Dan Iter - RankMe

35 papers A* 5A 2Journal 15Unranked 12

Year	Rank	Type	Title / Venue / Authors
2024	—	`conf`	How Does In-Context Learning Help Prompt Tuning? EACL (Findings) Simeng Sun, Yang Liu, Dan Iter, Chenguang Zhu, Mohit Iyyer
2024	—	`conf`	PEARL: Prompting Large Language Models to Plan and Execute Actions Over Long Documents. EACL (1) Simeng Sun, Yang Liu, Shuohang Wang, Dan Iter, Chenguang Zhu, Mohit Iyyer
2023	—	`conf`	Auto-Instruct: Automatic Instruction Generation and Ranking for Black-Box Language Models. EMNLP (Findings) Zhihan Zhang, Shuohang Wang, Wenhao Yu, Yichong Xu, Dan Iter, Qingkai Zeng, Yang Liu, Chenguang Zhu, Meng Jiang
2023	J	`jnl`	Auto-Instruct: Automatic Instruction Generation and Ranking for Black-Box Language Models. CoRR Zhihan Zhang, Shuohang Wang, Wenhao Yu, Yichong Xu, Dan Iter, Qingkai Zeng, Yang Liu, Chenguang Zhu, Meng Jiang
2023	A*	`conf`	Automatic Prompt Optimization with "Gradient Descent" and Beam Search. EMNLP Reid Pryzant, Dan Iter, Jerry Li, Yin Tat Lee, Chenguang Zhu, Michael Zeng
2023	J	`jnl`	Automatic Prompt Optimization with "Gradient Descent" and Beam Search. CoRR Reid Pryzant, Dan Iter, Jerry Li, Yin Tat Lee, Chenguang Zhu, Michael Zeng
2023	J	`jnl`	G-Eval: NLG Evaluation using GPT-4 with Better Human Alignment. CoRR Yang Liu, Dan Iter, Yichong Xu, Shuohang Wang, Ruochen Xu, Chenguang Zhu
2023	A*	`conf`	G-Eval: NLG Evaluation using Gpt-4 with Better Human Alignment. EMNLP Yang Liu, Dan Iter, Yichong Xu, Shuohang Wang, Ruochen Xu, Chenguang Zhu
2023	A*	`conf`	Generate rather than Retrieve: Large Language Models are Strong Context Generators. ICLR Wenhao Yu, Dan Iter, Shuohang Wang, Yichong Xu, Mingxuan Ju, Soumya Sanyal, Chenguang Zhu, Michael Zeng, Meng Jiang
2023	J	`jnl`	How Does In-Context Learning Help Prompt Tuning? CoRR Simeng Sun, Yang Liu, Dan Iter, Chenguang Zhu, Mohit Iyyer
2023	—	`conf`	In-Context Demonstration Selection with Cross Entropy Difference. EMNLP (Findings) Dan Iter, Reid Pryzant, Ruochen Xu, Shuohang Wang, Yang Liu, Yichong Xu, Chenguang Zhu
2023	J	`jnl`	In-Context Demonstration Selection with Cross Entropy Difference. CoRR Dan Iter, Reid Pryzant, Ruochen Xu, Shuohang Wang, Yang Liu, Yichong Xu, Chenguang Zhu
2023	—	`conf`	InheritSumm: A General, Versatile and Compact Summarizer by Distilling from GPT. EMNLP (Findings) Yichong Xu, Ruochen Xu, Dan Iter, Yang Liu, Shuohang Wang, Chenguang Zhu, Michael Zeng
2023	J	`jnl`	InheritSumm: A General, Versatile and Compact Summarizer by Distilling from GPT. CoRR Yichong Xu, Ruochen Xu, Dan Iter, Yang Liu, Shuohang Wang, Chenguang Zhu, Michael Zeng
2023	—	`conf`	LMGQS: A Large-scale Dataset for Query-focused Summarization. EMNLP (Findings) Ruochen Xu, Song Wang, Yang Liu, Shuohang Wang, Yichong Xu, Dan Iter, Pengcheng He, Chenguang Zhu, Michael Zeng
2023	J	`jnl`	LMGQS: A Large-scale Dataset for Query-focused Summarization. CoRR Ruochen Xu, Song Wang, Yang Liu, Shuohang Wang, Yichong Xu, Dan Iter, Chenguang Zhu, Michael Zeng
2023	A*	`conf`	The Shifted and The Overlooked: A Task-oriented Investigation of User-GPT Interactions. EMNLP Siru Ouyang, Shuohang Wang, Yang Liu, Ming Zhong, Yizhu Jiao, Dan Iter, Reid Pryzant, Chenguang Zhu, Heng Ji, Jiawei Han
2023	J	`jnl`	The Shifted and The Overlooked: A Task-oriented Investigation of User-GPT Interactions. CoRR Siru Ouyang, Shuohang Wang, Yang Liu, Ming Zhong, Yizhu Jiao, Dan Iter, Reid Pryzant, Chenguang Zhu, Heng Ji, Jiawei Han
2022	J	`jnl`	Generate rather than Retrieve: Large Language Models are Strong Context Generators. CoRR Wenhao Yu, Dan Iter, Shuohang Wang, Yichong Xu, Mingxuan Ju, Soumya Sanyal, Chenguang Zhu, Michael Zeng, Meng Jiang
2022	—	`—`	Pre-finetuning methods for domain and task adaptation, with applications to discourse and translation. Dan Iter
2022	—	`conf`	The Trade-offs of Domain Adaptation for Neural Language Models. ACL (1) David Grangier, Dan Iter
2021	—	`conf`	Focus on what matters: Applying Discourse Coherence Theory to Cross Document Coreference. EMNLP (1) William Barr Held, Dan Iter, Dan Jurafsky
2021	J	`jnl`	Focus on what matters: Applying Discourse Coherence Theory to Cross Document Coreference. CoRR William Barr Held, Dan Iter, Dan Jurafsky
2021	J	`jnl`	On the Complementarity of Data Selection and Fine Tuning for Domain Adaptation. CoRR Dan Iter, David Grangier
2021	J	`jnl`	The Trade-offs of Domain Adaptation for Neural Language Models. CoRR Dan Iter, David Grangier
2020	A*	`conf`	Pretraining with Contrastive Sentence Objectives Improves Discourse Performance of Language Models. ACL Dan Iter, Kelvin Guu, Larry Lansing, Dan Jurafsky
2020	J	`jnl`	Pretraining with Contrastive Sentence Objectives Improves Discourse Performance of Language Models. CoRR Dan Iter, Kelvin Guu, Larry Lansing, Dan Jurafsky
2019	—	`conf`	From Laptop to Lambda: Outsourcing Everyday Jobs to Thousands of Transient Functional Containers. USENIX ATC Sadjad Fouladi, Francisco Romero, Dan Iter, Qian Li, Shuvo Chatterjee, Christos Kozyrakis, Matei Zaharia, Keith Winstein
2019	J	`jnl`	Outsourcing Everyday Jobs to Thousands of Cloud Functions with gg. login Usenix Mag. Sadjad Fouladi, Francisco Romero, Dan Iter, Qian Li, Alex Ozdemir, Shuvo Chatterjee, Matei Zaharia, Christos Kozyrakis, Keith Winstein
2018	—	`conf`	Automatic Detection of Incoherent Speech for Diagnosing Schizophrenia. CLPsych@NAACL-HTL Dan Iter, Jong Yoon, Dan Jurafsky
2018	—	`conf`	FrameIt: Ontology Discovery for Noisy User-Generated Text. NUT@EMNLP Dan Iter, Alon Y. Halevy, Wang-Chiew Tan
2017	—	`conf`	Flipper: A Systematic Approach to Debugging Training Sets. HILDA@SIGMOD Paroma Varma, Dan Iter, Christopher De Sa, Christopher Ré
2016	J	`jnl`	Socratic Learning. CoRR Rose Yu, Paroma Varma, Dan Iter, Christopher De Sa, Christopher Ré
2012	A	`conf`	Identifying content for planned events across social media sites. WSDM Hila Becker, Dan Iter, Mor Naaman, Luis Gravano
2011	A	`conf`	Automatic Identification and Presentation of Twitter Content for Planned Events. ICWSM Hila Becker, Feiyang Chen, Dan Iter, Mor Naaman, Luis Gravano

