2 citations · 2 across the 7 of their papers we have counts for
9 papers
JevGPT: Thinking Fast and Slow in Autonomous Research
Yasheng Sun, Yanning Dai, Yimeng Chen +9
Autonomous research agents must acquire and reason over evidence within a limited budget. Yet relevant sources can remain uninspected or unused, leaving a gap between retrieval cov…
History Replays Itself: Unleashing Long-Context Capability in Linear Attention
Li Nanbo, Firas Laakom, Yilan Zhang +10
Linear attention promises the efficiency needed for long-context language modelling, yet its fixed-size recurrent state must simultaneously support ongoing computation and preserve…
Market Design for AI: Beyond the Copyright Binary
Yan Dai, Maryam Farboodi, Negin Golrezaei +1
How can we design a market of human-generated content for use in training AI models that both enables technological progress and preserves individual incentives for high-quality co…
Efficient Morphology-Control Co-Design via Stackelberg Proximal Policy Optimization
Yanning Dai, Yuhui Wang, Dylan R. Ashley +1
Morphology-control co-design concerns the coupled optimization of an agent's body structure and control policy. This problem exhibits a bi-level structure, where the control dynami…
A Unified Framework for Rethinking Policy Divergence Measures in GRPO
Qingyuan Wu, Yuhui Wang, Simon Sinong Zhan +6
Reinforcement Learning with Verified Reward (RLVR) has emerged as a critical paradigm for advancing the reasoning capabilities of Large Language Models (LLMs). Most existing RLVR m…
Efficiency, Feasibility, and Incentive-Awareness in Constrained Online Resource Allocation
Yan Dai, Negin Golrezaei, Patrick Jaillet
We study the dynamic allocation of indivisible resources to strategic agents under long-term constraints, where the planner aims to maximize social welfare, satisfy multiple constr…
Non-Monetary Mechanism Design without Priors: Achieving Efficiency via Adaptive Costly Audits
Yan Dai, Moise Blanchard, Patrick Jaillet
We study repeated resource allocation with strategic agents, where monetary transfers are disallowed and the planner has no prior information on agents' utility distributions. Insp…
Towards a Robust Soft Baby Robot With Rich Interaction Ability for Advanced Machine Learning Algorithms
Mohannad Alhakami, Dylan R. Ashley, Joel Dunham +4
Advanced machine learning algorithms require platforms that are extremely robust and equipped with rich sensory feedback to handle extensive trial-and-error learning without relyin…
Understanding Adam Optimizer via Online Learning of Updates: Adam is FTRL in Disguise
Kwangjun Ahn, Zhiyu Zhang, Yunbum Kook +1
Despite the success of the Adam optimizer in practice, the theoretical understanding of its algorithmic components still remains limited. In particular, most existing analyses of A…