2 citations · 3 across the 9 of their papers we have counts for
9 papers
Beyond N-Grams: Rethinking Evaluation Metrics and Strategies for Multilingual Abstractive Summarization
Itai Mondshine, Tzuf Paz-Argaman, Reut Tsarfaty
Automatic n-gram based metrics such as ROUGE are widely used for evaluating generative tasks such as summarization. While these metrics are considered indicative (even if imperfect…
Beyond English: The Impact of Prompt Translation Strategies across Languages and Tasks in Multilingual LLMs
Itai Mondshine, Tzuf Paz-Argaman, Reut Tsarfaty
Despite advances in the multilingual capabilities of Large Language Models (LLMs) across diverse tasks, English remains the dominant language for LLM research and development. So,…
Into the Unknown: Generating Geospatial Descriptions for New Environments
Tzuf Paz-Argaman, John Palowitch, Sayali Kulkarni +2
Similar to vision-and-language navigation (VLN) tasks that focus on bridging the gap between vision and language for embodied navigation, the new Rendezvous (RVS) task requires rea…
HeSum: a Novel Dataset for Abstractive Text Summarization in Hebrew
Tzuf Paz-Argaman, Itai Mondshine, Asaf Achi Mordechai +1
While large language models (LLMs) excel in various natural language tasks in English, their performance in lower-resourced languages like Hebrew, especially for generative tasks s…
Where Do We Go from Here? Multi-scale Allocentric Relational Inference from Natural Spatial Descriptions
Tzuf Paz-Argaman, Sayali Kulkarni, John Palowitch +2
When communicating routes in natural language, the concept of acquired spatial knowledge is crucial for geographic information retrieval (GIR) and in spatial cognitive research. Ho…
Apollo: Zero-shot MultiModal Reasoning with Multiple Experts
Daniela Ben-David, Tzuf Paz-Argaman, Reut Tsarfaty
We propose a modular framework that leverages the expertise of different foundation models over different modalities and domains in order to perform a single, complex, multi-modal…
HeGeL: A Novel Dataset for Geo-Location from Hebrew Text
Tzuf Paz-Argaman, Tal Bauman, Itai Mondshine +3
The task of textual geolocation - retrieving the coordinates of a place based on a free-form language description - calls for not only grounding but also natural language understan…
ZEST: Zero-shot Learning from Text Descriptions using Textual Similarity and Visual Summarization
Tzuf Paz-Argaman, Yuval Atzmon, Gal Chechik +1
We study the problem of recognizing visual entities from the textual descriptions of their classes. Specifically, given birds' images with free-text descriptions of their species,…
RUN through the Streets: A New Dataset and Baseline Models for Realistic Urban Navigation
Tzuf Paz-Argaman, Reut Tsarfaty
Following navigation instructions in natural language requires a composition of language, action, and knowledge of the environment. Knowledge of the environment may be provided via…