6 papers
User-Centric Evidence Ranking for Attribution and Fact Verification
Guy Alt, Eran Hirsch, Serwar Basch +2
Attribution and fact verification are critical challenges in natural language processing for assessing information reliability. While automated systems and Large Language Models (L…
PrefixNLI: Detecting Factual Inconsistencies as Soon as They Arise
Sapir Harary, Eran Hirsch, Aviv Slobodkin +3
Natural Language Inference (NLI) models have been used in various ways to improve the factuality of LLM outputs. This is typically done by applying an NLI model to judge whether th…
CRISP: Complex Reasoning with Interpretable Step-based Plans
Matan Vetzler, Koren Lazar, Guy Uziel +3
Recent advancements in large language models (LLMs) underscore the need for stronger reasoning capabilities to solve complex problems effectively. While Chain-of-Thought (CoT) reas…
GenerationPrograms: Fine-grained Attribution with Executable Programs
David Wan, Eran Hirsch, Elias Stengel-Eskin +2
Recent large language models (LLMs) achieve impressive performance in source-conditioned text generation but often fail to correctly provide fine-grained attributions for their out…
CLATTER: Comprehensive Entailment Reasoning for Hallucination Detection
Ron Eliav, Arie Cattan, Eran Hirsch +4
A common approach to hallucination detection casts it as a natural language inference (NLI) task, often using LLMs to classify whether the generated text is entailed by correspondi…
LAQuer: Localized Attribution Queries in Content-grounded Generation
Eran Hirsch, Aviv Slobodkin, David Wan +3
Grounded text generation models often produce content that deviates from their source material, requiring user verification to ensure accuracy. Existing attribution methods associa…