b'Danqi Chen'

research

∙ 06/01/2023

Learning Transformer Programs

Recent research in mechanistic interpretability has attempted to reverse...

0 Dan Friedman, et al. ∙

research

∙ 05/27/2023

Fine-Tuning Language Models with Just Forward Passes

Fine-tuning language models (LMs) has yielded success on diverse downstr...

8 Sadhika Malladi, et al. ∙

research

∙ 05/24/2023

CSTS: Conditional Semantic Textual Similarity

Semantic textual similarity (STS) has been a cornerstone task in NLP tha...

0 Ameet Deshpande, et al. ∙

research

∙ 05/24/2023

Privacy Implications of Retrieval-Based Language Models

Retrieval-based language models (LMs) have demonstrated improved interpr...

0 Yangsibo Huang, et al. ∙

research

∙ 05/24/2023

Adapting Language Models to Compress Contexts

Transformer-based language models (LMs) are powerful and widely-applicab...

0 Alexis Chevalier, et al. ∙

research

∙ 05/24/2023

Enabling Large Language Models to Generate Text with Citations

Large language models (LLMs) have emerged as a widely-used tool for info...

10 Tianyu Gao, et al. ∙

research

∙ 05/16/2023

What In-Context Learning "Learns" In-Context: Disentangling Task Recognition and Task Learning

Large language models (LLMs) exploit in-context learning (ICL) to solve ...

10 Jane Pan, et al. ∙

research

∙ 12/20/2022

Controllable Text Generation with Language Constraints

We consider the task of text generation in language models with constrai...

0 Howard Chen, et al. ∙

research

∙ 12/19/2022

Training Trajectories of Language Models Across Scales

Scaling up language models has led to unprecedented performance gains, b...

0 Mengzhou Xia, et al. ∙

research

∙ 10/26/2022

MABEL: Attenuating Gender Bias using Textual Entailment Data

Pre-trained language models encode undesirable social biases, which are ...

0 Jacqueline He, et al. ∙

research

∙ 10/26/2022

Don't Prompt, Search! Mining-based Zero-Shot Learning with Language Models

Masked language models like BERT can perform text classification in a ze...

0 Mozes van de Kar, et al. ∙

research

∙ 10/20/2022

Finding Dataset Shortcuts with Grammar Induction

Many NLP datasets have been found to contain shortcuts: simple decision ...

0 Dan Friedman, et al. ∙

research

∙ 10/11/2022

A Kernel-Based View of Language Model Fine-Tuning

It has become standard to solve NLP tasks by fine-tuning pre-trained lan...

0 Sadhika Malladi, et al. ∙

research

∙ 05/30/2022

Prompting ELECTRA: Few-Shot Learning with Discriminative Pre-Trained Models

Pre-trained masked language models successfully perform few-shot learnin...

0 Mengzhou Xia, et al. ∙

research

∙ 05/25/2022

Refining Query Representations for Dense Retrieval at Test Time

Dense retrieval uses a contrastive learning framework to learn dense rep...

0 Mujeen Sung, et al. ∙

research

∙ 05/25/2022

Training Language Models with Memory Augmentation

Recent work has improved language models remarkably by equipping them wi...

0 Zexuan Zhong, et al. ∙

research

∙ 05/25/2022

Generating Natural Language Proofs with Verifier-Guided Search

Deductive reasoning (drawing conclusions from assumptions) is a challeng...

0 Kaiyu Yang, et al. ∙

research

∙ 05/17/2022

Recovering Private Text in Federated Learning of Language Models

Federated learning allows distributed users to collaboratively train a m...

6 Samyak Gupta, et al. ∙

research

∙ 04/25/2022

Can Rationalization Improve Robustness?

A growing line of work has investigated the development of neural NLP mo...

2 Howard Chen, et al. ∙

research

∙ 04/01/2022

Structured Pruning Learns Compact and Accurate Models

The growing size of neural language models has led to increased attentio...

0 Mengzhou Xia, et al. ∙

research

∙ 02/16/2022

Should You Mask 15

Masked language models conventionally use a masking rate of 15 belief th...

5 Alexander Wettig, et al. ∙

research

∙ 12/16/2021

Ditch the Gold Standard: Re-evaluating Conversational Question Answering

Conversational question answering (CQA) systems aim to provide natural-l...

