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20232026
most citedNeuro-Inspired Information-Theoretic Hierarchical Perception for Multimodal Learning

5 citations · 9 across the 19 of their papers we have counts for

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8 papers · 1 filter

cs.AI2026

ReM-MoA: Reasoning Memory Sustains Mixture-of-Agents Scaling

Heng Ping, Arijit Bhattacharjee, Peiyu Zhang +5

Mixture-of-Agents (MoA) architectures improve inference-time scaling by organizing multiple LLM agents into layered reasoning pipelines. However, existing MoA variants fail to sust…

cs.AI2026

RaMem: Contextual Reinstatement for Long-term Agentic Memory

Wei Yang, Bryce Kan, Shixuan Li +5

Long-term memory has become increasingly important for LLM agents that operate across extended interactions and evolving task contexts. Recent memory systems have made past experie…

cs.AI2026

COEVO: Co-Evolutionary Framework for Joint Functional Correctness and PPA Optimization in LLM-Based RTL Generation

Heng Ping, Peiyu Zhang, Shixuan Li +5

LLM-based RTL code generation methods increasingly target both functional correctness and PPA quality, yet existing approaches universally decouple the two objectives, optimizing P…

cs.AI2026

Auditing Multi-Agent LLM Reasoning Trees Outperforms Majority Vote and LLM-as-Judge

Wei Yang, Shixuan Li, Heng Ping +3

Multi-agent systems (MAS) can substantially extend the reasoning capacity of large language models (LLMs). Most MAS frameworks aggregate agent outputs via simple majority voting, d…

cs.AI2025

Maestro: Learning to Collaborate via Conditional Listwise Policy Optimization for Multi-Agent LLMs

Wei Yang, Jiacheng Pang, Shixuan Li +3

Multi-agent systems (MAS) built on Large Language Models (LLMs) are being used to approach complex problems and can surpass single model inference. However, their success hinges on…

cs.AI2025

VeriMoA: A Mixture-of-Agents Framework for Spec-to-HDL Generation

Heng Ping, Arijit Bhattacharjee, Peiyu Zhang +8

Automation of Register Transfer Level (RTL) design can help developers meet increasing computational demands. Large Language Models (LLMs) show promise for Hardware Description Lan…

cs.AI2024

Multi-scale Generative Modeling for Fast Sampling

Xiongye Xiao, Shixuan Li, Luzhe Huang +6

While working within the spatial domain can pose problems associated with ill-conditioned scores caused by power-law decay, recent advances in diffusion-based generative models hav…

cs.AI2024★ 1 cited

Neuron-based Multifractal Analysis of Neuron Interaction Dynamics in Large Models

Xiongye Xiao, Heng Ping, Chenyu Zhou +6

In recent years, there has been increasing attention on the capabilities of large models, particularly in handling complex tasks that small-scale models are unable to perform. Nota…