43 citations · 55 across the 8 of their papers we have counts for
8 papers · 1 filter
The Curious Case of Hallucinatory (Un)answerability: Finding Truths in the Hidden States of Over-Confident Large Language Models
Aviv Slobodkin, Omer Goldman, Avi Caciularu +2
Large language models (LLMs) have been shown to possess impressive capabilities, while also raising crucial concerns about the faithfulness of their responses. A primary issue aris…
Optimizing Retrieval-augmented Reader Models via Token Elimination
Moshe Berchansky, Peter Izsak, Avi Caciularu +2
Fusion-in-Decoder (FiD) is an effective retrieval-augmented language model applied across a variety of open-domain tasks, such as question answering, fact checking, etc. In FiD, su…
A Comprehensive Evaluation of Tool-Assisted Generation Strategies
Alon Jacovi, Avi Caciularu, Jonathan Herzig +3
A growing area of research investigates augmenting language models with tools (e.g., search engines, calculators) to overcome their shortcomings (e.g., missing or incorrect knowled…
Dont Add, dont Miss: Effective Content Preserving Generation from Pre-Selected Text Spans
Aviv Slobodkin, Avi Caciularu, Eran Hirsch +1
The recently introduced Controlled Text Reduction (CTR) task isolates the text generation step within typical summarization-style tasks. It does so by challenging models to generat…
Representation Learning via Variational Bayesian Networks
Oren Barkan, Avi Caciularu, Idan Rejwan +4
We present Variational Bayesian Network (VBN) - a novel Bayesian entity representation learning model that utilizes hierarchical and relational side information and is particularly…
Revisiting Sentence Union Generation as a Testbed for Text Consolidation
Eran Hirsch, Valentina Pyatkin, Ruben Wolhandler +3
Tasks involving text generation based on multiple input texts, such as multi-document summarization, long-form question answering and contemporary dialogue applications, challenge…