Increasing the Power of the Dealer in Non-interactive Zero-Knowledge Proof Systems. - Danny Gutfreund; Michael Ben-Or (ASIACRYPT, 2000)

Uniform hardness vs. randomness tradeoffs for Arthur-Merlin games. - Dan Gutfreund; Ronen Shaltiel; Amnon Ta-Shma (CCC, 2003)

Uniform hardness versus randomness tradeoffs for Arthur-Merlin games. - Dan Gutfreund; Ronen Shaltiel; Amnon Ta-Shma (Comput. Complex., 2003)

Trading Help for Interaction in Statistical Zero-Knowledge Proofs. - Michael Ben-Or; Danny Gutfreund (J. Cryptol., 2003)

Fooling Parity Tests with Parity Gates - Emanuele Viola; Dan Gutfreund (Electron. Colloquium Comput. Complex., 2004)

A lower bound for testing juntas. - Hana Chockler; Dan Gutfreund (Inf. Process. Lett., 2004)

Derandomization, hard functions, and average-case complexity (דה-רנדומיזציה, פונקציות קשות וסיבוכיות ממוצעת.). - Dan Gutfreund (2005)

Worst-Case Vs. Algorithmic Average-Case Complexity in the Polynomial-Time Hierarchy. - Dan Gutfreund (APPROX-RANDOM, 2006)

New connections between derandomization, worst-case complexity and average-case complexity. - Dan Gutfreund; Amnon Ta-Shma (Electron. Colloquium Comput. Complex., 2006)

Worst-Case to Average-Case Reductions Revisited. - Dan Gutfreund; Amnon Ta-Shma (APPROX-RANDOM, 2007)

Verifying and decoding in constant depth. - Shafi Goldwasser; Dan Gutfreund; Alexander Healy; Tali Kaufman; Guy N. Rothblum (STOC, 2007)

If NP Languages are Hard on the Worst-Case, Then it is Easy to Find Their Hard Instances. - Dan Gutfreund; Ronen Shaltiel; Amnon Ta-Shma (Comput. Complex., 2007)

A (De)constructive Approach to Program Checking. - Shafi Goldwasser; Dan Gutfreund; Alexander Healy; Tali Kaufman; Guy N. Rothblum (Electron. Colloquium Comput. Complex., 2007)

The Complexity of Local List Decoding. - Dan Gutfreund; Guy N. Rothblum (Electron. Colloquium Comput. Complex., 2008)

Limitations of Hardness vs. Randomness under Uniform Reductions. - Dan Gutfreund; Salil P. Vadhan (Electron. Colloquium Comput. Complex., 2008)

Derandomizing Arthur-Merlin Games and Approximate Counting Implies Exponential-Size Lower Bounds. - Dan Gutfreund; Akinori Kawachi (Electron. Colloquium Comput. Complex., 2009)

On Approximating the Entropy of Polynomial Mappings. - Zeev Dvir; Dan Gutfreund; Guy N. Rothblum; Salil P. Vadhan (Electron. Colloquium Comput. Complex., 2010)

Derandomizing Arthur-Merlin Games and Approximate Counting Implies Exponential-Size Lower Bounds. - Baris Aydinlioglu; Dan Gutfreund; John M. Hitchcock; Akinori Kawachi (Comput. Complex., 2011)

Succinct Permanent is NEXP-hard with Many Hard Instances. - Shlomi Dolev; Nova Fandina; Dan Gutfreund (Electron. Colloquium Comput. Complex., 2012)

Succinct Permanent Is NEXP-Hard with Many Hard Instances. - Shlomi Dolev; Nova Fandina; Dan Gutfreund (CIAC, 2013)

Exploiting label dependencies for improved sample complexity. - Lena Chekina; Dan Gutfreund; Aryeh Kontorovich; Lior Rokach; Bracha Shapira (Mach. Learn., 2013)

A Benchmark Dataset for Automatic Detection of Claims and Evidence in the Context of Controversial Topics. - Ehud Aharoni; Anatoly Polnarov; Tamar Lavee; Daniel Hershcovich; Ran Levy 001; Ruty Rinott; Dan Gutfreund; Noam Slonim (ArgMining@ACL, 2014)

