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H. Shi

8 papers hereh-index 6136 citations9 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author3
  • last author4

Across the 8 of 8 papers where every author was matched, so the position is known.

fields
  • cs.LG7
  • cs.AI1
same name
  • H. Shi — 220 papers, h 25
  • H. Shi — 186 papers, h 4
  • H. Shi — 115 papers, h 5
  • H. Shi — 94 papers, h 6
  • H. Shi — 16 papers, h 16
  • H. Shi — 12 papers

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20232026
collaborators
Showing 2026Show all

4 papers · 1 filter

cs.AI2026

Proximity-Based Multi-Turn Optimization: Practical Credit Assignment for LLM Agent Training

Yangyi Fang, Jiaye Lin, Xiaoliang Fu +4

Multi-turn LLM agents are becoming pivotal to production systems, spanning customer service automation, e-commerce assistance, and interactive task management, where accurately dis…

cs.LG2026

Clarifying Shampoo: Adapting Spectral Descent to Stochasticity and the Parameter Trajectory

Runa Eschenhagen, Anna Cai, Tsung-Hsien Lee +1

Optimizers leveraging the matrix structure in neural networks, such as Shampoo and Muon, are more data-efficient than element-wise algorithms like Adam and Signum. While in specifi…

cs.LG2026

How to Allocate, How to Learn? Dynamic Rollout Allocation and Advantage Modulation for Policy Optimization

Yangyi Fang, Jiaye Lin, Xiaoliang Fu +6

Reinforcement Learning with Verifiable Rewards (RLVR) has proven effective for Large Language Model (LLM) reasoning, yet current methods face key challenges in resource allocation…

cs.LG2026

Adaptive Batch Sizes Using Non-Euclidean Gradient Noise Scales for Stochastic Sign and Spectral Descent

Hiroki Naganuma, Shagun Gupta, Youssef Briki +4

To maximize hardware utilization, modern machine learning systems typically employ large constant or manually tuned batch size schedules, relying on heuristics that are brittle and…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.