Hannaneh Hajishirzi

research

∙ 08/08/2023

SILO Language Models: Isolating Legal Risk In a Nonparametric Datastore

The legality of training language models (LMs) on copyrighted or otherwi...

0 Sewon Min, et al. ∙

research

∙ 07/19/2023

Efficiency Pentathlon: A Standardized Arena for Efficiency Evaluation

Rising computational demands of modern natural language processing (NLP)...

0 Hao Peng, et al. ∙

research

∙ 06/02/2023

Fine-Grained Human Feedback Gives Better Rewards for Language Model Training

Language models (LMs) often exhibit undesirable text generation behavior...

5 Zeqiu Wu, et al. ∙

research

∙ 05/27/2023

PuMer: Pruning and Merging Tokens for Efficient Vision Language Models

Large-scale vision language (VL) models use Transformers to perform cros...

0 Qingqing Cao, et al. ∙

research

∙ 05/24/2023

BUFFET: Benchmarking Large Language Models for Few-shot Cross-lingual Transfer

Despite remarkable advancements in few-shot generalization in natural la...

0 Akari Asai, et al. ∙

research

∙ 05/23/2023

FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generation

Evaluating the factuality of long-form text generated by large language ...

0 Sewon Min, et al. ∙

research

∙ 05/22/2023

TaskWeb: Selecting Better Source Tasks for Multi-task NLP

Recent work in NLP has shown promising results in training models on lar...

0 Joongwon Kim, et al. ∙

research

∙ 05/19/2023

Inference-time Re-ranker Relevance Feedback for Neural Information Retrieval

Neural information retrieval often adopts a retrieve-and-rerank framewor...

0 Revanth Gangi Reddy, et al. ∙

research

∙ 04/27/2023

DataComp: In search of the next generation of multimodal datasets

Large multimodal datasets have been instrumental in recent breakthroughs...

0 Samir Yitzhak Gadre, et al. ∙

research

∙ 03/16/2023

ART: Automatic multi-step reasoning and tool-use for large language models

Large language models (LLMs) can perform complex reasoning in few- and z...

0 Bhargavi Paranjape, et al. ∙

research

∙ 12/20/2022

When Not to Trust Language Models: Investigating Effectiveness and Limitations of Parametric and Non-Parametric Memories

Despite their impressive performance on diverse tasks, large language mo...

0 Alex Mallen, et al. ∙

research

∙ 12/19/2022

Z-ICL: Zero-Shot In-Context Learning with Pseudo-Demonstrations

Although large language models can be prompted for both zero- and few-sh...

0 Xinxi Lyu, et al. ∙

research

∙ 12/08/2022

Editing Models with Task Arithmetic

Changing how pre-trained models behave – e.g., improving their performan...

0 Gabriel Ilharco, et al. ∙

research

∙ 12/02/2022

Nonparametric Masked Language Modeling

Existing language models (LMs) predict tokens with a softmax over a fini...

0 Sewon Min, et al. ∙

research

∙ 12/02/2022

AGRO: Adversarial Discovery of Error-prone groups for Robust Optimization

Models trained via empirical risk minimization (ERM) are known to rely o...

0 Bhargavi Paranjape, et al. ∙

research

∙ 12/01/2022

Data-Efficient Finetuning Using Cross-Task Nearest Neighbors

Language models trained on massive prompted multitask datasets like T0 (...

0 Hamish Ivison, et al. ∙

research

∙ 11/30/2022

CREPE: Open-Domain Question Answering with False Presuppositions

Information seeking users often pose questions with false presupposition...

0 Xinyan Velocity Yu, et al. ∙

research

∙ 11/16/2022

Task-aware Retrieval with Instructions

We study the problem of retrieval with instructions, where users of a re...

0 Akari Asai, et al. ∙

research

∙ 10/25/2022

SciFact-Open: Towards open-domain scientific claim verification

While research on scientific claim verification has led to the developme...

17 David Wadden, et al. ∙

research

∙ 10/22/2022

Exploring The Landscape of Distributional Robustness for Question Answering Models

We conduct a large empirical evaluation to investigate the landscape of ...

0 Anas Awadalla, et al. ∙

research

∙ 10/22/2022

Correcting Diverse Factual Errors in Abstractive Summarization via Post-Editing and Language Model Infilling

Abstractive summarization models often generate inconsistent summaries c...

0 Vidhisha Balachandran, et al. ∙

research

∙ 10/10/2022

CORE: A Retrieve-then-Edit Framework for Counterfactual Data Generation

Counterfactual data augmentation (CDA) – i.e., adding minimally perturbe...

0 Tanay Dixit, et al. ∙

research

∙ 08/10/2022

Patching open-vocabulary models by interpolating weights

Open-vocabulary models like CLIP achieve high accuracy across many image...

10 Gabriel Ilharco, et al. ∙

research

∙ 07/02/2022

INSCIT: Information-Seeking Conversations with Mixed-Initiative Interactions

In an information-seeking conversation, a user converses with an agent t...

0 Zeqiu Wu, et al. ∙

research

∙ 05/24/2022

Attentional Mixtures of Soft Prompt Tuning for Parameter-efficient Multi-task Knowledge Sharing

This work introduces ATTEMPT (Attentional Mixture of Prompt Tuning), a n...

