Jonathan Herzig | DeepAI

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∙ 05/23/2023

Evaluating and Modeling Attribution for Cross-Lingual Question Answering

Trustworthy answer content is abundant in many high-resource languages a...

0 Benjamin Müller, et al. ∙

∙ 05/18/2023

TrueTeacher: Learning Factual Consistency Evaluation with Large Language Models

Factual consistency evaluation is often conducted using Natural Language...

0 Zorik Gekhman, et al. ∙

∙ 05/17/2023

What You See is What You Read? Improving Text-Image Alignment Evaluation

Automatically determining whether a text and a corresponding image are s...

0 Michal Yarom, et al. ∙

∙ 12/20/2022

mFACE: Multilingual Summarization with Factual Consistency Evaluation

Abstractive summarization has enjoyed renewed interest in recent years, ...

0 Roee Aharoni, et al. ∙

∙ 05/25/2022

QAMPARI: : An Open-domain Question Answering Benchmark for Questions with Many Answers from Multiple Paragraphs

Existing benchmarks for open-domain question answering (ODQA) typically ...

4 Samuel Joseph Amouyal, et al. ∙

∙ 05/24/2022

Evaluating the Impact of Model Scale for Compositional Generalization in Semantic Parsing

Despite their strong performance on many tasks, pre-trained language mod...

0 Linlu Qiu, et al. ∙

∙ 04/11/2022

TRUE: Re-evaluating Factual Consistency Evaluation

Grounded text generation systems often generate text that contains factu...

2 Or Honovich, et al. ∙

∙ 12/16/2021

Learning To Retrieve Prompts for In-Context Learning

In-context learning is a recent paradigm in natural language understandi...

0 Ohad Rubin, et al. ∙

∙ 09/06/2021

Finding needles in a haystack: Sampling Structurally-diverse Training Sets from Synthetic Data for Compositional Generalization

Modern semantic parsers suffer from two principal limitations. First, tr...

0 Inbar Oren, et al. ∙

∙ 03/22/2021

Open Domain Question Answering over Tables via Dense Retrieval

Recent advances in open-domain QA have led to strong models based on den...

11 Jonathan Herzig, et al. ∙

∙ 10/12/2020

Improving Compositional Generalization in Semantic Parsing

Generalization of models to out-of-distribution (OOD) data has captured ...

0 Inbar Oren, et al. ∙

∙ 09/13/2020

Span-based Semantic Parsing for Compositional Generalization

Despite the success of sequence-to-sequence (seq2seq) models in semantic...

0 Jonathan Herzig, et al. ∙

∙ 04/05/2020

TAPAS: Weakly Supervised Table Parsing via Pre-training

Answering natural language questions over tables is usually seen as a se...

10 Jonathan Herzig, et al. ∙

∙ 08/29/2019

A Summarization System for Scientific Documents

We present a novel system providing summaries for Computer Science publi...

0 Shai Erera, et al. ∙

∙ 08/26/2019

Don't paraphrase, detect! Rapid and Effective Data Collection for Semantic Parsing

A major hurdle on the road to conversational interfaces is the difficult...

20 Jonathan Herzig, et al. ∙

∙ 06/04/2019

TalkSumm: A Dataset and Scalable Annotation Method for Scientific Paper Summarization Based on Conference Talks

Currently, no large-scale training data is available for the task of sci...

0 Guy Lev, et al. ∙

∙ 11/02/2018

Value-based Search in Execution Space for Mapping Instructions to Programs

Training models to map natural language instructions to programs given t...

0 Dor Muhlgay, et al. ∙

∙ 11/02/2018

CommonsenseQA: A Question Answering Challenge Targeting Commonsense Knowledge

When answering a question, people often draw upon their rich world knowl...

0 Alon Talmor, et al. ∙

∙ 04/21/2018

Decoupling Structure and Lexicon for Zero-Shot Semantic Parsing

Building a semantic parser quickly in a new domain is a fundamental chal...

0 Jonathan Herzig, et al. ∙

∙ 11/15/2017

Detecting Egregious Conversations between Customers and Virtual Agents

Virtual agents are becoming a prominent channel of interaction in custom...

0 Tommy Sandbank, et al. ∙

∙ 02/06/2017

Neural Semantic Parsing over Multiple Knowledge-bases

A fundamental challenge in developing semantic parsers is the paucity of...

0 Jonathan Herzig, et al. ∙

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