The lab is run by Yonatan Bisk and is housed primarily in the Language Technologies Institute (LTI), with members from the Machine Learning Department (MLD), Robotics Institute(RI), and Computer Science Department (CSD).
What're we up to?
Postdocs
PhD Students
📚Generalization
@_Yingshan she/her
Model Successor Functions
Language Models Need Inductive Biases to Count Inductively
Tools Fail: Detecting Silent Errors in Faulty Tools
DiffusionPID: Interpreting Diffusion via Partial Information Decomposition
VISREAS: Complex Visual Reasoning with Unanswerable Questions
Skews in the Phenomenon Space Hinder Generalization in Text-to-Image Generation
Training Vision-Language Transformers from Captions
WebQA: Multihop and Multimodal QA
Model Successor Functions
Language Models Need Inductive Biases to Count Inductively
Tools Fail: Detecting Silent Errors in Faulty Tools
DiffusionPID: Interpreting Diffusion via Partial Information Decomposition
VISREAS: Complex Visual Reasoning with Unanswerable Questions
Skews in the Phenomenon Space Hinder Generalization in Text-to-Image Generation
Training Vision-Language Transformers from Captions
WebQA: Multihop and Multimodal QA
Jared Fernandez Jared Fernandez
📚Energy/Resource Efficiency
@FernJared he/him
(co- Emma Strubell)
Position: Evaluation of {ML} Resource Utilization Requires Model Life Cycle Assessment
Energy Considerations of Large Language Model Inference and Efficiency Optimizations
Efficient Hardware Scaling and Diminishing Returns in Large-Scale Training of Language Models
Gradient Localization Improves Lifelong Pretraining of Language Models
The Framework Tax: Disparities Between Inference Efficiency in Research and Deployment
Position: Evaluation of {ML} Resource Utilization Requires Model Life Cycle Assessment
Energy Considerations of Large Language Model Inference and Efficiency Optimizations
Efficient Hardware Scaling and Diminishing Returns in Large-Scale Training of Language Models
Gradient Localization Improves Lifelong Pretraining of Language Models
The Framework Tax: Disparities Between Inference Efficiency in Research and Deployment
📚Dexterity
@DanielXieee he/him
MM-SeR: Multimodal Self-Refinement for Lightweight Image Captioning
Unsupervised Discovery of Long-Term Spatiotemporal Periodic Workflows in Human Activities
Affordance RAG: Hierarchical Multimodal Retrieval with Affordance-Aware Embodied Memory for Mobile Manipulation
Embodied-RAG: General non-parametric Embodied Memory for Retrieval and Generation
Toward General-Purpose Robots via Foundation Models: A Survey and Meta-Analysis
Reasoning about the Unseen for Efficient Outdoor Object Navigation
MM-SeR: Multimodal Self-Refinement for Lightweight Image Captioning
Unsupervised Discovery of Long-Term Spatiotemporal Periodic Workflows in Human Activities
Affordance RAG: Hierarchical Multimodal Retrieval with Affordance-Aware Embodied Memory for Mobile Manipulation
Embodied-RAG: General non-parametric Embodied Memory for Retrieval and Generation
Toward General-Purpose Robots via Foundation Models: A Survey and Meta-Analysis
Reasoning about the Unseen for Efficient Outdoor Object Navigation
Masters, Independent Studies, and Visitors
Cats
Star 🌟
she/her
Comet 💫
he/him
Alumni
| 2026 | Yash Jangir | MSR | → PhD @ JHU | |
| 2026 | Claire Jin | 5th Year MS | → PhD @ CMU | |
| 2025 | Sheryl Matthew | Undergrad | → PhD @ USC |  |
| 2024 | Minyoung Hwang | Intern | → PhD @ MIT | |
| 2022 | Xiang Fan | Undergraduate | → PhD @ UWashington | |
| 2022 | Andy Liu | Intern | → PhD @ CMU | |
| 2022 | Deogratias Amani | Intern | → | |
| 2022 | Josh Zhanson | MLT | → Data Scientist @ MSFT | |
| 2022 | Xiaoyu (Erin) Zhang | 5th year MS | → PhD @ UIUC | |
| 2021 | Feiyu (Gavin) Zhu | Undergrad | → PhD @ CMU | |
| 2021 | Blessing Bassey | Intern | → | |
| 2021 | Melanie Sclar | Intern | → PhD @ UWashington | |