Laixi Shi — Papers on Cortexa

crossrefMachine Learning: Science and Technology2026-07-09

Lessons learned from the 2025 agentic AI for science hackathon

Jaehyung Lee, Harichandana Neralla, Charles Rhys Campbell, Kent Zhang, Akshaya Ajith, Justin Ely, et al.

Abstract The rapid emergence of agentic AI presents new opportunities and challenges for accelerating scientific discovery through tool-augmented reasoning, autonomous workflows, and reproducible results. To explore these capabilities in a hands-on, community-driven setting, we h…

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arxivcs.LGcs.AI2026-06-30

Geometry-Preserving Orthonormal Initialization for Low-Rank Adaptation in RLVR

Ruijia Zhang, Jiacheng Zhu, Hanqing Zhu, Laixi Shi

Low-rank adaptation (LoRA) and its variants enable parameter-efficient fine-tuning of large language models under the supervised fine-tuning (SFT) paradigm. However, their efficacy and behavior under Reinforcement learning with verifiable rewards (RLVR) are less well understood.…

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