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05/24/2023
Attentiveness to Answer Choices Doesn't Always Entail High QA Accuracy
When large language models (LMs) are applied in zero- or few-shot settin...
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05/23/2023
Language Models with Rationality
While large language models (LLMs) are proficient at question-answering ...
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05/23/2023
IfQA: A Dataset for Open-domain Question Answering under Counterfactual Presuppositions
Although counterfactual reasoning is a fundamental aspect of intelligenc...
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05/23/2023
Improving Language Models via Plug-and-Play Retrieval Feedback
Large language models (LLMs) exhibit remarkable performance across vario...
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01/30/2023
Specializing Smaller Language Models towards Multi-Step Reasoning
The surprising ability of Large Language Models (LLMs) to perform well o...
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12/20/2022
DISCO: Distilling Phrasal Counterfactuals with Large Language Models
Recent methods demonstrate that data augmentation using counterfactual k...
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12/20/2022
Interleaving Retrieval with Chain-of-Thought Reasoning for Knowledge-Intensive Multi-Step Questions
Recent work has shown that large language models are capable of generati...
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11/15/2022
Breakpoint Transformers for Modeling and Tracking Intermediate Beliefs
Can we teach natural language understanding models to track their belief...
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10/31/2022
Lila: A Unified Benchmark for Mathematical Reasoning
Mathematical reasoning skills are essential for general-purpose intellig...
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10/06/2022
Transformers Can Be Expressed In First-Order Logic with Majority
Characterizing the implicit structure of the computation within neural n...
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10/05/2022
Decomposed Prompting: A Modular Approach for Solving Complex Tasks
Few-shot prompting is a surprisingly powerful way to use Large Language ...
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10/03/2022
Complexity-Based Prompting for Multi-Step Reasoning
We study the task of prompting large-scale language models to perform mu...
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07/02/2022
Log-Precision Transformers are Constant-Depth Uniform Threshold Circuits
We prove that transformer neural networks with logarithmic precision in ...
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05/25/2022
Teaching Broad Reasoning Skills via Decomposition-Guided Contexts
Question-answering datasets require a broad set of reasoning skills. We ...
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05/07/2022
Better Retrieval May Not Lead to Better Question Answering
Considerable progress has been made recently in open-domain question ans...
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04/19/2022
What Makes Instruction Learning Hard? An Investigation and a New Challenge in a Synthetic Environment
The instruction learning paradigm – where a model learns to perform new ...
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12/16/2021
Pushing the Limits of Rule Reasoning in Transformers through Natural Language Satisfiability
Investigating the reasoning abilities of transformer models, and discove...
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10/27/2021
How Much Coffee Was Consumed During EMNLP 2019? Fermi Problems: A New Reasoning Challenge for AI
Many real-world problems require the combined application of multiple re...
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10/16/2021
Learning to Solve Complex Tasks by Talking to Agents
Humans often solve complex problems by interacting (in natural language)...
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08/02/2021
MuSiQue: Multi-hop Questions via Single-hop Question Composition
To build challenging multi-hop question answering datasets, we propose a...
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06/02/2021
Ethical-Advice Taker: Do Language Models Understand Natural Language Interventions?
Is it possible to use natural language to intervene in a model's behavio...
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04/18/2021
GooAQ: Open Question Answering with Diverse Answer Types
While day-to-day questions come with a variety of answer types, the curr...
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03/23/2021
Multi-Modal Answer Validation for Knowledge-Based VQA
The problem of knowledge-based visual question answering involves answer...
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02/05/2021
Think you have Solved Direct-Answer Question Answering? Try ARC-DA, the Direct-Answer AI2 Reasoning Challenge
We present the ARC-DA dataset, a direct-answer ("open response", "freefo...
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10/24/2020
ReadOnce Transformers: Reusable Representations of Text for Transformers
While large-scale language models are extremely effective when directly ...
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10/24/2020
Temporal Reasoning on Implicit Events from Distant Supervision
Existing works on temporal reasoning among events described in text focu...
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10/06/2020
UNQOVERing Stereotyping Biases via Underspecified Questions
While language embeddings have been shown to have stereotyping biases, h...
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09/01/2020
Text Modular Networks: Learning to Decompose Tasks in the Language of Existing Models
A common approach to solve complex tasks is by breaking them down into s...
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07/01/2020
Belief Propagation Neural Networks
Learned neural solvers have successfully been used to solve combinatoria...
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05/02/2020
Measuring and Reducing Non-Multifact Reasoning in Multi-hop Question Answering
The measurement of true progress in multihop question-answering has been...
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05/02/2020
UnifiedQA: Crossing Format Boundaries With a Single QA System
Question answering (QA) tasks have been posed using a variety of formats...
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04/14/2020
A Simple Yet Strong Pipeline for HotpotQA
State-of-the-art models for multi-hop question answering typically augme...
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04/09/2020
Natural Perturbation for Robust Question Answering
While recent models have achieved human-level scores on many NLP dataset...
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02/10/2020
Adversarial Filters of Dataset Biases
Large neural models have demonstrated human-level performance on languag...
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12/31/2019
What Does My QA Model Know? Devising Controlled Probes using Expert Knowledge
Open-domain question answering (QA) is known to involve several underlyi...
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11/26/2019
Approximating the Permanent by Sampling from Adaptive Partitions
Computing the permanent of a non-negative matrix is a core problem with ...
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11/10/2019
Not All Claims are Created Equal: Choosing the Right Approach to Assess Your Hypotheses
Empirical research in Natural Language Processing (NLP) has adopted a na...
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10/25/2019
QASC: A Dataset for Question Answering via Sentence Composition
Composing knowledge from multiple pieces of texts is a key challenge in ...
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10/13/2019
AdaWISH: Faster Discrete Integration via Adaptive Quantiles
Discrete integration in a high dimensional space of n variables poses fu...
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09/19/2019
What's Missing: A Knowledge Gap Guided Approach for Multi-hop Question Answering
Multi-hop textual question answering requires combining information from...
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09/16/2019
Probing Natural Language Inference Models through Semantic Fragments
Do state-of-the-art models for language understanding already have, or c...
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09/04/2019
From 'F' to 'A' on the N.Y. Regents Science Exams: An Overview of the Aristo Project
AI has achieved remarkable mastery over games such as Chess, Go, and Pok...
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06/09/2019
Question Answering as Global Reasoning over Semantic Abstractions
We propose a novel method for exploiting the semantic structure of text ...
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04/20/2019
Repurposing Entailment for Multi-Hop Question Answering Tasks
Question Answering (QA) naturally reduces to an entailment problem, name...
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01/08/2019
On the Capabilities and Limitations of Reasoning for Natural Language Understanding
Recent systems for natural language understanding are strong at overcomi...
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11/20/2018
QuaRel: A Dataset and Models for Answering Questions about Qualitative Relationships
Many natural language questions require recognizing and reasoning with q...
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11/02/2018
Exploiting Explicit Paths for Multi-hop Reading Comprehension
We focus on the task of multi-hop reading comprehension where a system i...
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09/08/2018
Can a Suit of Armor Conduct Electricity? A New Dataset for Open Book Question Answering
We present a new kind of question answering dataset, OpenBookQA, modeled...
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08/28/2018
Bridging Knowledge Gaps in Neural Entailment via Symbolic Models
Most textual entailment models focus on lexical gaps between the premise...
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05/12/2018
