What makes an image memorable? - Phillip Isola; Jianxiong Xiao; Antonio Torralba 001; Aude Oliva (CVPR, 2011)

Understanding the Intrinsic Memorability of Images. - Phillip Isola; Devi Parikh; Antonio Torralba 001; Aude Oliva (NIPS, 2011)

Establishing a Database for Studying Human Face Photograph Memory. - Wilma A. Bainbridge; Phillip Isola; Idan Blank; Aude Oliva (CogSci, 2012)

Shapecollage: Occlusion-Aware, Example-Based Shape Interpretation. - Forrester Cole; Phillip Isola; William T. Freeman; Frédo Durand; Edward H. Adelson (ECCV (3), 2012)

Image memorability and visual inception. - Aditya Khosla; Jianxiong Xiao; Phillip Isola; Antonio Torralba 001; Aude Oliva (SIGGRAPH Asia Technical Briefs, 2012)

Scene Collaging: Analysis and Synthesis of Natural Images with Semantic Layers. - Phillip Isola; Ce Liu (ICCV, 2013)

What Makes a Visualization Memorable? - Michelle Borkin; Azalea A. Vo; Zoya Bylinskii; Phillip Isola; Shashank Sunkavalli; Aude Oliva; Hanspeter Pfister (IEEE Trans. Vis. Comput. Graph., 2013)

Crisp Boundary Detection Using Pointwise Mutual Information. - Phillip Isola; Daniel Zoran; Dilip Krishnan; Edward H. Adelson (ECCV (3), 2014)

Sparkle Vision: Seeing the World through Random Specular Microfacets. - Zhengdong Zhang; Phillip Isola; Edward H. Adelson (CoRR, 2014)

What Makes a Photograph Memorable? - Phillip Isola; Jianxiong Xiao; Devi Parikh; Antonio Torralba 001; Aude Oliva (IEEE Trans. Pattern Anal. Mach. Intell., 2014)

Discovering states and transformations in image collections. - Phillip Isola; Joseph J. Lim; Edward H. Adelson (CVPR, 2015)

SparkleVision: Seeing the world through random specular microfacets. - Zhengdong Zhang 001; Phillip Isola; Edward H. Adelson (CVPR Workshops, 2015)

Learning Ordinal Relationships for Mid-Level Vision. - Daniel Zoran; Phillip Isola; Dilip Krishnan; William T. Freeman (ICCV, 2015)

Learning visual groups from co-occurrences in space and time. - Phillip Isola; Daniel Zoran; Dilip Krishnan; Edward H. Adelson (CoRR, 2015)

Visually Indicated Sounds. - Andrew Owens; Phillip Isola; Josh H. McDermott; Antonio Torralba 001; Edward H. Adelson; William T. Freeman (CVPR, 2016)

Colorful Image Colorization. - Richard Zhang 001; Phillip Isola; Alexei A. Efros (ECCV (3), 2016)

Mining Visual Evolution in 21 Years of Web Design. - Ali Jahanian 002; Phillip Isola; Donglai Wei 001 (CHI Extended Abstracts, 2017)

Image-to-Image Translation with Conditional Adversarial Networks. - Phillip Isola; Jun-Yan Zhu; Tinghui Zhou; Alexei A. Efros (CVPR, 2017)

Split-Brain Autoencoders: Unsupervised Learning by Cross-Channel Prediction. - Richard Zhang 001; Phillip Isola; Alexei A. Efros (CVPR, 2017)

Unpaired Image-to-Image Translation Using Cycle-Consistent Adversarial Networks. - Jun-Yan Zhu; Taesung Park; Phillip Isola; Alexei A. Efros (ICCV, 2017)

Combining self-supervised learning and imitation for vision-based rope manipulation. - Ashvin Nair; Dian Chen 001; Pulkit Agrawal 001; Phillip Isola; Pieter Abbeel; Jitendra Malik; Sergey Levine (ICRA, 2017)

What You Sketch Is What You Get: 3D Sketching using Multi-View Deep Volumetric Prediction. - Johanna Delanoy; Adrien Bousseau; Mathieu Aubry; Phillip Isola; Alexei A. Efros (CoRR, 2017)

Real-time user-guided image colorization with learned deep priors. - Richard Zhang 001; Jun-Yan Zhu; Phillip Isola; Xinyang Geng; Angela S. Lin; Tianhe Yu; Alexei A. Efros (ACM Trans. Graph., 2017)