Claims on demand - an initial demonstration of a system for automatic detection and polarity identification of context dependent claims in massive corpora. - Noam Slonim; Ehud Aharoni; Carlos Alzate; Roy Bar-Haim; Yonatan Bilu; Lena Dankin; Iris Eiron; Daniel Hershcovich; Shay Hummel; Mitesh M. Khapra; Tamar Lavee; Ran Levy 001; et al. (COLING (Demos), 2014)

Automatic Arguments Construction - From Search Engine to Research Engine. - Dan Gutfreund; Yoav Katz; Noam Slonim (AAAI Fall Symposia, 2016)

Boosting conditional probability estimators. - Dan Gutfreund; Aryeh Kontorovich; Ran Levy 001; Michal Rosen-Zvi (Ann. Math. Artif. Intell., 2017)

Semantically Guided Visual Question Answering. - Handong Zhao; Quanfu Fan; Dan Gutfreund; Yun Fu 001 (WACV, 2018)

Grounding Spoken Words in Unlabeled Video. - Angie W. Boggust; Kartik Audhkhasi; Dhiraj Joshi; David Harwath; Samuel Thomas 001; Rogério Schmidt Feris; Danny Gutfreund; Yang Zhang 001; Antonio Torralba 001; Michael Picheny; James R. Glass (CVPR Workshops, 2019)

Identifying Interpretable Action Concepts in Deep Networks. - Kandan Ramakrishnan; Mathew Monfort; Barry A. McNamara; Alex Lascelles; Dan Gutfreund; Rogério Schmidt Feris; Aude Oliva (CVPR Workshops, 2019)

Reasoning About Human-Object Interactions Through Dual Attention Networks. - Tete Xiao; Quanfu Fan; Danny Gutfreund; Mathew Monfort; Aude Oliva; Bolei Zhou (ICCV, 2019)

ObjectNet: A large-scale bias-controlled dataset for pushing the limits of object recognition models. - Andrei Barbu; David Mayo; Julian Alverio; William Luo; Christopher Wang; Dan Gutfreund; Josh Tenenbaum 001; Boris Katz (NeurIPS, 2019)

SimVAE: Simulator-Assisted Training forInterpretable Generative Models. - Akash Srivastava; Jessie C. Rosenberg; Dan Gutfreund; David D. Cox (CoRR, 2019)

ThreeDWorld: A Platform for Interactive Multi-Modal Physical Simulation. - Chuang Gan 001; Jeremy Schwartz; Seth Alter; Martin Schrimpf; James Traer; Julian De Freitas; Jonas Kubilius; Abhishek Bhandwaldar; Nick Haber; Megumi Sano; Kuno Kim; Elias Wang; et al. (CoRR, 2020)

Improving the Reconstruction of Disentangled Representation Learners via Multi-Stage Modelling. - Akash Srivastava; Yamini Bansal; Yukun Ding; Cole L. Hurwitz; Kai Xu 016; Bernhard Egger 001; Prasanna Sattigeri; Josh Tenenbaum 001; David D. Cox; Dan Gutfreund (CoRR, 2020)

Template Controllable keywords-to-text Generation. - Abhijit Mishra; Md. Faisal Mahbub Chowdhury; Sagar Manohar; Dan Gutfreund; Karthik Sankaranarayanan (CoRR, 2020)

Moments in Time Dataset: One Million Videos for Event Understanding. - Mathew Monfort; Carl Vondrick; Aude Oliva; Alex Andonian; Bolei Zhou; Kandan Ramakrishnan; Sarah Adel Bargal; Tom Yan; Lisa M. Brown; Quanfu Fan; Dan Gutfreund (IEEE Trans. Pattern Anal. Mach. Intell., 2020)

AGENT: A Benchmark for Core Psychological Reasoning. - Tianmin Shu; Abhishek Bhandwaldar; Chuang Gan 001; Kevin A. Smith 001; Shari Liu; Dan Gutfreund; Elizabeth S. Spelke; Joshua B. Tenenbaum; Tomer D. Ullman (ICML, 2021)

