21 citations · 51 across the 12 of their papers we have counts for
14 papers
SAGE: Structure Aware Graph Expansion for Retrieval of Heterogeneous Data
Prasham Titiya, Rohit Khoja, Tomer Wolfson +2
Retrieval-augmented question answering over heterogeneous corpora requires connected evidence across text, tables, and graph nodes. While entity-level knowledge graphs support stru…
Decomposed Prompting Does Not Fix Knowledge Gaps, But Helps Models Say "I Don't Know"
Dhruv Madhwal, Lyuxin David Zhang, Dan Roth +2
Large language models often struggle to recognize their knowledge limits in closed-book question answering, leading to confident hallucinations. While decomposed prompting is typic…
MoNaCo: More Natural and Complex Questions for Reasoning Across Dozens of Documents
Tomer Wolfson, Harsh Trivedi, Mor Geva +5
Automated agents, powered by Large language models (LLMs), are emerging as the go-to tool for querying information. However, evaluation benchmarks for LLM agents rarely feature nat…
EnrichIndex: Using LLMs to Enrich Retrieval Indices Offline
Peter Baile Chen, Tomer Wolfson, Michael Cafarella +1
Existing information retrieval systems excel in cases where the language of target documents closely matches that of the user query. However, real-world retrieval systems are often…
Generating Tables from the Parametric Knowledge of Language Models
Yevgeni Berkovitch, Oren Glickman, Amit Somech +1
We explore generating factual and accurate tables from the parametric knowledge of large language models (LLMs). While LLMs have demonstrated impressive capabilities in recreating…
LINX: A Language Driven Generative System for Goal-Oriented Automated Data Exploration
Tavor Lipman, Tova Milo, Amit Somech +2
Data exploration is a challenging process in which users examine a dataset by iteratively employing a series of queries. While in some cases the user explores a new dataset to beco…
Making Retrieval-Augmented Language Models Robust to Irrelevant Context
Ori Yoran, Tomer Wolfson, Ori Ram +1
Retrieval-augmented language models (RALMs) hold promise to produce language understanding systems that are are factual, efficient, and up-to-date. An important desideratum of RALM…
Answering Questions by Meta-Reasoning over Multiple Chains of Thought
Ori Yoran, Tomer Wolfson, Ben Bogin +3
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.…
QAMPARI: An Open-domain Question Answering Benchmark for Questions with Many Answers from Multiple Paragraphs
Samuel Joseph Amouyal, Tomer Wolfson, Ohad Rubin +3
Existing benchmarks for open-domain question answering (ODQA) typically focus on questions whose answers can be extracted from a single paragraph. By contrast, many natural questio…
Weakly Supervised Text-to-SQL Parsing through Question Decomposition
Tomer Wolfson, Daniel Deutch, Jonathan Berant
Text-to-SQL parsers are crucial in enabling non-experts to effortlessly query relational data. Training such parsers, by contrast, generally requires expertise in annotating natura…
Break, Perturb, Build: Automatic Perturbation of Reasoning Paths Through Question Decomposition
Mor Geva, Tomer Wolfson, Jonathan Berant
Recent efforts to create challenge benchmarks that test the abilities of natural language understanding models have largely depended on human annotations. In this work, we introduc…
Obtaining Faithful Interpretations from Compositional Neural Networks
Sanjay Subramanian, Ben Bogin, Nitish Gupta +4
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…
Break It Down: A Question Understanding Benchmark
Tomer Wolfson, Mor Geva, Ankit Gupta +4
Understanding natural language questions entails the ability to break down a question into the requisite steps for computing its answer. In this work, we introduce a Question Decom…
Explaining Queries over Web Tables to Non-Experts
Jonathan Berant, Daniel Deutch, Amir Globerson +2
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) c…