The Unreasonable Effectiveness of Deep Features as a Perceptual Metric. - Richard Zhang 001; Phillip Isola; Alexei A. Efros; Eli Shechtman; Oliver Wang (CVPR, 2018)

CyCADA: Cycle-Consistent Adversarial Domain Adaptation. - Judy Hoffman; Eric Tzeng; Taesung Park; Jun-Yan Zhu; Phillip Isola; Kate Saenko; Alexei A. Efros; Trevor Darrell (ICML, 2018)

Evolved Policy Gradients. - Rein Houthooft; Yuhua Chen; Phillip Isola; Bradly C. Stadie; Filip Wolski; Jonathan Ho; Pieter Abbeel (NeurIPS, 2018)

Evolved Policy Gradients. - Rein Houthooft; Richard Y. Chen; Phillip Isola; Bradly C. Stadie; Filip Wolski; Jonathan Ho; Pieter Abbeel (CoRR, 2018)

Internal Distribution Matching for Natural Image Retargeting. - Assaf Shocher; Shai Bagon; Phillip Isola; Michal Irani (CoRR, 2018)

3D Sketching using Multi-View Deep Volumetric Prediction. - Johanna Delanoy; Mathieu Aubry; Phillip Isola; Alexei A. Efros; Adrien Bousseau (Proc. ACM Comput. Graph. Interact. Tech., 2018)

Experience-Embedded Visual Foresight. - Yen-Chen Lin; Maria Bauzá 001; Phillip Isola (CoRL, 2019)

GANalyze: Toward Visual Definitions of Cognitive Image Properties. - Lore Goetschalckx; Alex Andonian; Aude Oliva; Phillip Isola (ICCV, 2019)

InGAN: Capturing and Retargeting the "DNA" of a Natural Image. - Assaf Shocher; Shai Bagon; Phillip Isola; Michal Irani (ICCV, 2019)

Omnipush: accurate, diverse, real-world dataset of pushing dynamics with RGB-D video. - Maria Bauzá 001; Ferran Alet; Yen-Chen Lin; Tomás Lozano-Pérez; Leslie Pack Kaelbling; Phillip Isola; Alberto Rodriguez 003 (IROS, 2019)

Learning to Control Self-Assembling Morphologies: A Study of Generalization via Modularity. - Deepak Pathak; Christopher Lu 001; Trevor Darrell; Phillip Isola; Alexei A. Efros (NeurIPS, 2019)

Neural MMO: A Massively Multiagent Game Environment for Training and Evaluating Intelligent Agents. - Joseph Suarez; Yilun Du; Phillip Isola; Igor Mordatch (CoRR, 2019)

Lore Goetschalckx, Alex Andonian, Aude Oliva, Phillip Isola: GANalyze: Toward Visual Definitions of Cognitive Image Properties. - Lore Goetschalckx; Alex Andonian; Aude Oliva; Phillip Isola (CoRR, 2019)

Neural MMO v1.3: A Massively Multiagent Game Environment for Training and Evaluating Neural Networks. - Joseph Suarez; Yilun Du; Igor Mordatch; Phillip Isola (AAMAS, 2020)

What Makes Fake Images Detectable? Understanding Properties that Generalize. - Lucy Chai; David Bau; Ser-Nam Lim; Phillip Isola (ECCV (26), 2020)

Contrastive Multiview Coding. - Yonglong Tian; Dilip Krishnan; Phillip Isola (ECCV (11), 2020)

Rethinking Few-Shot Image Classification: A Good Embedding is All You Need? - Yonglong Tian; Yue Wang 041; Dilip Krishnan; Joshua B. Tenenbaum; Phillip Isola (ECCV (14), 2020)

On the "steerability" of generative adversarial networks. - Ali Jahanian 002; Lucy Chai; Phillip Isola (ICLR, 2020)

Contrastive Representation Distillation. - Yonglong Tian; Dilip Krishnan; Phillip Isola (ICLR, 2020)

Understanding Contrastive Representation Learning through Alignment and Uniformity on the Hypersphere. - Tongzhou Wang 001; Phillip Isola (ICML, 2020)

Learning to See before Learning to Act: Visual Pre-training for Manipulation. - Yen-Chen Lin; Andy Zeng 001; Shuran Song; Phillip Isola; Tsung-Yi Lin (ICRA, 2020)