ThreeDWorld: A Platform for Interactive Multi-Modal Physical Simulation. - Chuang Gan 001; Jeremy Schwartz; Seth Alter; Damian Mrowca; Martin Schrimpf; James Traer; Julian De Freitas; Jonas Kubilius; Abhishek Bhandwaldar; Nick Haber; Megumi Sano; Kuno Kim; et al. (NeurIPS Datasets and Benchmarks, 2021)

3DP3: 3D Scene Perception via Probabilistic Programming. - Nishad Gothoskar; Marco F. Cusumano-Towner; Ben Zinberg; Matin Ghavamizadeh; Falk Pollok; Austin Garrett; Josh Tenenbaum 001; Dan Gutfreund; Vikash K. Mansinghka (NeurIPS, 2021)

A Bayesian-Symbolic Approach to Reasoning and Learning in Intuitive Physics. - Kai Xu 016; Akash Srivastava; Dan Gutfreund; Felix Sosa; Tomer D. Ullman; Josh Tenenbaum 001; Charles Sutton (NeurIPS, 2021)

The ThreeDWorld Transport Challenge: A Visually Guided Task-and-Motion Planning Benchmark for Physically Realistic Embodied AI. - Chuang Gan 001; Siyuan Zhou; Jeremy Schwartz; Seth Alter; Abhishek Bhandwaldar; Dan Gutfreund; Daniel L. K. Yamins; James J. DiCarlo; Josh H. McDermott; Antonio Torralba 001; Joshua B. Tenenbaum (CoRR, 2021)

An autonomous debating system. - Noam Slonim; Yonatan Bilu; Carlos Alzate; Roy Bar-Haim; Ben Bogin; Francesca Bonin; Leshem Choshen; Edo Cohen-Karlik; Lena Dankin; Lilach Edelstein; Liat Ein-Dor; Roni Friedman-Melamed; et al. (Nat., 2021)

Finding Fallen Objects Via Asynchronous Audio-Visual Integration. - Chuang Gan 001; Yi Gu 002; Siyuan Zhou; Jeremy Schwartz; Seth Alter; James Traer; Dan Gutfreund; Joshua B. Tenenbaum; Josh H. McDermott; Antonio Torralba 001 (CVPR, 2022)

The ThreeDWorld Transport Challenge: A Visually Guided Task-and-Motion Planning Benchmark Towards Physically Realistic Embodied AI. - Chuang Gan 001; Siyuan Zhou; Jeremy Schwartz; Seth Alter; Abhishek Bhandwaldar; Dan Gutfreund; Daniel L. K. Yamins; James J. DiCarlo; Josh H. McDermott; Antonio Torralba 001; Joshua B. Tenenbaum (ICRA, 2022)

Incorporating Rich Social Interactions Into MDPs. - Ravi Tejwani; Yen-Ling Kuo; Tianmin Shu; Bennett Stankovits; Dan Gutfreund; Joshua B. Tenenbaum; Boris Katz; Andrei Barbu (ICRA, 2022)

Solving the Baby Intuitions Benchmark with a Hierarchically Bayesian Theory of Mind. - Tan Zhi-Xuan; Nishad Gothoskar; Falk Pollok; Dan Gutfreund; Joshua B. Tenenbaum; Vikash K. Mansinghka (CoRR, 2022)

LINKS: A dataset of a hundred million planar linkage mechanisms for data-driven kinematic design. - Amin Heyrani Nobari; Akash Srivastava; Dan Gutfreund; Faez Ahmed (CoRR, 2022)

Multi-Moments in Time: Learning and Interpreting Models for Multi-Action Video Understanding. - Mathew Monfort; Bowen Pan; Kandan Ramakrishnan; Alex Andonian; Barry A. McNamara; Alex Lascelles; Quanfu Fan; Dan Gutfreund; Rogério Schmidt Feris; Aude Oliva (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

Zero-Shot Linear Combinations of Grounded Social Interactions with Linear Social MDPs. - Ravi Tejwani; Yen-Ling Kuo; Tianmin Shu; Bennett Stankovits; Dan Gutfreund; Joshua B. Tenenbaum; Boris Katz; Andrei Barbu (AAAI, 2023)

