333 citations · 588 across the 48 of their papers we have counts for
6 papers · 1 filter
RoboQuest: Generalist Physical Agents that Search, Inspect and Test
Liu Renhang, Navonil Majumder, Tej Deep Pala +1
Recent advances in multimodal foundation models have made them capable generalist physical agents for a range of manipulation tasks. However, successful operation in an unfamiliar…
MemBodied: Recurrent Associative Memory for Vision-Language-Action Models
Tej Deep Pala, Navonil Majumder, Bryce Goh +4
Vision-Language-Action models provide a strong foundation for general-purpose robot control, yet a vast majority of policies do not preserve and leverage episode-level information…
MNIST-PRO: MNIST is Back as a Partially Observable World for AI Agents
Vernon Toh, Navonil Majumder, Zhengyuan Liu +2
AI agents in partially observable environments need to coordinate active sensing with working memory to maintain an evolving perceptual state. However, existing benchmarks struggle…
ScrambleToolBench: Agents Search Exhaustively Even When Their Own Map Points to the Next Step
Vernon Toh, Navonil Majumder, Zhengyuan Liu +2
To operate robustly in open-world environments, autonomous agents should be able to infer the behavior of unfamiliar systems through interaction alone, even in the absence of docum…
IDEAgent: Agentic Quality-Diversity Search for Research Idea Generation
Varun Gumma, Navonil Majumder, Soumitra Sinhahajari +1
Large Language Models (LLMs) have significantly advanced the automation of scientific discovery. However, existing systems share a core limitation: they optimize ideas independentl…
On the Limits of LLM-as-Judge for Scientific Novelty Assessment
Soumitra Sinhahajari, Navonil Majumder, Soujanya Poria
LLMs are increasingly used to generate and judge scientific ideas. This makes novelty evaluation a central problem. Full idea evaluation is difficult because it often requires judg…