Supervised Contrastive Learning. - Prannay Khosla; Piotr Teterwak; Chen Wang 050; Aaron Sarna; Yonglong Tian; Phillip Isola; Aaron Maschinot; Ce Liu 001; Dilip Krishnan (NeurIPS, 2020)

What Makes for Good Views for Contrastive Learning? - Yonglong Tian; Chen Sun 002; Ben Poole; Dilip Krishnan; Cordelia Schmid; Phillip Isola (NeurIPS, 2020)

iNeRF: Inverting Neural Radiance Fields for Pose Estimation. - Yen-Chen Lin; Pete Florence; Jonathan T. Barron; Alberto Rodriguez Garcia; Phillip Isola; Tsung-Yi Lin (CoRR, 2020)

Ensembling With Deep Generative Views. - Lucy Chai; Jun-Yan Zhu; Eli Shechtman; Phillip Isola; Richard Zhang 001 (CVPR, 2021)

Curious Representation Learning for Embodied Intelligence. - Yilun Du; Chuang Gan 001; Phillip Isola (ICCV, 2021)

Explaining in Style: Training a GAN to explain a classifier in StyleSpace. - Oran Lang; Yossi Gandelsman; Michal Yarom; Yoav Wald; Gal Elidan; Avinatan Hassidim; William T. Freeman; Phillip Isola; Amir Globerson; Michal Irani; Inbar Mosseri (ICCV, 2021)

Contrastive Feature Loss for Image Prediction. - Alex Andonian; Taesung Park; Bryan Russell; Phillip Isola; Jun-Yan Zhu; Richard Zhang 001 (ICCVW, 2021)

Using latent space regression to analyze and leverage compositionality in GANs. - Lucy Chai; Jonas Wulff; Phillip Isola (ICLR, 2021)

OPEn: An Open-ended Physics Environment for Learning Without a Task. - Chuang Gan 001; Abhishek Bhandwaldar; Antonio Torralba 001; Joshua B. Tenenbaum; Phillip Isola (IROS, 2021)

iNeRF: Inverting Neural Radiance Fields for Pose Estimation. - Yen-Chen Lin; Pete Florence; Jonathan T. Barron; Alberto Rodriguez 003; Phillip Isola; Tsung-Yi Lin (IROS, 2021)

Adaptable Agent Populations via a Generative Model of Policies. - Kenneth Derek; Phillip Isola (NeurIPS, 2021)

Learning to See by Looking at Noise. - Manel Baradad Jurjo; Jonas Wulff; Tongzhou Wang 001; Phillip Isola; Antonio Torralba 001 (NeurIPS, 2021)

Learning to Ground Multi-Agent Communication with Autoencoders. - Toru Lin; Jacob Huh; Christopher Stauffer; Ser-Nam Lim; Phillip Isola (NeurIPS, 2021)

The NeurIPS 2022 Neural MMO Challenge: A Massively Multiagent Competition with Specialization and Trade. - Enhong Liu; Joseph Suarez; Chenhui You; Bo Wu; Bingcheng Chen; Jun Hu 014; Jiaxin Chen; Xiaolong Zhu; Clare Zhu; Julian Togelius; Sharada P. Mohanty; Weijun Hong; et al. (NeurIPS (Competition and Demos), 2021)

The Neural MMO Platform for Massively Multiagent Research. - Joseph Suarez; Yilun Du; Clare Zhu; Igor Mordatch; Phillip Isola (NeurIPS Datasets and Benchmarks, 2021)

Learning to Ground Multi-Agent Communication with Autoencoders. - Toru Lin; Minyoung Huh; Christopher Stauffer; Ser-Nam Lim; Phillip Isola (CoRR, 2021)

MIRA: Mental Imagery for Robotic Affordances. - Yen-Chen Lin; Pete Florence; Andy Zeng 001; Jonathan T. Barron; Yilun Du; Wei-Chiu Ma; Anthony Simeonov; Alberto Rodriguez Garcia; Phillip Isola (CoRL, 2022)

Learning to generate line drawings that convey geometry and semantics. - Caroline Chan; Frédo Durand; Phillip Isola (CVPR, 2022)

Any-Resolution Training for High-Resolution Image Synthesis. - Lucy Chai; Michaël Gharbi; Eli Shechtman; Phillip Isola; Richard Zhang 001 (ECCV (16), 2022)

