activity
20192026
most citedDERA: Enhancing Large Language Model Completions with Dialog-Enabled Resolving Agents

13 citations · 32 across the 10 of their papers we have counts for

collaborators

10 papers

cs.RO2026

Primitive Subspaces Mediate Few-Shot Transfer in VLAs

Anya Singh, Cabrel Happi, Jai Relan +2

Deploying vision-language-action (VLA) policies in industrial environments requires the ability to teach new tasks at low cost, a property current VLAs lack, since each new task re…

cs.CV2026

WristCompass: Kinematic Coupling as a Learnable Visual Concept for Ego-Camera Orientation

Varun Nair, Vidyut Baradwaj, Jiahang He +3

Recovering ego-camera orientation from manipulation video is a prerequisite for disentangling hand motion from camera motion, a key step in imitation learning from egocentric demon…

cs.LG2026

BOKBO (Best of K Bad Options): Calibrated Abstention for VLA Policies

Anya Singh, Cabrel Happi, Jai Relan +2

Test-time scaling for vision-language-action (VLA) policies, methods such as RoboMonkey, SEAL, MG-Select, and V-GPS, samples K candidate action chunks at inference and executes the…

cs.CL2023★ 1 cited

Extrinsically-Focused Evaluation of Omissions in Medical Summarization

Elliot Schumacher, Daniel Rosenthal, Dhruv Naik +4

Large language models (LLMs) have shown promise in safety-critical applications such as healthcare, yet the ability to quantify performance has lagged. An example of this challenge…

cs.CL2023★ 2 cited

Generating medically-accurate summaries of patient-provider dialogue: A multi-stage approach using large language models

Varun Nair, Elliot Schumacher, Anitha Kannan

A medical provider's summary of a patient visit serves several critical purposes, including clinical decision-making, facilitating hand-offs between providers, and as a reference f…

cs.CL2023

CONSCENDI: A Contrastive and Scenario-Guided Distillation Approach to Guardrail Models for Virtual Assistants

Albert Yu Sun, Varun Nair, Elliot Schumacher +1

A wave of new task-based virtual assistants has been fueled by increasingly powerful large language models (LLMs), such as GPT-4 (OpenAI, 2023). A major challenge in deploying LLM-…

cs.CL2023★ 13 cited

DERA: Enhancing Large Language Model Completions with Dialog-Enabled Resolving Agents

Varun Nair, Elliot Schumacher, Geoffrey Tso +1

Large language models (LLMs) have emerged as valuable tools for many natural language understanding tasks. In safety-critical applications such as healthcare, the utility of these…

cs.CL2021

Adding more data does not always help: A study in medical conversation summarization with PEGASUS

Varun Nair, Namit Katariya, Xavier Amatriain +2

Medical conversation summarization is integral in capturing information gathered during interactions between patients and physicians. Summarized conversations are used to facilitat…

cs.LG2021★ 4 cited

Training Neural Networks with Fixed Sparse Masks

Yi-Lin Sung, Varun Nair, Colin Raffel

During typical gradient-based training of deep neural networks, all of the model's parameters are updated at each iteration. Recent work has shown that it is possible to update onl…

cs.LG2019★ 12 cited

RealMix: Towards Realistic Semi-Supervised Deep Learning Algorithms

Varun Nair, Javier Fuentes Alonso, Tony Beltramelli

Semi-Supervised Learning (SSL) algorithms have shown great potential in training regimes when access to labeled data is scarce but access to unlabeled data is plentiful. However, o…