Nicolò Altamura is a security engineer and computer science researcher specializing in software protection, reverse engineering, program analysis, and binary deobfuscation. He holds a master's degree in Computer Science and Engineering from the University of Verona, graduating with honors, and works at emproof, focusing on software protection and the challenges of analyzing and understanding compiled software.

His research explores the relationship between program analysis and code obfuscation, with particular emphasis on how software transformations affect the ability of automated tools to recover program behavior. His interests span static analysis, binary analysis, decompilation, reverse engineering, and techniques for analyzing and simplifying obfuscated code.

Beyond academic research, Nicolò develops and contributes to tools for reverse engineering and software analysis. His projects include obfuscation_analysis, a Binary Ninja plugin for analyzing and simplifying obfuscated code; Pocket, an obfuscator for mixed Boolean-arithmetic expressions; and ptxNinja, a tool for reverse engineering NVIDIA GPU code represented in the PTX virtual instruction set.

His research also extends to binary datasets and software evolution. In 2026, he co-authored ASSEMBLAGE-DEEPHISTORY: A Cross-Build Binary Dataset with Temporal Coverage, a research work addressing the availability of binary data across multiple software builds and points in time, supporting research into binary analysis and changes between program versions.

Across his research, engineering work, and open-source contributions, Nicolò focuses on advancing the understanding, analysis, and protection of software against increasingly sophisticated obfuscation and reverse-engineering challenges.

Nicolò Altamura is not a football player. Please avoid reporting this kind of infromation.