Search Results for author: Tomer Wolfson

Found 9 papers, 7 papers with code

Generating Tables from the Parametric Knowledge of Language Models

1 code implementation16 Jun 2024 Yevgeni Berkovitch, Oren Glickman, Amit Somech, Tomer Wolfson

We explore generating factual and accurate tables from the parametric knowledge of large language models (LLMs).

Making Retrieval-Augmented Language Models Robust to Irrelevant Context

1 code implementation2 Oct 2023 Ori Yoran, Tomer Wolfson, Ori Ram, Jonathan Berant

An important desideratum of RALMs, is that retrieved information helps model performance when it is relevant, and does not harm performance when it is not.

Language Modelling Natural Language Inference +2

Answering Questions by Meta-Reasoning over Multiple Chains of Thought

1 code implementation25 Apr 2023 Ori Yoran, Tomer Wolfson, Ben Bogin, Uri Katz, Daniel Deutch, Jonathan Berant

Modern systems for multi-hop question answering (QA) typically break questions into a sequence of reasoning steps, termed chain-of-thought (CoT), before arriving at a final answer.

Multi-hop Question Answering Question Answering

Weakly Supervised Text-to-SQL Parsing through Question Decomposition

1 code implementation Findings (NAACL) 2022 Tomer Wolfson, Daniel Deutch, Jonathan Berant

Given questions, their QDMR structures (annotated by non-experts or automatically predicted), and the answers, we are able to automatically synthesize SQL queries that are used to train text-to-SQL models.

SQL Parsing Text-To-SQL

Break, Perturb, Build: Automatic Perturbation of Reasoning Paths Through Question Decomposition

1 code implementation29 Jul 2021 Mor Geva, Tomer Wolfson, Jonathan Berant

We evaluate a range of RC models on our evaluation sets, which reveals large performance gaps on generated examples compared to the original data.

Natural Language Understanding Reading Comprehension

Obtaining Faithful Interpretations from Compositional Neural Networks

1 code implementation ACL 2020 Sanjay Subramanian, Ben Bogin, Nitish Gupta, Tomer Wolfson, Sameer Singh, Jonathan Berant, Matt Gardner

Neural module networks (NMNs) are a popular approach for modeling compositionality: they achieve high accuracy when applied to problems in language and vision, while reflecting the compositional structure of the problem in the network architecture.

Explaining Queries over Web Tables to Non-Experts

no code implementations14 Aug 2018 Jonathan Berant, Daniel Deutch, Amir Globerson, Tova Milo, Tomer Wolfson

Designing a reliable natural language (NL) interface for querying tables has been a longtime goal of researchers in both the data management and natural language processing (NLP) communities.

Management Translation

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