1 citations · 1 across the 7 of their papers we have counts for
7 papers
PersonalHomeBench: Evaluating Agents in Personalized Smart Homes
Manasa Bharadwaj, Yolanda Liu, InJung Yang +5
Agentic AI systems are rapidly advancing toward real-world applications, yet their readiness in complex and personalized environments remains insufficiently characterized. To addre…
MAPLE: Modality-Aware Post-training and Learning Ecosystem
Nikhil Verma, Minjung Kim, JooYoung Yoo +5
Multimodal language models now integrate text, audio, and video for unified reasoning. Yet existing RL post-training pipelines treat all input signals as equally relevant, ignoring…
SMaRT: Select, Mix, and ReinvenT -- A Strategy Fusion Framework for LLM-Driven Reasoning and Planning
Nikhil Verma, Manasa Bharadwaj, Wonjun Jang +4
Large Language Models (LLMs) have redefined complex task automation with exceptional generalization capabilities. Despite these advancements, state-of-the-art methods rely on singl…
OmniReflect: Discovering Transferable Constitutions for LLM agents via Neuro-Symbolic Reflections
Manasa Bharadwaj, Nikhil Verma, Kevin Ferreira
Efforts to improve Large Language Model (LLM) agent performance on complex tasks have largely focused on fine-tuning and iterative self-correction. However, these approaches often…
Cross-Attention Speculative Decoding
Wei Zhong, Manasa Bharadwaj, Yixiao Wang +2
Speculative decoding (SD) is a widely adopted approach for accelerating inference in large language models (LLMs), particularly when the draft and target models are well aligned. H…
Fake It To Make It: Virtual Multiviews to Enhance Monocular Indoor Semantic Scene Completion
Anith Selvakumar, Manasa Bharadwaj
Monocular Indoor Semantic Scene Completion (SSC) aims to reconstruct a 3D semantic occupancy map from a single RGB image of an indoor scene, inferring spatial layout and object cat…
S3D: A Simple and Cost-Effective Self-Speculative Decoding Scheme for Low-Memory GPUs
Wei Zhong, Manasa Bharadwaj
Speculative decoding (SD) has attracted a significant amount of research attention due to the substantial speedup it can achieve for LLM inference. However, despite the high speedu…