Influencing Flock Formation in Low-Density Settings. - Daniel Y. Fu; Emily S. Wang; Peter M. Krafft; Barbara J. Grosz (AAMAS, 2018)

Automatic Parallelization of Sequential Programs. - Peter Kraft; Amos Waterland; Daniel Y. Fu; Anitha Gollamudi; Shai Szulanski; Margo I. Seltzer (CoRR, 2018)

Multi-Resolution Weak Supervision for Sequential Data. - Paroma Varma; Frederic Sala; Shiori Sagawa; Jason Alan Fries; Daniel Y. Fu; Saelig Khattar; Ashwini Ramamoorthy; Ke Xiao; Kayvon Fatahalian; James Priest; Christopher Ré (NeurIPS, 2019)

Rekall: Specifying Video Events using Compositions of Spatiotemporal Labels. - Daniel Y. Fu; Will Crichton; James Hong; Xinwei Yao 002; Haotian Zhang 004; Anh Truong; Avanika Narayan; Maneesh Agrawala; Christopher Ré; Kayvon Fatahalian (CoRR, 2019)

Fast and Three-rious: Speeding Up Weak Supervision with Triplet Methods. - Daniel Y. Fu; Mayee F. Chen; Frederic Sala; Sarah M. Hooper; Kayvon Fatahalian; Christopher Ré (ICML, 2020)

Train and You'll Miss It: Interactive Model Iteration with Weak Supervision and Pre-Trained Embeddings. - Mayee F. Chen; Daniel Y. Fu; Frederic Sala; Sen Wu 002; Ravi Teja Mullapudi; Fait Poms; Kayvon Fatahalian; Christopher Ré (CoRR, 2020)

Analyzing Who and What Appears in a Decade of US Cable TV News. - James Hong; Will Crichton; Haotian Zhang 004; Daniel Y. Fu; Jacob Ritchie; Jeremy Barenholtz; Ben Hannel; Xinwei Yao 002; Michaela Murray; Geraldine Moriba; Maneesh Agrawala; Kayvon Fatahalian (CoRR, 2020)

Let's Hope it Works! Inaccurate Supervision of Neural Networks with Incorrect Labels: Application to Epilepsy. - Florian Dubost; Erin Hong; Daniel Y. Fu; Nandita Bhaskhar; Siyi Tang; Khaled Saab 002; Daniel L. Rubin; Jared Dunnmon; Christopher Lee-Messer (CoRR, 2020)

Analysis of Faces in a Decade of US Cable TV News. - James Hong; Will Crichton; Haotian Zhang 004; Daniel Y. Fu; Jacob Ritchie; Jeremy Barenholtz; Ben Hannel; Xinwei Yao 002; Michaela Murray; Geraldine Moriba; Maneesh Agrawala; Kayvon Fatahalian (KDD, 2021)

Double Descent Optimization Pattern and Aliasing: Caveats of Noisy Labels. - Florian Dubost; Khaled Kamal Saab; Erin Hong; Daniel Yang Fu; Max Pike; Siddharth Sharma; Siyi Tang; Nandita Bhaskhar; Christopher Lee-Messer; Daniel L. Rubin (CoRR, 2021)

TABi: Type-Aware Bi-Encoders for Open-Domain Entity Retrieval. - Megan Leszczynski; Daniel Y. Fu; Mayee F. Chen; Christopher Ré (ACL (Findings), 2022)

Perfectly Balanced: Improving Transfer and Robustness of Supervised Contrastive Learning. - Mayee F. Chen; Daniel Y. Fu; Avanika Narayan; Michael Zhang; Zhao Song 002; Kayvon Fatahalian; Christopher Ré (ICML, 2022)

FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness. - Tri Dao; Daniel Y. Fu; Stefano Ermon; Atri Rudra; Christopher Ré (NeurIPS, 2022)

Shoring up the foundations: fusing model embeddings and weak supervision. - Mayee F. Chen; Daniel Y. Fu; Dyah Adila; Michael Zhang; Frederic Sala; Kayvon Fatahalian; Christopher Ré (UAI, 2022)

Lost in Transmission: On the Impact of Networking Corruptions on Video Machine Learning Models. - Trenton Chang; Daniel Y. Fu (CoRR, 2022)