3D Neural Embedding Likelihood: Probabilistic Inverse Graphics for Robust 6D Pose Estimation. - Guangyao Zhou; Nishad Gothoskar; Lirui Wang; Joshua B. Tenenbaum; Dan Gutfreund; Miguel Lázaro-Gredilla; Dileep George; Vikash K. Mansinghka (ICCV, 2023)

How hard are computer vision datasets? Calibrating dataset difficulty to viewing time. - David Mayo; Jesse Cummings; Xinyu Lin; Dan Gutfreund; Boris Katz; Andrei Barbu (NeurIPS, 2023)

3D Neural Embedding Likelihood for Robust Sim-to-Real Transfer in Inverse Graphics. - Guangyao Zhou; Nishad Gothoskar; Lirui Wang; Joshua B. Tenenbaum; Dan Gutfreund; Miguel Lázaro-Gredilla; Dileep George; Vikash K. Mansinghka (CoRR, 2023)

Learning from Invalid Data: On Constraint Satisfaction in Generative Models. - Giorgio Giannone; Lyle Regenwetter; Akash Srivastava; Dan Gutfreund; Faez Ahmed (CoRR, 2023)

Beyond Statistical Similarity: Rethinking Metrics for Deep Generative Models in Engineering Design. - Lyle Regenwetter; Akash Srivastava; Dan Gutfreund; Faez Ahmed (Comput. Aided Des., 2023)

Visual Chain-of-Thought Prompting for Knowledge-Based Visual Reasoning. - Zhenfang Chen; Qinhong Zhou; Yikang Shen; Yining Hong; Zhiqing Sun; Dan Gutfreund; Chuang Gan 001 (AAAI, 2024)

A Graph per Persona: Reasoning about Subjective Natural Language Descriptions. - Eunjeong Hwang; Vered Shwartz; Dan Gutfreund; Veronika Thost (ACL (Findings), 2024)

LInK: Learning Joint Representations of Design and Performance Spaces through Contrastive Learning for Mechanism Synthesis. - Amin Heyrani Nobari; Akash Srivastava; Dan Gutfreund; Kai Xu 016; Faez Ahmed (Trans. Mach. Learn. Res., 2024)

Constraining Generative Models for Engineering Design with Negative Data. - Lyle Regenwetter; Giorgio Giannone; Akash Srivastava; Dan Gutfreund; Faez Ahmed (Trans. Mach. Learn. Res., 2024)

M+: Extending MemoryLLM with Scalable Long-Term Memory. - Yu Wang 170; Dmitry Krotov; Yuanzhe Hu; Yifan Gao 001; Wangchunshu Zhou; Julian J. McAuley; Dan Gutfreund; Rogério Feris; Zexue He (CoRR, 2025)

Granite Vision: a lightweight, open-source multimodal model for enterprise Intelligence. - Leonid Karlinsky; Assaf Arbelle; Abraham Daniels; Ahmed Nassar; Amit Alfassi; Bo Wu 018; Eli Schwartz; Dhiraj Joshi; Jovana Kondic; Nimrod Shabtay; Pengyuan Li 001; Roei Herzig; et al. (CoRR, 2025)

Satori-SWE: Evolutionary Test-Time Scaling for Sample-Efficient Software Engineering. - Guangtao Zeng; Maohao Shen; Delin Chen; Zhenting Qi; Subhro Das; Dan Gutfreund; David Cox; Gregory W. Wornell; Wei Lu; Zhang-Wei Hong; Chuang Gan 001 (CoRR, 2025)

ChartGen: Scaling Chart Understanding Via Code-Guided Synthetic Chart Generation. - Jovana Kondic; Pengyuan Li 001; Dhiraj Joshi; Zexue He; Shafiq Abedin; Jennifer Sun; Ben Wiesel; Eli Schwartz; Ahmed Nassar; Bo Wu 018; Assaf Arbelle; Aude Oliva; et al. (CoRR, 2025)