2 citations · 4 across the 14 of their papers we have counts for
7 papers · 1 filter
I2CD: Direct Image-to-Convex Decomposition for Simulation-Ready Collision Geometry
Qian Wang, Liam Merz Hoffmeister, Brian Scassellati +1
Physics simulators and motion planners require convex collision geometry, yet image-to-3D generative models output dense, frequently non-manifold visual meshes. Bridging the two to…
Compiling Learning Problems into Adaptation Programs for Language Models
Rebecca Ramnauth, Brian Scassellati
Model adaptation is typically governed by a fixed recipe, even though different update programs can produce substantially different behavioral outcomes. We introduce adaptation com…
Robots Influencing Humans to Reveal their Goals during Collaboration and Competition
Debasmita Ghose, Oz Gitelson, Michal Lewkowicz +3
We propose a unified strategy for fast goal inference in human-robot interaction. The core idea is to drive the human toward Critical Decision Points (CDPs)-states where competing…
Localized Adaptation Reveals Distinct Learning Signatures in Transformers
Rebecca Ramnauth, Brian Scassellati
Transformer adaptation is typically distributed across model depth, even when the intended change is narrow. We investigate how adaptation site shapes what a model learns, how well…
The Attentional White Bear Effect in Transformer Language Models
Rebecca Ramnauth, Brian Scassellati
Instruction-based suppression is widely used to prevent language models from generating prohibited content, yet it remains unclear whether suppression reduces internal representati…
Robotics-Inspired Guardrails for Foundation Models in Socially Sensitive Domains
Rebecca Ramnauth, Drazen Brscic, Brian Scassellati
Foundation models are increasingly deployed in socially sensitive domains such as education, mental health, and caregiving, where failures are often cumulative and context-dependen…
Towards Zero-Knowledge Task Planning via a Language-based Approach
Liam Merz Hoffmeister, Brian Scassellati, Daniel Rakita
In this work, we introduce and formalize the Zero-Knowledge Task Planning (ZKTP) problem, i.e., formulating a sequence of actions to achieve some goal without task-specific knowled…