Totems: Physical Objects for Verifying Visual Integrity. - Jingwei Ma; Lucy Chai; Minyoung Huh; Tongzhou Wang 001; Ser-Nam Lim; Phillip Isola; Antonio Torralba 001 (ECCV (14), 2022)

On the Learning and Learnability of Quasimetrics. - Tongzhou Wang 001; Phillip Isola (ICLR, 2022)

Generative Models as a Data Source for Multiview Representation Learning. - Ali Jahanian 002; Xavier Puig; Yonglong Tian; Phillip Isola (ICLR, 2022)

Denoised MDPs: Learning World Models Better Than the World Itself. - Tongzhou Wang 001; Simon S. Du; Antonio Torralba 001; Phillip Isola; Amy Zhang 001; Yuandong Tian (ICML, 2022)

NeRF-Supervision: Learning Dense Object Descriptors from Neural Radiance Fields. - Yen-Chen Lin; Pete Florence; Jonathan T. Barron; Tsung-Yi Lin; Alberto Rodriguez 003; Phillip Isola (ICRA, 2022)

Noisy Agents: Self-supervised Exploration by Predicting Auditory Events. - Chuang Gan 001; Xiaoyu Chen; Phillip Isola; Antonio Torralba 001; Joshua B. Tenenbaum (IROS, 2022)

Procedural Image Programs for Representation Learning. - Manel Baradad; Chun-Fu Richard Chen; Jonas Wulff; Tongzhou Wang 001; Rogério Feris; Antonio Torralba 001; Phillip Isola (NeurIPS, 2022)

Semantic uncertainty intervals for disentangled latent spaces. - Swami Sankaranarayanan; Anastasios Angelopoulos; Stephen Bates; Yaniv Romano; Phillip Isola (NeurIPS, 2022)

Offline Multi-Agent Reinforcement Learning with Knowledge Distillation. - Wei-Cheng Tseng; Tsun-Hsuan Johnson Wang; Yen-Chen Lin; Phillip Isola (NeurIPS, 2022)

NeRF-Supervision: Learning Dense Object Descriptors from Neural Radiance Fields. - Yen-Chen Lin; Pete Florence; Jonathan T. Barron; Tsung-Yi Lin; Alberto Rodriguez Garcia; Phillip Isola (CoRR, 2022)

Visual Prompting: Modifying Pixel Space to Adapt Pre-trained Models. - Hyojin Bahng; Ali Jahanian 002; Swami Sankaranarayanan; Phillip Isola (CoRR, 2022)

MultiEarth 2022 - Multimodal Learning for Earth and Environment Workshop and Challenge. - Miriam Cha; Kuan Wei Huang; Morgan Schmidt; Gregory Angelides; Mark Hamilton; Sam Goldberg; Armando Cabrera; Phillip Isola; Taylor Perron; Bill Freeman; Yen-Chen Lin; Brandon Swenson; et al. (CoRR, 2022)

On the Learning and Learnablity of Quasimetrics. - Tongzhou Wang 001; Phillip Isola (CoRR, 2022)

Developing a Series of AI Challenges for the United States Department of the Air Force. - Vijay Gadepally; Gregory Angelides; Andrei Barbu; Andrew Bowne; Laura J. Brattain; Tamara Broderick; Armando Cabrera; Glenn Carl; Ronisha Carter; Miriam Cha; Emilie Cowen; Jesse Cummings; et al. (CoRR, 2022)

Improved Representation of Asymmetrical Distances with Interval Quasimetric Embeddings. - Tongzhou Wang 001; Phillip Isola (CoRR, 2022)

Benchmarking Robustness and Generalization in Multi-Agent Systems: A Case Study on Neural MMO. - Yangkun Chen; Joseph Suarez; Junjie Zhang; Chenghui Yu; Bo Wu; Hanmo Chen; Hengman Zhu; Rui Du; Shanliang Qian; Shuai Liu; Weijun Hong; Jinke He; et al. (AAMAS, 2023)

Distilled Feature Fields Enable Few-Shot Language-Guided Manipulation. - William Shen; Ge Yang; Alan Yu; Jansen Wong; Leslie Pack Kaelbling; Phillip Isola (CoRL, 2023)

