activity
20222025
most citedQAID: Question Answering Inspired Few-shot Intent Detection

1 citations · 3 across the 8 of their papers we have counts for

collaborators
Showing cs.CLShow all

6 papers · 1 filter

cs.CL2025

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…

cs.CL2024

SpeCrawler: Generating OpenAPI Specifications from API Documentation Using Large Language Models

Koren Lazar, Matan Vetzler, Guy Uziel +4

In the digital era, the widespread use of APIs is evident. However, scalable utilization of APIs poses a challenge due to structure divergence observed in online API documentation.…

cs.CL2023★ 1 cited

NERetrieve: Dataset for Next Generation Named Entity Recognition and Retrieval

Uri Katz, Matan Vetzler, Amir DN Cohen +1

Recognizing entities in texts is a central need in many information-seeking scenarios, and indeed, Named Entity Recognition (NER) is arguably one of the most successful examples of…

cs.CL2023

Reliable and Interpretable Drift Detection in Streams of Short Texts

Ella Rabinovich, Matan Vetzler, Samuel Ackerman +1

Data drift is the change in model input data that is one of the key factors leading to machine learning models performance degradation over time. Monitoring drift helps detecting t…

cs.CL2023★ 1 cited

QAID: Question Answering Inspired Few-shot Intent Detection

Asaf Yehudai, Matan Vetzler, Yosi Mass +3

Intent detection with semantically similar fine-grained intents is a challenging task. To address it, we reformulate intent detection as a question-answering retrieval task by trea…

cs.CL2022★ 1 cited

Gaining Insights into Unrecognized User Utterances in Task-Oriented Dialog Systems

Ella Rabinovich, Matan Vetzler, David Boaz +3

The rapidly growing market demand for automatic dialogue agents capable of goal-oriented behavior has caused many tech-industry leaders to invest considerable efforts into task-ori…