declare-lab/RoboQuest
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AI & ML interests
Natural Language Processing
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Papers
MNIST-PRO: MNIST is Back as a Partially Observable World for AI Agents
ScrambleToolBench: Agents Search Exhaustively Even When Their Own Map Points to the Next Step
liu-hanghang
updated a
dataset about 3 hours ago
soujanyaporia
published a
dataset about 22 hours ago
soujanyaporia
authored 4
papers 7 days ago
BaRe-Mem: Bayesian Reliability Memory for Robust and Adaptive Agent Consultation
Paper • 2609.35551 • Published • 8
Just MLPs: Efficient Visual State Reconstruction for Multimodal Language Models
Paper • 2609.34972 • Published • 30
MemBodied: Recurrent Associative Memory for Vision-Language-Action Models
Paper • 2609.28256 • Published • 17
Chain-of-Knowledge: Grounding Large Language Models via Dynamic Knowledge Adapting over Heterogeneous Sources
Paper • 2305.13269 • Published
Sssunset
authored a
paper 8 days ago
huaXiaKyrie
authored a
paper 8 days ago
Sssunset
authored a
paper 8 days ago
Sssunset
submitted a
paper to Daily Papers 8 days ago
huaXiaKyrie
submitted a
paper to Daily Papers 8 days ago
soujanyaporia
submitted a
paper to Daily Papers 13 days ago
soujanyaporia
authored 8
papers 27 days ago
GE-Act 2.0: Pretraining and Scaling a World-Action Model for Robotic Manipulation
Paper • 2609.05588 • Published • 57
MNIST-PRO: MNIST is Back as a Partially Observable World for AI Agents
Paper • 2608.31022 • Published • 9
ScrambleToolBench: Agents Search Exhaustively Even When Their Own Map Points to the Next Step
Paper • 2608.02358 • Published • 12
Data Agent: Learning to Select Data via End-to-End Dynamic Optimization
Paper • 2603.07433 • Published
$Σ$-Mem: An Online Reliability Memory for LLM-based Multi-Agent Systems
Paper • 2607.27958 • Published • 19
IDEAgent: Agentic Quality-Diversity Search for Research Idea Generation
Paper • 2607.22375 • Published • 10
On the Limits of LLM-as-Judge for Scientific Novelty Assessment
Paper • 2606.12071 • Published • 2
GRAIL: Gradient-Reweighted Advantages for Reinforcement Learning with Verifiable Rewards
Paper • 2606.04889 • Published • 4