Hungry Hungry Hippos: Towards Language Modeling with State Space Models. - Daniel Y. Fu; Tri Dao; Khaled Kamal Saab; Armin W. Thomas; Atri Rudra; Christopher Ré (ICLR, 2023)

Simple Hardware-Efficient Long Convolutions for Sequence Modeling. - Daniel Y. Fu; Elliot L. Epstein; Eric Nguyen; Armin W. Thomas; Michael Zhang; Tri Dao; Atri Rudra; Christopher Ré (ICML, 2023)

Hyena Hierarchy: Towards Larger Convolutional Language Models. - Michael Poli; Stefano Massaroli; Eric Nguyen; Daniel Y. Fu; Tri Dao; Stephen Baccus; Yoshua Bengio; Stefano Ermon; Christopher Ré (ICML, 2023)

Monarch Mixer: A Simple Sub-Quadratic GEMM-Based Architecture. - Daniel Y. Fu; Simran Arora; Jessica Grogan; Isys Johnson; Evan Sabri Eyuboglu; Armin W. Thomas; Benjamin Spector; Michael Poli; Atri Rudra; Christopher Ré (NeurIPS, 2023)

Laughing Hyena Distillery: Extracting Compact Recurrences From Convolutions. - Stefano Massaroli; Michael Poli; Daniel Y. Fu; Hermann Kumbong; Rom N. Parnichkun; David W. Romero; Aman Timalsina; Quinn McIntyre; Beidi Chen; Atri Rudra; Ce Zhang 001; Christopher Ré; et al. (NeurIPS, 2023)

High-throughput Generative Inference of Large Language Models with a Single GPU. - Ying Sheng 007; Lianmin Zheng; Binhang Yuan; Zhuohan Li 001; Max Ryabinin; Daniel Y. Fu; Zhiqiang Xie; Beidi Chen; Clark W. Barrett; Joseph E. Gonzalez; Percy Liang; Christopher Ré; et al. (CoRR, 2023)

FlashFFTConv: Efficient Convolutions for Long Sequences with Tensor Cores. - Daniel Y. Fu; Hermann Kumbong; Eric Nguyen; Christopher Ré (ICLR, 2024)

Benchmarking and Building Long-Context Retrieval Models with LoCo and M2-BERT. - Jon Saad-Falcon; Daniel Y. Fu; Simran Arora; Neel Guha; Christopher Ré (ICML, 2024)

RedPajama: an Open Dataset for Training Large Language Models. - Maurice Weber; Daniel Y. Fu; Quentin Anthony; Yonatan Oren; Shane Adams; Anton Alexandrov; Xiaozhong Lyu; Huu Nguyen; Xiaozhe Yao; Virginia Adams; Ben Athiwaratkun; Rahul Chalamala; et al. (NeurIPS, 2024)

Hydragen: High-Throughput LLM Inference with Shared Prefixes. - Jordan Juravsky; Bradley C. A. Brown; Ryan Ehrlich; Daniel Y. Fu; Christopher Ré; Azalia Mirhoseini (CoRR, 2024)

ThunderKittens: Simple, Fast, and Adorable AI Kernels. - Benjamin Spector; Simran Arora; Aaryan Singhal; Daniel Y. Fu; Christopher Ré (CoRR, 2024)

HMAR: Efficient Hierarchical Masked Auto-Regressive Image Generation. - Hermann Kumbong; Xian Liu; Tsung-Yi Lin; Ming-Yu Liu 001; Xihui Liu; Ziwei Liu; Daniel Y. Fu; Christopher Ré; David W. Romero (CVPR, 2025)

ThunderKittens: Simple, Fast, and Adorable Kernels. - Benjamin Frederick Spector; Simran Arora; Aaryan Singhal; Arjun Parthasarathy; Daniel Y. Fu; Christopher Ré (ICLR, 2025)

Chipmunk: Training-Free Acceleration of Diffusion Transformers with Dynamic Column-Sparse Deltas. - Austin Silveria; Soham Govande; Daniel Y. Fu (CoRR, 2025)

Exploring Diffusion Transformer Designs via Grafting. - Keshigeyan Chandrasegaran; Michael Poli; Daniel Y. Fu; Dongjun Kim; Lea M. Hadzic; Manling Li; Agrim Gupta; Stefano Massaroli; Azalia Mirhoseini; Juan Carlos Niebles; Stefano Ermon; Li Fei-Fei 001 (CoRR, 2025)