Persistent Nature: A Generative Model of Unbounded 3D Worlds. - Lucy Chai; Richard Tucker 001; Zhengqi Li; Phillip Isola; Noah Snavely (CVPR, 2023)

Powderworld: A Platform for Understanding Generalization via Rich Task Distributions. - Kevin Frans; Phillip Isola (ICLR, 2023)

Is CLIP Fooled by Optical Illusions? - Jerry Ngo; Swami Sankaranarayanan; Phillip Isola (Tiny Papers @ ICLR, 2023)

Optimal Goal-Reaching Reinforcement Learning via Quasimetric Learning. - Tongzhou Wang 001; Antonio Torralba 001; Phillip Isola; Amy Zhang 001 (ICML, 2023)

Straightening Out the Straight-Through Estimator: Overcoming Optimization Challenges in Vector Quantized Networks. - Minyoung Huh; Brian Cheung; Pulkit Agrawal 001; Phillip Isola (ICML, 2023)

Improving CLIP Training with Language Rewrites. - Lijie Fan; Dilip Krishnan; Phillip Isola; Dina Katabi; Yonglong Tian (NeurIPS, 2023)

DreamSim: Learning New Dimensions of Human Visual Similarity using Synthetic Data. - Stephanie Fu; Netanel Tamir; Shobhita Sundaram; Lucy Chai; Richard Zhang 001; Tali Dekel; Phillip Isola (NeurIPS, 2023)

Neural MMO 2.0: A Massively Multi-task Addition to Massively Multi-agent Learning. - Joseph Suarez; David Bloomin; Kyoung Whan Choe; Hao Xiang Li; Ryan Sullivan; Nishaanth Kanna; Daniel Scott; Rose S. Shuman; Herbie Bradley; Louis Castricato; Phillip Isola; Chenghui Yu; et al. (NeurIPS, 2023)

StableRep: Synthetic Images from Text-to-Image Models Make Strong Visual Representation Learners. - Yonglong Tian; Lijie Fan; Phillip Isola; Huiwen Chang; Dilip Krishnan (NeurIPS, 2023)

Steerable Equivariant Representation Learning. - Sangnie Bhardwaj; Willie McClinton; Tongzhou Wang 001; Guillaume Lajoie; Chen Sun 002; Phillip Isola; Dilip Krishnan (CoRR, 2023)

MultiEarth 2023 - Multimodal Learning for Earth and Environment Workshop and Challenge. - Miriam Cha; Gregory Angelides; Mark Hamilton; Andy Soszynski; Brandon Swenson; Nathaniel Maidel; Phillip Isola; Taylor Perron; Bill Freeman (CoRR, 2023)

Neural MMO 2.0: A Massively Multi-task Addition to Massively Multi-agent Learning. - Joseph Suárez; Phillip Isola; Kyoung Whan Choe; David Bloomin; Hao Xiang Li; Nikhil Pinnaparaju; Nishaanth Kanna; Daniel Scott; Ryan Sullivan; Rose S. Shuman; Lucas de Alcântara; Herbie Bradley; et al. (CoRR, 2023)

The Low-Rank Simplicity Bias in Deep Networks. - Minyoung Huh; Hossein Mobahi; Richard Zhang 001; Brian Cheung; Pulkit Agrawal 001; Phillip Isola (Trans. Mach. Learn. Res., 2023)

Learning Visual Parkour from Generated Images. - Alan Yu; Ge Yang; Ran Choi; Yajvan Ravan; John Leonard; Phillip Isola (CoRL, 2024)

Scaling Laws of Synthetic Images for Model Training ... for Now. - Lijie Fan; Kaifeng Chen; Dilip Krishnan; Dina Katabi; Phillip Isola; Yonglong Tian (CVPR, 2024)

A Vision Check-up for Language Models. - Pratyusha Sharma; Tamar Rott Shaham; Manel Baradad; Adrián Rodríuez-Muñoz; Shivam Duggal; Phillip Isola; Antonio Torralba 001; Stephanie Fu (CVPR, 2024)

Learning Vision from Models Rivals Learning Vision from Data. - Yonglong Tian; Lijie Fan; Kaifeng Chen; Dina Katabi; Dilip Krishnan; Phillip Isola (CVPR, 2024)

Position: The Platonic Representation Hypothesis. - Minyoung Huh; Brian Cheung; Tongzhou Wang 001; Phillip Isola (ICML, 2024)

