Search Results for author: Arie Cattan

Found 17 papers, 14 papers with code

Attribute First, then Generate: Locally-attributable Grounded Text Generation

no code implementations25 Mar 2024 Aviv Slobodkin, Eran Hirsch, Arie Cattan, Tal Schuster, Ido Dagan

Recent efforts to address hallucinations in Large Language Models (LLMs) have focused on attributed text generation, which supplements generated texts with citations of supporting sources for post-generation fact-checking and corrections.

Attribute Document Summarization +5

From Key Points to Key Point Hierarchy: Structured and Expressive Opinion Summarization

1 code implementation6 Jun 2023 Arie Cattan, Lilach Eden, Yoav Kantor, Roy Bar-Haim

Key Point Analysis (KPA) has been recently proposed for deriving fine-grained insights from collections of textual comments.

Natural Language Inference Opinion Summarization +1

Evaluating and Improving the Coreference Capabilities of Machine Translation Models

no code implementations16 Feb 2023 Asaf Yehudai, Arie Cattan, Omri Abend, Gabriel Stanovsky

Machine translation (MT) requires a wide range of linguistic capabilities, which current end-to-end models are expected to learn implicitly by observing aligned sentences in bilingual corpora.

coreference-resolution Machine Translation +1

How "Multi" is Multi-Document Summarization?

1 code implementation23 Oct 2022 Ruben Wolhandler, Arie Cattan, Ori Ernst, Ido Dagan

To that end, we propose an automated measure for evaluating the degree to which a summary is ``disperse'', in the sense of the number of source documents needed to cover its content.

Document Summarization Multi-Document Summarization

F-coref: Fast, Accurate and Easy to Use Coreference Resolution

1 code implementation9 Sep 2022 Shon Otmazgin, Arie Cattan, Yoav Goldberg

We introduce fastcoref, a python package for fast, accurate, and easy-to-use English coreference resolution.

coreference-resolution

LingMess: Linguistically Informed Multi Expert Scorers for Coreference Resolution

2 code implementations25 May 2022 Shon Otmazgin, Arie Cattan, Yoav Goldberg

While coreference resolution typically involves various linguistic challenges, recent models are based on a single pairwise scorer for all types of pairs.

coreference-resolution

Realistic Evaluation Principles for Cross-document Coreference Resolution

1 code implementation Joint Conference on Lexical and Computational Semantics 2021 Arie Cattan, Alon Eirew, Gabriel Stanovsky, Mandar Joshi, Ido Dagan

We point out that common evaluation practices for cross-document coreference resolution have been unrealistically permissive in their assumed settings, yielding inflated results.

coreference-resolution Cross Document Coreference Resolution

Cross-document Coreference Resolution over Predicted Mentions

1 code implementation Findings (ACL) 2021 Arie Cattan, Alon Eirew, Gabriel Stanovsky, Mandar Joshi, Ido Dagan

Here, we introduce the first end-to-end model for CD coreference resolution from raw text, which extends the prominent model for within-document coreference to the CD setting.

coreference-resolution Cross Document Coreference Resolution

WEC: Deriving a Large-scale Cross-document Event Coreference dataset from Wikipedia

2 code implementations NAACL 2021 Alon Eirew, Arie Cattan, Ido Dagan

To complement these resources and enhance future research, we present Wikipedia Event Coreference (WEC), an efficient methodology for gathering a large-scale dataset for cross-document event coreference from Wikipedia, where coreference links are not restricted within predefined topics.

coreference-resolution Event Coreference Resolution

CD\^2CR: Co-reference resolution across documents and domains

no code implementations EACL 2021 James Ravenscroft, Amanda Clare, Arie Cattan, Ido Dagan, Maria Liakata

Cross-document co-reference resolution (CDCR) is the task of identifying and linking mentions to entities and concepts across many text documents.

CD2CR: Co-reference Resolution Across Documents and Domains

1 code implementation29 Jan 2021 James Ravenscroft, Arie Cattan, Amanda Clare, Ido Dagan, Maria Liakata

Cross-document co-reference resolution (CDCR) is the task of identifying and linking mentions to entities and concepts across many text documents.

CDLM: Cross-Document Language Modeling

2 code implementations Findings (EMNLP) 2021 Avi Caciularu, Arman Cohan, Iz Beltagy, Matthew E. Peters, Arie Cattan, Ido Dagan

We introduce a new pretraining approach geared for multi-document language modeling, incorporating two key ideas into the masked language modeling self-supervised objective.

Citation Recommendation Coreference Resolution +6

CoRefi: A Crowd Sourcing Suite for Coreference Annotation

2 code implementations EMNLP 2020 Aaron Bornstein, Arie Cattan, Ido Dagan

Coreference annotation is an important, yet expensive and time consuming, task, which often involved expert annotators trained on complex decision guidelines.

Cross Document Coreference Resolution

Streamlining Cross-Document Coreference Resolution: Evaluation and Modeling

2 code implementations23 Sep 2020 Arie Cattan, Alon Eirew, Gabriel Stanovsky, Mandar Joshi, Ido Dagan

Recent evaluation protocols for Cross-document (CD) coreference resolution have often been inconsistent or lenient, leading to incomparable results across works and overestimation of performance.

coreference-resolution Cross Document Coreference Resolution +2

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