1 citations · 1 across the 6 of their papers we have counts for
7 papers
InfraVLA: Extending Vision-Language-Action Navigation with Infrastructure Cameras
Lukas Vierling, Benjamin Ramtoula, Luke Robinson +2
Many indoor environments in which robots operate, such as warehouses, offices, and hospitals, already have cameras installed. They observe parts of the building that the robot cann…
Multimodal Model Diffing for Feature Discovery and Control
Hunar Batra, Lachin Naghashyar, Ashkan Khakzar +4
Multimodal Large Language Models (MLLMs) exhibit strong visual understanding, yet the internal features that cause these behaviors remain difficult to identify, audit, or control.…
MCJudgeBench: A Benchmark for Constraint-Level Judge Evaluation in Multi-Constraint Instruction Following
Jaeyun Lee, Junyoung Koh, Zeynel Tok +2
Multi-constraint instruction following requires verifying whether a response satisfies multiple individual requirements, yet LLM judges are often assessed only through overall-resp…
Medmarks: A Comprehensive Open-Source LLM Benchmark Suite for Medical Tasks
Benjamin Warner, Ratna Sagari Grandhi, Max Kieffer +32
Evaluating large language models (LLMs) for medical applications remains challenging due to benchmark saturation, limited data accessibility, and insufficient coverage of relevant…
Towards Understanding Multimodal Fine-Tuning: Spatial Features
Lachin Naghashyar, Hunar Batra, Ashkan Khakzar +4
Contemporary Vision-Language Models (VLMs) achieve strong performance on a wide range of tasks by pairing a vision encoder with a pre-trained language model, fine-tuned for visual-…
SpatialThinker: Reinforcing Scene Graph-Grounded Spatial Reasoning via Dense Rewards
Hunar Batra, Haoqin Tu, Hardy Chen +3
Multimodal large language models (MLLMs) have achieved remarkable progress in vision-language tasks, but continue to struggle with spatial reasoning. Existing spatial MLLMs rely on…
EVCL: Elastic Variational Continual Learning with Weight Consolidation
Hunar Batra, Ronald Clark
Continual learning aims to allow models to learn new tasks without forgetting what has been learned before. This work introduces Elastic Variational Continual Learning with Weight…