no code implementations • *SEM (NAACL) 2022 • Ronen Tamari, Kyle Richardson, Noam Kahlon, Aviad Sar-Shalom, Nelson F. Liu, Reut Tsarfaty, Dafna Shahaf
However, the main synthetic resource for story understanding, the bAbI benchmark, lacks such a systematic mechanism for controllable task generation.
1 code implementation • 3 Oct 2024 • Oren Sultan, Alex Khasin, Guy Shiran, Asnat Greenstein-Messica, Dafna Shahaf
We present a practical distillation approach to fine-tune LLMs for invoking tools in real-time applications.
1 code implementation • 2 Mar 2024 • Oren Sultan, Yonatan Bitton, Ron Yosef, Dafna Shahaf
We demonstrate our pipeline and create ProPara-Logy, a dataset of analogies between scientific processes.
2 code implementations • 31 Dec 2023 • Moran Mizrahi, Guy Kaplan, Dan Malkin, Rotem Dror, Dafna Shahaf, Gabriel Stanovsky
Recent advances in large language models (LLMs) have led to the development of various evaluation benchmarks.
1 code implementation • 20 Dec 2023 • Hen Emuna, Nadav Borenstein, Xin Qian, Hyeonsu Kang, Joel Chan, Aniket Kittur, Dafna Shahaf
We release data and code; we view BARcode as a step towards addressing the challenges that have historically hindered the practical application of BID to engineering innovation.
no code implementations • 3 Nov 2023 • Shahar Jacob, Chen Shani, Dafna Shahaf
In this work, we relax the input requirements, requiring only names of entities to be mapped.
1 code implementation • 3 Nov 2023 • Chen Shani, Jilles Vreeken, Dafna Shahaf
Concepts play a pivotal role in various human cognitive functions, including learning, reasoning and communication.
1 code implementation • 27 Mar 2023 • Ron Yosef, Yonatan Bitton, Dafna Shahaf
We release our dataset, benchmark, and code, in hopes of driving the development of models that can better understand figurative language.
1 code implementation • 8 Dec 2022 • Yonatan Bitton, Ron Yosef, Eli Strugo, Dafna Shahaf, Roy Schwartz, Gabriel Stanovsky
We leverage situation recognition annotations and the CLIP model to generate a large set of 500k candidate analogies.
Ranked #1 on
Visual Reasoning
on VASR
no code implementations • 15 Nov 2022 • Chen Shani, Jonathan Zarecki, Dafna Shahaf
Machine learning (ML) is revolutionizing the world, affecting almost every field of science and industry.
1 code implementation • 15 Nov 2022 • Kyle Richardson, Ronen Tamari, Oren Sultan, Reut Tsarfaty, Dafna Shahaf, Ashish Sabharwal
Can we teach natural language understanding models to track their beliefs through intermediate points in text?
no code implementations • 31 Oct 2022 • Moran Mizrahi, Dafna Shahaf
The web is full of guidance on a wide variety of tasks, from changing the oil in your car to baking an apple pie.
1 code implementation • 24 Oct 2022 • Dan Ofer, Dafna Shahaf
We introduce a novel dataset of 300, 000 online games of Cards Against Humanity, including 785K unique jokes, analyze it and provide insights.
2 code implementations • 21 Oct 2022 • Oren Sultan, Dafna Shahaf
Analogy-making gives rise to reasoning, abstraction, flexible categorization and counterfactual inference -- abilities lacking in even the best AI systems today.
no code implementations • 30 Nov 2021 • Ronen Tamari, Kyle Richardson, Aviad Sar-Shalom, Noam Kahlon, Nelson Liu, Reut Tsarfaty, Dafna Shahaf
However, the main synthetic resource for story understanding, the bAbI benchmark, lacks such a systematic mechanism for controllable task generation.
no code implementations • 13 Oct 2021 • David Tsurel, Michael Doron, Alexander Nus, Arnon Dagan, Ido Guy, Dafna Shahaf
E-Commerce marketplaces support millions of daily transactions, and some disagreements between buyers and sellers are unavoidable.
no code implementations • ACL 2021 • Nir Sweed, Dafna Shahaf
In this paper, we study snowclones originating from pop-culture quotes; our goal is to automatically detect cultural references in text.
1 code implementation • ACL 2021 • Chen Shani, Nadav Borenstein, Dafna Shahaf
We construct a dataset containing thousands of funny papers and use it to learn classifiers, combining findings from psychology and linguistics with recent advances in NLP.
no code implementations • 12 May 2021 • Chen Shani, Alexander Libov, Sofia Tolmach, Liane Lewin-Eytan, Yoelle Maarek, Dafna Shahaf
Examples include jokes or absurd requests or questions such as, "Are you afraid of the dark?
no code implementations • 19 Feb 2021 • Tom Hope, Ronen Tamari, Hyeonsu Kang, Daniel Hershcovich, Joel Chan, Aniket Kittur, Dafna Shahaf
Large repositories of products, patents and scientific papers offer an opportunity for building systems that scour millions of ideas and help users discover inspirations.
1 code implementation • Findings of the Association for Computational Linguistics 2020 • Moran Mizrahi, Stav Yardeni Seelig, Dafna Shahaf
Spoken languages are ever-changing, with new words entering them all the time.
no code implementations • ACL 2020 • Ronen Tamari, Chen Shani, Tom Hope, Miriam R. L. Petruck, Omri Abend, Dafna Shahaf
While natural language understanding (NLU) is advancing rapidly, today's technology differs from human-like language understanding in fundamental ways, notably in its inferior efficiency, interpretability, and generalization.
no code implementations • 10 Mar 2020 • Ronen Tamari, Gabriel Stanovsky, Dafna Shahaf, Reut Tsarfaty
Large-scale natural language understanding (NLU) systems have made impressive progress: they can be applied flexibly across a variety of tasks, and employ minimal structural assumptions.
1 code implementation • WS 2019 • Ronen Tamari, Hiroyuki Shindo, Dafna Shahaf, Yuji Matsumoto
Understanding procedural text requires tracking entities, actions and effects as the narrative unfolds.
no code implementations • 19 Dec 2017 • Karni Gilon, Felicia Y Ng, Joel Chan, Hila Lifshitz Assaf, Aniket Kittur, Dafna Shahaf
Finding analogical inspirations in distant domains is a powerful way of solving problems.
1 code implementation • 13 Dec 2017 • Tom Hope, Dafna Shahaf
By collecting rough guesses on groups of instances and using machine learning to infer the individual labels, our lightweight framework is able to address core crowdsourcing challenges and train machine learning models in a cost-effective way.
no code implementations • 10 Aug 2017 • Asaf Valadarsky, Michael Schapira, Dafna Shahaf, Aviv Tamar
Can ideas and techniques from machine learning be leveraged to automatically generate "good" routing configurations?
no code implementations • 17 Jun 2017 • Tom Hope, Joel Chan, Aniket Kittur, Dafna Shahaf
The availability of large idea repositories (e. g., the U. S. patent database) could significantly accelerate innovation and discovery by providing people with inspiration from solutions to analogous problems.
no code implementations • 30 Jun 2016 • Tom Hope, Dafna Shahaf
We are interested in estimating individual labels given only coarse, aggregated signal over the data points.