2 Huihan Li, et al. ∙

research

∙ 09/28/2021

Single-dataset Experts for Multi-dataset Question Answering

Many datasets have been created for training reading comprehension model...

0 Dan Friedman, et al. ∙

research

∙ 09/17/2021

Simple Entity-Centric Questions Challenge Dense Retrievers

Open-domain question answering has exploded in popularity recently due t...

0 Christopher Sciavolino, et al. ∙

research

∙ 09/16/2021

Phrase Retrieval Learns Passage Retrieval, Too

Dense retrieval methods have shown great promise over sparse retrieval m...

0 Jinhyuk Lee, et al. ∙

research

∙ 04/26/2021

Non-Parametric Few-Shot Learning for Word Sense Disambiguation

Word sense disambiguation (WSD) is a long-standing problem in natural la...

0 Howard Chen, et al. ∙

research

∙ 04/18/2021

SimCSE: Simple Contrastive Learning of Sentence Embeddings

This paper presents SimCSE, a simple contrastive learning framework that...

16 Tianyu Gao, et al. ∙

research

∙ 04/12/2021

Factual Probing Is [MASK]: Learning vs. Learning to Recall

Petroni et al. (2019) demonstrated that it is possible to retrieve world...

0 Zexuan Zhong, et al. ∙

research

∙ 01/01/2021

NeurIPS 2020 EfficientQA Competition: Systems, Analyses and Lessons Learned

We review the EfficientQA competition from NeurIPS 2020. The competition...

15 Sewon Min, et al. ∙

research

∙ 12/31/2020

Making Pre-trained Language Models Better Few-shot Learners

The recent GPT-3 model (Brown et al., 2020) achieves remarkable few-shot...

11 Tianyu Gao, et al. ∙

research

∙ 12/23/2020

Learning Dense Representations of Phrases at Scale

Open-domain question answering can be reformulated as a phrase retrieval...

0 Jinhyuk Lee, et al. ∙

research

∙ 10/24/2020

A Frustratingly Easy Approach for Joint Entity and Relation Extraction

End-to-end relation extraction aims to identify named entities and extra...

0 Zexuan Zhong, et al. ∙

research

∙ 10/12/2020

TextHide: Tackling Data Privacy in Language Understanding Tasks

An unsolved challenge in distributed or federated learning is to effecti...

7 Yangsibo Huang, et al. ∙

research

∙ 04/10/2020

Dense Passage Retrieval for Open-Domain Question Answering

Open-domain question answering relies on efficient passage retrieval to ...

0 Vladimir Karpukhin, et al. ∙

research

∙ 11/10/2019

Knowledge Guided Text Retrieval and Reading for Open Domain Question Answering

This paper presents a general approach for open-domain question answerin...

30 Sewon Min, et al. ∙

research

∙ 10/22/2019

MRQA 2019 Shared Task: Evaluating Generalization in Reading Comprehension

We present the results of the Machine Reading for Question Answering (MR...

0 Adam Fisch, et al. ∙

research

∙ 09/11/2019

A Discrete Hard EM Approach for Weakly Supervised Question Answering

Many question answering (QA) tasks only provide weak supervision for how...

0 Sewon Min, et al. ∙

research

∙ 07/26/2019

RoBERTa: A Robustly Optimized BERT Pretraining Approach

Language model pretraining has led to significant performance gains but ...

0 Yinhan Liu, et al. ∙

research

∙ 07/24/2019

SpanBERT: Improving Pre-training by Representing and Predicting Spans

We present SpanBERT, a pre-training method that is designed to better re...

0 Mandar Joshi, et al. ∙

research

∙ 08/21/2018

CoQA: A Conversational Question Answering Challenge

Humans gather information by engaging in conversations involving a serie...

4 Siva Reddy, et al. ∙

research

∙ 03/31/2017

Reading Wikipedia to Answer Open-Domain Questions

This paper proposes to tackle open- domain question answering using Wiki...

0 Danqi Chen, et al. ∙

research

∙ 06/09/2016

A Thorough Examination of the CNN/Daily Mail Reading Comprehension Task

Enabling a computer to understand a document so that it can answer compr...

0 Danqi Chen, et al. ∙

research

∙ 01/16/2013

Learning New Facts From Knowledge Bases With Neural Tensor Networks and Semantic Word Vectors

Knowledge bases provide applications with the benefit of easily accessib...

0 Danqi Chen, et al. ∙

Danqi Chen

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