Yehonatan Elisha

24 papers A* 9A 3Journal 10Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Concept-Guided Fine-Tuning: Steering ViTs away from Spurious Correlations to Improve Robustness. CoRR Yehonatan Elisha, Oren Barkan, Noam Koenigstein
2026	A*	`conf`	Extracting Interaction-Aware Monosemantic Concepts in Recommender Systems. AAAI Dor Arviv, Yehonatan Elisha, Oren Barkan, Noam Koenigstein
2026	A*	`conf`	Fidelity-Aware Recommendation Explanations via Stochastic Path Integration. AAAI Oren Barkan, Yahlly Schein, Yehonatan Elisha, Veronika Bogina, Mikhail Baklanov, Noam Koenigstein
2026	J	`jnl`	LXR: Learning to eXplain Recommendations. Trans. Recomm. Syst. Liya Gurevitch, Veronika Bogina, Oren Barkan, Yahlly Schein, Yehonatan Elisha, Noam Koenigstein
2026	A*	`conf`	Rethinking Saliency Maps: A Cognitive Human Aligned Taxonomy and Evaluation Framework for Explanations. AAAI Yehonatan Elisha, Seffi Cohen, Oren Barkan, Noam Koenigstein
2025	A*	`conf`	BEE: Metric-Adapted Explanations via Baseline Exploration-Exploitation. AAAI Oren Barkan, Yehonatan Elisha, Jonathan Weill, Noam Koenigstein
2025	J	`jnl`	Extracting Interaction-Aware Monosemantic Concepts in Recommender Systems. CoRR Dor Arviv, Yehonatan Elisha, Oren Barkan, Noam Koenigstein
2025	J	`jnl`	Fidelity-Aware Recommendation Explanations via Stochastic Path Integration. CoRR Oren Barkan, Yahlly Schein, Yehonatan Elisha, Veronika Bogina, Mikhail Baklanov, Noam Koenigstein
2025	A*	`conf`	Forget What You Know about LLMs Evaluations - LLMs are Like a Chameleon. EMNLP Nurit Cohen-Inger, Yehonatan Elisha, Bracha Shapira, Lior Rokach, Seffi Cohen
2025	J	`jnl`	Forget What You Know about LLMs Evaluations - LLMs are Like a Chameleon. CoRR Nurit Cohen-Inger, Yehonatan Elisha, Bracha Shapira, Lior Rokach, Seffi Cohen
2025	A*	`conf`	Refining Fidelity Metrics for Explainable Recommendations. SIGIR Mikhail Baklanov, Veronika Bogina, Yehonatan Elisha, Yahlly Schein, Liron I. Allerhand, Oren Barkan, Noam Koenigstein
2025	J	`jnl`	Rethinking Saliency Maps: A Cognitive Human Aligned Taxonomy and Evaluation Framework for Explanations. CoRR Yehonatan Elisha, Seffi Cohen, Oren Barkan, Noam Koenigstein
2024	A	`conf`	A Learning-based Approach for Explaining Language Models. CIKM Oren Barkan, Yonatan Toib, Yehonatan Elisha, Noam Koenigstein
2024	J	`jnl`	BEE: Metric-Adapted Explanations via Baseline Exploration-Exploitation. CoRR Oren Barkan, Yehonatan Elisha, Jonathan Weill, Noam Koenigstein
2024	—	`conf`	Improving LLM Attributions with Randomized Path-Integration. EMNLP (Findings) Oren Barkan, Yehonatan Elisha, Yonatan Toib, Jonathan Weill, Noam Koenigstein
2024	—	`conf`	LLM Explainability via Attributive Masking Learning. EMNLP (Findings) Oren Barkan, Yonatan Toib, Yehonatan Elisha, Jonathan Weill, Noam Koenigstein
2024	A	`conf`	Probabilistic Path Integration with Mixture of Baseline Distributions. CIKM Yehonatan Elisha, Oren Barkan, Noam Koenigstein
2023	A	`conf`	Deep Integrated Explanations. CIKM Oren Barkan, Yehonatan Elisha, Jonathan Weill, Yuval Asher, Amit Eshel, Noam Koenigstein
2023	J	`jnl`	Deep Integrated Explanations. CoRR Oren Barkan, Yehonatan Elisha, Jonathan Weill, Yuval Asher, Amit Eshel, Noam Koenigstein
2023	A*	`conf`	Learning to Explain: A Model-Agnostic Framework for Explaining Black Box Models. ICDM Oren Barkan, Yuval Asher, Amit Eshel, Yehonatan Elisha, Noam Koenigstein
2023	J	`jnl`	Learning to Explain: A Model-Agnostic Framework for Explaining Black Box Models. CoRR Oren Barkan, Yuval Asher, Amit Eshel, Yehonatan Elisha, Noam Koenigstein
2023	A*	`conf`	Stochastic Integrated Explanations for Vision Models. ICDM Oren Barkan, Yehonatan Elisha, Jonathan Weill, Yuval Asher, Amit Eshel, Noam Koenigstein
2023	A*	`conf`	Visual Explanations via Iterated Integrated Attributions. ICCV Oren Barkan, Yehonatan Elisha, Yuval Asher, Amit Eshel, Noam Koenigstein
2023	J	`jnl`	Visual Explanations via Iterated Integrated Attributions. CoRR Oren Barkan, Yehonatan Elisha, Yuval Asher, Amit Eshel, Noam Koenigstein