10 citations · 10 across the 12 of their papers we have counts for
6 papers · 1 filter
You Know What I Mean: A Benchmark for Agentic Conversational Reference Grounding
Karen Fuchs, Uri Katz, Yoav Goldberg
Collaborative conversations frequently contain references whose targets are indirect rather than named: resolving "this looks like the fix discussed yesterday" requires combining c…
Factual Retrieval in LLMs Is a Redundant, Distributed and Non-Contiguous Process
Hail Hochman, Natalie Shapira, Yoav Goldberg
Large language models (LLMs) store and recall factual knowledge, yet the precise mechanism of how entity representations are transformed to enable specific attribute retrieval rema…
Compared to What? Baselines and Metrics for Counterfactual Prompting
Zihao Yang, Mosh Levy, Yoav Goldberg +1
Counterfactual prompting (i.e., perturbing a single factor and measuring output change) is widely used to evaluate things like LLM bias and CoT faithfulness. But in this work we ar…
State over Tokens: Characterizing the Role of Reasoning Tokens
Mosh Levy, Zohar Elyoseph, Shauli Ravfogel +1
Large Language Models (LLMs) can generate reasoning tokens before their final answer to boost performance on complex tasks. While these sequences seem like human thought processes,…
Same Task, More Tokens: the Impact of Input Length on the Reasoning Performance of Large Language Models
Mosh Levy, Alon Jacoby, Yoav Goldberg
This paper explores the impact of extending input lengths on the capabilities of Large Language Models (LLMs). Despite LLMs advancements in recent times, their performance consiste…
Leveraging Collection-Wide Similarities for Unsupervised Document Structure Extraction
Gili Lior, Yoav Goldberg, Gabriel Stanovsky
Document collections of various domains, e.g., legal, medical, or financial, often share some underlying collection-wide structure, which captures information that can aid both hum…