Yftah Ziser

According to our database1, Yftah Ziser authored at least 23 papers between 2017 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Spectral Editing of Activations for Large Language Model Alignment.
CoRR, 2024

Are Large Language Model Temporally Grounded?
Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024

Layer by Layer: Uncovering Where Multi-Task Learning Happens in Instruction-Tuned Large Language Models.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

2023
Rant or rave: variation over time in the language of online reviews.
Lang. Resour. Evaluation, September, 2023

Erasure of Unaligned Attributes from Neural Representations.
Trans. Assoc. Comput. Linguistics, 2023

Are Large Language Models Temporally Grounded?
CoRR, 2023

Detecting and Mitigating Hallucinations in Multilingual Summarisation.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

A Joint Matrix Factorization Analysis of Multilingual Representations.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

Gold Doesn't Always Glitter: Spectral Removal of Linear and Nonlinear Guarded Attribute Information.
Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics, 2023

BERT Is Not The Count: Learning to Match Mathematical Statements with Proofs.
Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics, 2023

2022
Domain Adaptation from Scratch.
CoRR, 2022

Factorizing Content and Budget Decisions in Abstractive Summarization of Long Documents by Sampling Summary Views.
CoRR, 2022

Factorizing Content and Budget Decisions in Abstractive Summarization of Long Documents.
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

Understanding Domain Learning in Language Models Through Subpopulation Analysis.
Proceedings of the Fifth BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP, 2022

2021
DILBERT: Customized Pre-Training for Domain Adaptation withCategory Shift, with an Application to Aspect Extraction.
CoRR, 2021

Answering Product-Questions by Utilizing Questions from Other Contextually Similar Products.
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

DILBERT: Customized Pre-Training for Domain Adaptation with Category Shift, with an Application to Aspect Extraction.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

WikiSum: Coherent Summarization Dataset for Efficient Human-Evaluation.
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

2020
Humor Detection in Product Question Answering Systems.
Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, 2020

2019
Task Refinement Learning for Improved Accuracy and Stability of Unsupervised Domain Adaptation.
Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

2018
Pivot Based Language Modeling for Improved Neural Domain Adaptation.
Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2018

Deep Pivot-Based Modeling for Cross-language Cross-domain Transfer with Minimal Guidance.
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018

2017
Neural Structural Correspondence Learning for Domain Adaptation.
Proceedings of the 21st Conference on Computational Natural Language Learning (CoNLL 2017), 2017


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