172 citations · 646 across the 82 of their papers we have counts for
9 papers · 1 filter
OpenAsp: A Benchmark for Multi-document Open Aspect-based Summarization
Shmuel Amar, Liat Schiff, Ori Ernst +3
The performance of automatic summarization models has improved dramatically in recent years. Yet, there is still a gap in meeting specific information needs of users in real-world…
CHAMP: Efficient Annotation and Consolidation of Cluster Hierarchies
Arie Cattan, Tom Hope, Doug Downey +4
Various NLP tasks require a complex hierarchical structure over nodes, where each node is a cluster of items. Examples include generating entailment graphs, hierarchical cross-docu…
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…
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…
SummHelper: Collaborative Human-Computer Summarization
Aviv Slobodkin, Niv Nachum, Shmuel Amar +2
Current approaches for text summarization are predominantly automatic, with rather limited space for human intervention and control over the process. In this paper, we introduce Su…