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Shuo Ren

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Preprint Aug 2026

EviGraph: Evidence-Guided Autonomous Research Agents

EviGraph is introduced, an autonomous research framework that represents the research process as a typed evidence graph containing Problem, Gap, Hypothesis, Experiment, Finding, and Claim nodes, and the graph serves as the operational state of the agent rather than a post-hoc record.

Zhen-Jiang Ren, Rui-Ji Li, Xu-Jing Zhang et al. · 1 citation
Preprint Sep 2026

PhysBrain 1.5: From Vision-Language Models to Physical Foundation Models

Qualitative examples show the PhysBrain 1.5 model's ability to produce end-effector trajectories and predict future scenes through spatially aligned RGB, depth, and robot-mask outputs.

DeepCybo Team, Yue Bin, Hai-Peng Cao et al. · 0 citations
#artificial intelligence Preprint Sep 2026

SkillAlign: Aligning Skill Interfaces for LLM-based Agents

SkillAlign is proposed, a provider-agnostic framework that represents candidate skills as multi-view procedural cards and renders them through alternative exposure interfaces, including full instructions, hints, compressed summaries, workflows, or no exposure, which enables counterfactual evaluation where the task, age...

Shuo Ren, Xiaomian Kang, Jia-Jun Zhang · 0 citations
Preprint Aug 2026

AgenticECO: An Agentic Framework for ECO on 3D Integrated Circuits

AgenticECO, an evidence-gated tool-using agent workflow for 3D-IC ECO on the open-source TaiWei flow, paired with EcoRoute, a minimal-disturbance ECO-routing layer that drives the unmodified pinned router so a repair is attributable to its edit.

Shuo Ren, Yaohui Han, Libo Shen et al. · 0 citations
Preprint Aug 2026

EDGE: Experience-Distillation for Guided Exploration in Agentic Reinforcement Learning

This work proposes EDGE (Experience-Distillation for Guided Exploration), a framework that treats retrieved experiences as temporary training-time scaffolds and progressively internalizes their benefits into the parametric policy.

Can Xie, Yu-Yi Zhou, Wen Yang et al. · 2 citations
Preprint Jul 2026

AgenticPD: A Stage-Aware Agentic Framework for Physical Design QoR Optimization

AgenticPD is a stage-aware agentic framework for physical design QoR optimization, organized around the stage boundaries of the physical design flow, where a Judge Agent navigates the search and stage-specialized agents make local decisions within their own stage using stage-local tools.

Shuo Ren, Zijin Cheng, Yaohui Han et al. · 0 citations

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