10 citations · 10 across the 12 of their papers we have counts for
13 papers
Quantum-Classical Hybrid Methods for Optimization: Lessons from Classical Decomposition
David E. Bernal Neira
Quantum and physics-inspired solvers provide specialized sampling interfaces for Ising and quadratic unconstrained binary optimization models, but constrained optimization requires…
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…
Forecasting Future Behavior as a Learning Task
Mosh Levy, Yoav Goldberg, Asa Cooper Stickland
Trust in an AI system is often anchored by explanations of how it works, which one then uses to forecast its behavior on new inputs. For large reasoning models (LRMs), this convent…
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…
Understanding Usage and Engagement in AI-Powered Scientific Research Tools: The Asta Interaction Dataset
Dany Haddad, Dan Bareket, Joseph Chee Chang +19
AI-powered scientific research tools are rapidly being integrated into research workflows, yet the field lacks a clear lens into how researchers use these systems in real-world set…
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,…
NER Retriever: Zero-Shot Named Entity Retrieval with Type-Aware Embeddings
Or Shachar, Uri Katz, Yoav Goldberg +1
We present NER Retriever, a zero-shot retrieval framework for ad-hoc Named Entity Retrieval, a variant of Named Entity Recognition (NER), where the types of interest are not provid…
Humans Perceive Wrong Narratives from AI Reasoning Texts
Mosh Levy, Zohar Elyoseph, Yoav Goldberg
A new generation of AI models generates step-by-step reasoning text before producing an answer. This text appears to offer a human-readable window into their computation process, a…
Knowledge Navigator: LLM-guided Browsing Framework for Exploratory Search in Scientific Literature
Uri Katz, Mosh Levy, Yoav Goldberg
The exponential growth of scientific literature necessitates advanced tools for effective knowledge exploration. We present Knowledge Navigator, a system designed to enhance explor…
Evaluating D-MERIT of Partial-annotation on Information Retrieval
Royi Rassin, Yaron Fairstein, Oren Kalinsky +4
Retrieval models are often evaluated on partially-annotated datasets. Each query is mapped to a few relevant texts and the remaining corpus is assumed to be irrelevant. As a result…
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…