Addressing the Loss-Metric Mismatch with Adaptive Loss Alignment. - Chen Huang 001; Shuangfei Zhai; Walter Talbott; Miguel Ángel Bautista 001; Shih-Yu Sun; Carlos Guestrin; Joshua M. Susskind (ICML, 2019)

Adversarial Fisher Vectors for Unsupervised Representation Learning. - Shuangfei Zhai; Walter Talbott; Carlos Guestrin; Joshua M. Susskind (NeurIPS, 2019)

Set Distribution Networks: a Generative Model for Sets of Images. - Shuangfei Zhai; Walter Talbott; Miguel Ángel Bautista 001; Carlos Guestrin; Josh M. Susskind (CoRR, 2020)

On the generalization of learning-based 3D reconstruction. - Miguel Ángel Bautista 001; Walter Talbott; Shuangfei Zhai; Nitish Srivastava; Joshua M. Susskind (WACV, 2021)

An Attention Free Transformer. - Shuangfei Zhai; Walter Talbott; Nitish Srivastava; Chen Huang 001; Hanlin Goh; Ruixiang Zhang; Josh M. Susskind (CoRR, 2021)

Robust Robotic Control from Pixels using Contrastive Recurrent State-Space Models. - Nitish Srivastava; Walter Talbott; Martin Bertran Lopez; Shuangfei Zhai; Josh M. Susskind (CoRR, 2021)

Efficient Representation Learning via Adaptive Context Pooling. - Chen Huang 001; Walter Talbott; Navdeep Jaitly; Joshua M. Susskind (ICML, 2022)

Position Prediction as an Effective Pretraining Strategy. - Shuangfei Zhai; Navdeep Jaitly; Jason Ramapuram; Dan Busbridge; Tatiana Likhomanenko; Joseph Y. Cheng; Walter Talbott; Chen Huang 001; Hanlin Goh; Joshua M. Susskind (ICML, 2022)

Regularized Training of Nearest Neighbor Language Models. - Jean-Francois Ton; Walter Talbott; Shuangfei Zhai; Joshua M. Susskind (NAACL-HLT (Student Research Workshop), 2022)

GAUDI: A Neural Architect for Immersive 3D Scene Generation. - Miguel Ángel Bautista 001; Pengsheng Guo; Samira Abnar; Walter Talbott; Alexander Toshev; Zhuoyuan Chen; Laurent Dinh; Shuangfei Zhai; Hanlin Goh; Daniel Ulbricht; Afshin Dehghan; Joshua M. Susskind (NeurIPS, 2022)

Efficient Embedding of Semantic Similarity in Control Policies via Entangled Bisimulation. - Martin Bertran Lopez; Walter Talbott; Nitish Srivastava; Joshua M. Susskind (CoRR, 2022)

TRACT: Denoising Diffusion Models with Transitive Closure Time-Distillation. - David Berthelot; Arnaud Autef; Jierui Lin; Dian Ang Yap; Shuangfei Zhai; Siyuan Hu; Daniel Zheng; Walter Talbott; Eric Gu (CoRR, 2023)

Value function estimation using conditional diffusion models for control. - Bogdan Mazoure; Walter Talbott; Miguel Ángel Bautista 001; R. Devon Hjelm; Alexander Toshev; Joshua M. Susskind (CoRR, 2023)

Large Language Models as Generalizable Policies for Embodied Tasks. - Andrew Szot; Max Schwarzer; Harsh Agrawal; Bogdan Mazoure; Walter Talbott; Katherine Metcalf; Natalie Mackraz; R. Devon Hjelm; Alexander Toshev (CoRR, 2023)

Large Language Models as Generalizable Policies for Embodied Tasks. - Andrew Szot; Max Schwarzer; Harsh Agrawal; Bogdan Mazoure; Rin Metcalf; Walter Talbott; Natalie Mackraz; R. Devon Hjelm; Alexander T. Toshev (ICLR, 2024)

Efficient Non-Parametric Uncertainty Quantification for Black-Box Large Language Models and Decision Planning. - Yao-Hung Hubert Tsai; Walter Talbott; Jian Zhang 050 (CoRR, 2024)

On the benefits of pixel-based hierarchical policies for task generalization. - Tudor Cristea-Platon; Bogdan Mazoure; Josh Susskind; Walter Talbott (CoRR, 2024)

Local Policies Enable Zero-shot Long-horizon Manipulation. - Murtaza Dalal; Min Liu; Walter Talbott; Chen Chen 032; Deepak Pathak; Jian Zhang 050; Ruslan Salakhutdinov (CoRR, 2024)

EMOTION: Expressive Motion Sequence Generation for Humanoid Robots with In-Context Learning. - Peide Huang; Yuhan Hu; Nataliya Nechyporenko; Daehwa Kim; Walter Talbott; Jian Zhang (CoRR, 2024)

EMOTION: Expressive Motion Sequence Generation for Humanoid Robots With In-Context Learning. - Peide Huang; Yuhan Hu; Nataliya Nechyporenko; Daehwa Kim; Walter Talbott; Jian Zhang 050 (IEEE Robotics Autom. Lett., 2025)