26 citations · 56 across the 23 of their papers we have counts for
6 papers · 1 filter
QAPyramid: Fine-grained Evaluation of Content Selection for Text Summarization
Shiyue Zhang, David Wan, Arie Cattan +3
How to properly conduct human evaluations for text summarization is a longstanding challenge. The Pyramid human evaluation protocol, which assesses content selection by breaking th…
Localizing Factual Inconsistencies in Attributable Text Generation
Arie Cattan, Paul Roit, Shiyue Zhang +5
There has been an increasing interest in detecting hallucinations in model-generated texts, both manually and automatically, at varying levels of granularity. However, most existin…
Explicating the Implicit: Argument Detection Beyond Sentence Boundaries
Paul Roit, Aviv Slobodkin, Eran Hirsch +4
Detecting semantic arguments of a predicate word has been conventionally modeled as a sentence-level task. The typical reader, however, perfectly interprets predicate-argument rela…
SEAM: A Stochastic Benchmark for Multi-Document Tasks
Gili Lior, Avi Caciularu, Arie Cattan +3
Various tasks, such as summarization, multi-hop question answering, or coreference resolution, are naturally phrased over collections of real-world documents. Such tasks present a…
DoubleDipper: Improving Long-Context LLMs via Context Recycling
Arie Cattan, Alon Jacovi, Alex Fabrikant +8
Despite recent advancements in Large Language Models (LLMs), their performance on tasks involving long contexts remains sub-optimal. In this work, we propose DoubleDipper, a novel…
Attribute First, then Generate: Locally-attributable Grounded Text Generation
Aviv Slobodkin, Eran Hirsch, Arie Cattan +2
Recent efforts to address hallucinations in Large Language Models (LLMs) have focused on attributed text generation, which supplements generated texts with citations of supporting…