LangNav: Language as a Perceptual Representation for Navigation. - Bowen Pan; Rameswar Panda; SouYoung Jin; Rogério Feris; Aude Oliva; Phillip Isola; Yoon Kim (NAACL-HLT (Findings), 2024)

Scalable Optimization in the Modular Norm. - Tim Large; Yang Liu; Jacob Huh; Hyojin Bahng; Phillip Isola; Jeremy Bernstein (NeurIPS, 2024)

When does perceptual alignment benefit vision representations? - Shobhita Sundaram; Stephanie Fu; Lukas Muttenthaler; Netanel Tamir; Lucy Chai; Simon Kornblith; Trevor Darrell; Phillip Isola (NeurIPS, 2024)

A Vision Check-up for Language Models. - Pratyusha Sharma; Tamar Rott Shaham; Manel Baradad; Stephanie Fu; Adrián Rodríguez-Muñoz; Shivam Duggal; Phillip Isola; Antonio Torralba 001 (CoRR, 2024)

Training Neural Networks from Scratch with Parallel Low-Rank Adapters. - Minyoung Huh; Brian Cheung; Jeremy Bernstein; Phillip Isola; Pulkit Agrawal 001 (CoRR, 2024)

The Platonic Representation Hypothesis. - Minyoung Huh; Brian Cheung; Tongzhou Wang 001; Phillip Isola (CoRR, 2024)

Scalable Optimization in the Modular Norm. - Tim Large; Yang Liu; Minyoung Huh; Hyojin Bahng; Phillip Isola; Jeremy Bernstein (CoRR, 2024)

Automating the Search for Artificial Life with Foundation Models. - Akarsh Kumar; Chris Lu 001; Louis Kirsch; Yujin Tang; Kenneth O. Stanley; Phillip Isola; David Ha (CoRR, 2024)

What Makes for a Good Stereoscopic Image? - Netanel Tamir; Shir Amir; Ranel Itzhaky; Noam Atia; Shobhita Sundaram; Stephanie Fu; Ron Sokolovsky; Phillip Isola; Tali Dekel; Richard Zhang 001; Miriam Farber (CVPR Workshops, 2025)

Adaptive Length Image Tokenization via Recurrent Allocation. - Shivam Duggal; Phillip Isola; Antonio Torralba 001; William T. Freeman (ICLR, 2025)

Personalized Representation from Personalized Generation. - Shobhita Sundaram; Julia Chae; Yonglong Tian; Sara Beery; Phillip Isola (ICLR, 2025)

Scalable Real2Sim: Physics-Aware Asset Generation Via Robotic Pick-and-Place Setups. - Nicholas Pfaff; Evelyn Fu; Jeremy Binagia; Phillip Isola; Russ Tedrake (CoRR, 2025)

Cycle Consistency as Reward: Learning Image-Text Alignment without Human Preferences. - Hyojin Bahng; Caroline Chan; Frédo Durand; Phillip Isola (CoRR, 2025)

Single-pass Adaptive Image Tokenization for Minimum Program Search. - Shivam Duggal; Sanghyun Byun; William T. Freeman; Antonio Torralba 001; Phillip Isola (CoRR, 2025)

Assessing Adaptive World Models in Machines with Novel Games. - Lance Ying; Katherine M. Collins; Prafull Sharma; Cedric Colas; Kaiya Ivy Zhao; Adrian Weller; Zenna Tavares; Phillip Isola; Samuel J. Gershman; Jacob Andreas; Thomas L. Griffiths 001; François Chollet; et al. (CoRR, 2025)

Training Transformers with Enforced Lipschitz Constants. - Laker Newhouse; R. Preston Hess; Franz Cesista; Andrii Zahorodnii; Jeremy Bernstein; Phillip Isola (CoRR, 2025)

Separating Knowledge and Perception with Procedural Data. - Adrián Rodríguez-Muñoz; Manel Baradad; Phillip Isola; Antonio Torralba 001 (CoRR, 2025)

Results of the NeurIPS 2023 Neural MMO Competition on Multi-task Reinforcement Learning. - Joseph Suárez; Kyoung Whan Choe; David Bloomin; Jianming Gao; Yunkun Li; Yao Feng; Saidinesh Pola; Kun Zhang; Yonghui Zhu; Nikhil Pinnaparaju; Hao Xiang Li; Nishaanth Kanna; et al. (CoRR, 2025)