans have a remarkable capacity to reason about abstract relational st...
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 ...
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...
research
∙
04/29/2020
Pragmatic Issue-Sensitive Image Captioning
Image captioning systems have recently improved dramatically, but they s...
research
∙
09/25/2019
TalkDown: A Corpus for Condescension Detection in Context
Condescending language use is caustic; it can bring dialogues to an end ...
research
∙
09/16/2019
Communication-based Evaluation for Natural Language Generation
Natural language generation (NLG) systems are commonly evaluated using n...
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...
research
∙
10/31/2018
Effective Feature Representation for Clinical Text Concept Extraction
Crucial information about the practice of healthcare is recorded only in...
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...
research
∙
09/30/2018
An Incremental Iterated Response Model of Pragmatics
Recent Iterated Response (IR) models of pragmatics conceptualize languag...
research
∙
09/10/2018
A case for deep learning in semantics
Pater's target article builds a persuasive case for establishing stronge...
research
∙
08/25/2018
Representing Social Media Users for Sarcasm Detection
We explore two methods for representing authors in the context of textua...
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...
research
∙
03/11/2018
Generating Bilingual Pragmatic Color References
Contextual influences on language exhibit substantial language-independe...
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...
research
∙
08/01/2017