Data Intensive Enterprise Applications. - Peter Izsak; Aidan Shribman (Data Intensive Storage Services for Cloud Environments, 2013)

Leveraging memory mirroring for transparent memory scale-out with zero-downtime failover of remote hosts. - Roei Tell; Peter Izsak; Aidan Shribman; Steve Walsh; Benoit Hudzia (ISCC, 2013)

The search duel: a response to a strong ranker. - Peter Izsak; Fiana Raiber; Oren Kurland; Moshe Tennenholtz (SIGIR, 2014)

SetExpander: End-to-end Term Set Expansion Based on Multi-Context Term Embeddings. - Jonathan Mamou; Oren Pereg; Moshe Wasserblat; Ido Dagan; Yoav Goldberg; Alon Eirew; Yael Green; Shira Guskin; Peter Izsak; Daniel Korat (COLING (Demos), 2018)

Term Set Expansion based NLP Architect by Intel AI Lab. - Jonathan Mamou; Oren Pereg; Moshe Wasserblat; Alon Eirew; Yael Green; Shira Guskin; Peter Izsak; Daniel Korat (EMNLP (Demonstration), 2018)

Term Set Expansion based on Multi-Context Term Embeddings: an End-to-end Workflow. - Jonathan Mamou; Oren Pereg; Moshe Wasserblat; Ido Dagan; Yoav Goldberg; Alon Eirew; Yael Green; Shira Guskin; Peter Izsak; Daniel Korat (CoRR, 2018)

Training Compact Models for Low Resource Entity Tagging using Pre-trained Language Models. - Peter Izsak; Shira Guskin; Moshe Wasserblat (EMC2@NeurIPS, 2019)

Q8BERT: Quantized 8Bit BERT. - Ofir Zafrir; Guy Boudoukh; Peter Izsak; Moshe Wasserblat (EMC2@NeurIPS, 2019)

Exploring the Boundaries of Low-Resource BERT Distillation. - Moshe Wasserblat; Oren Pereg; Peter Izsak (SustaiNLP@EMNLP, 2020)

How to Train BERT with an Academic Budget. - Peter Izsak; Moshe Berchansky; Omer Levy (EMNLP (1), 2021)

Transformer Language Models without Positional Encodings Still Learn Positional Information. - Adi Haviv; Ori Ram; Ofir Press; Peter Izsak; Omer Levy (EMNLP (Findings), 2022)

Optimizing Retrieval-augmented Reader Models via Token Elimination. - Moshe Berchansky; Peter Izsak; Avi Caciularu; Ido Dagan; Moshe Wasserblat (EMNLP, 2023)

CoTAR: Chain-of-Thought Attribution Reasoning with Multi-level Granularity. - Moshe Berchansky; Daniel Fleischer; Moshe Wasserblat; Peter Izsak (EMNLP (Findings), 2024)

RAG Foundry: A Framework for Enhancing LLMs for Retrieval Augmented Generation. - Daniel Fleischer; Moshe Berchansky; Moshe Wasserblat; Peter Izsak (CoRR, 2024)

HELMET: How to Evaluate Long-Context Language Models Effectively and Thoroughly. - Howard Yen; Tianyu Gao 001; Minmin Hou; Ke Ding; Daniel Fleischer; Peter Izsak; Moshe Wasserblat; Danqi Chen 001 (CoRR, 2024)

HELMET: How to Evaluate Long-context Models Effectively and Thoroughly. - Howard Yen; Tianyu Gao 001; Minmin Hou; Ke Ding; Daniel Fleischer; Peter Izsak; Moshe Wasserblat; Danqi Chen 001 (ICLR, 2025)