13 Akari Asai, et al. ∙

research

∙ 02/25/2022

Rethinking the Role of Demonstrations: What Makes In-Context Learning Work?

Large language models (LMs) are able to in-context learn – perform a new...

2 Sewon Min, et al. ∙

research

∙ 02/23/2022

UnifiedQA-v2: Stronger Generalization via Broader Cross-Format Training

We present UnifiedQA-v2, a QA model built with the same process as Unifi...

0 Daniel Khashabi, et al. ∙

research

∙ 02/22/2022

Knowledge Base Question Answering by Case-based Reasoning over Subgraphs

Question answering (QA) over real-world knowledge bases (KBs) is challen...

7 Rajarshi Das, et al. ∙

research

∙ 12/16/2021

Evidentiality-guided Generation for Knowledge-Intensive NLP Tasks

Retrieval-augmented generation models have shown state-of-the-art perfor...

8 Akari Asai, et al. ∙

research

∙ 12/02/2021

LongChecker: Improving scientific claim verification by modeling full-abstract context

We introduce the LongChecker system for scientific claim verification. G...

8 David Wadden, et al. ∙

research

∙ 12/01/2021

Iconary: A Pictionary-Based Game for Testing Multimodal Communication with Drawings and Text

Communicating with humans is challenging for AIs because it requires a s...

8 Christopher Clark, et al. ∙

research

∙ 10/29/2021

MetaICL: Learning to Learn In Context

We introduce MetaICL (Meta-training for In-Context Learning), a new meta...

0 Sewon Min, et al. ∙

research

∙ 09/16/2021

Reframing Instructional Prompts to GPTk's Language

How can model designers turn task instructions into effective prompts fo...

9 Swaroop Mishra, et al. ∙

research

∙ 09/10/2021

DIALKI: Knowledge Identification in Conversational Systems through Dialogue-Document Contextualization

Identifying relevant knowledge to be used in conversational systems that...

0 Zeqiu Wu, et al. ∙

research

∙ 09/04/2021

Robust fine-tuning of zero-shot models

Large pre-trained models such as CLIP offer consistent accuracy across a...

7 Mitchell Wortsman, et al. ∙

research

∙ 08/09/2021

Noisy Channel Language Model Prompting for Few-Shot Text Classification

We introduce a noisy channel approach for language model prompting in fe...

0 Sewon Min, et al. ∙

research

∙ 07/26/2021

One Question Answering Model for Many Languages with Cross-lingual Dense Passage Retrieval

We present CORA, a Cross-lingual Open-Retrieval Answer Generation model ...

8 Akari Asai, et al. ∙

research

∙ 07/05/2021

FaVIQ: FAct Verification from Information-seeking Questions

Despite significant interest in developing general purpose fact checking...

0 Jungsoo Park, et al. ∙

research

∙ 06/17/2021

Scientific Language Models for Biomedical Knowledge Base Completion: An Empirical Study

Biomedical knowledge graphs (KGs) hold rich information on entities such...

0 Rahul Nadkarni, et al. ∙

research

∙ 06/12/2021

Prompting Contrastive Explanations for Commonsense Reasoning Tasks

Many commonsense reasoning NLP tasks involve choosing between one or mor...

4 Bhargavi Paranjape, et al. ∙

research

∙ 06/02/2021

Efficient Passage Retrieval with Hashing for Open-domain Question Answering

Most state-of-the-art open-domain question answering systems use a neura...

11 Ikuya Yamada, et al. ∙

research

∙ 04/18/2021

Natural Instructions: Benchmarking Generalization to New Tasks from Natural Language Instructions

Can we enable NLP models to appropriately respond to instructional promp...

12 Swaroop Mishra, et al. ∙

research

∙ 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...

0 Daniel Khashabi, et al. ∙

research

∙ 04/17/2021

Joint Passage Ranking for Diverse Multi-Answer Retrieval

We study multi-answer retrieval, an under-explored problem that requires...

0 Sewon Min, et al. ∙

research

∙ 03/24/2021

NaturalProofs: Mathematical Theorem Proving in Natural Language

Understanding and creating mathematics using natural mathematical langua...

0 Sean Welleck, 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

∙ 11/13/2020

IIRC: A Dataset of Incomplete Information Reading Comprehension Questions

Humans often have to read multiple documents to address their informatio...

0 James Ferguson, et al. ∙

research

∙ 10/22/2020

XOR QA: Cross-lingual Open-Retrieval Question Answering

Multilingual question answering tasks typically assume answers exist in ...

9 Akari Asai, et al. ∙

research

∙ 10/12/2020

MedICaT: A Dataset of Medical Images, Captions, and Textual References

Understanding the relationship between figures and text is key to scient...

18 Sanjay Subramanian, et al. ∙

research

∙ 10/08/2020

Extracting a Knowledge Base of Mechanisms from COVID-19 Papers

The urgency of mitigating COVID-19 has spawned a large and diverse body ...

0 Aida Amini, et al. ∙

Hannaneh Hajishirzi

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