1 citations · 1 across the 7 of their papers we have counts for
8 papers
MoRSE: Task-Oriented Multi-Agent System with Mixture of Role-Subtask Experts
Peiwen Li, Shiyang Zhang, Yangtian Zhang +3
Large language model-based multi-agent systems have recently shown strong potential for complex, long-horizon tasks. However, existing methods mainly rely on coarse prompt-level di…
Learning Permutation Distributions via Reflected Diffusion on Ranks
Sizhuang He, Yangtian Zhang, Shiyang Zhang +1
The finite symmetric group S_n provides a natural domain for permutations, yet learning probability distributions on S_n is challenging due to its factorially growing size and disc…
STRIDE: Post-Training LLMs to Reason and Refine Bio-Sequences via Edit Trajectories
Daiheng Zhang, Shiyang Zhang, Sizhuang He +3
Discrete biological sequence optimization often requires goal-directed, parser-valid edits to an existing protein or molecule. Diffusion models support iterative refinement but do…
Echo-N1: Affective RL Frontier
Naifan Zhang, Ruihan Sun, Ruixi Su +9
The LLM field has spent a year perfecting RL for tasks machines already excel at, math, code, and deterministic reasoning, while completely sidestepping the domain that actually de…
Non-Markovian Discrete Diffusion with Causal Language Models
Yangtian Zhang, Sizhuang He, Daniel Levine +7
Discrete diffusion models offer a flexible, controllable approach to structured sequence generation, yet they still lag behind causal language models in expressive power. A key lim…
TANTE: Time-Adaptive Operator Learning via Neural Taylor Expansion
Zhikai Wu, Sifan Wang, Shiyang Zhang +5
Operator learning for time-dependent partial differential equations (PDEs) has seen rapid progress in recent years, enabling efficient approximation of complex spatiotemporal dynam…
A Simple and Efficient Baseline for Zero-Shot Generative Classification
Zipeng Qi, Buhua Liu, Shiyan Zhang +4
Large diffusion models have become mainstream generative models in both academic studies and industrial AIGC applications. Recently, a number of works further explored how to emplo…
Intelligence at the Edge of Chaos
Shiyang Zhang, Aakash Patel, Syed A Rizvi +5
We explore the emergence of intelligent behavior in artificial systems by investigating how the complexity of rule-based systems influences the capabilities of models trained to pr…