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researcher

Dan Zhao

11 papers hereh-index 5646 citations13 works total

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

author position
  • sole author1
  • first author1
  • middle author8
  • last author1

Across the 11 of 11 papers where every author was matched, so the position is known.

fields
  • cs.LG6
  • cs.AI1
  • cs.AR1
  • cs.CL1
  • cs.DC1
  • quant-ph1
same name
  • Dan Zhao — 10 papers, h 12
  • Dan Zhao — 8 papers, h 4
  • Dan Zhao — 7 papers, h 5
  • Dan Zhao — 4 papers, h 8
  • Dan Zhao — 4 papers, h 3
  • Dan Zhao — 4 papers, h 3

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
most citedSustainable Supercomputing for AI: GPU Power Capping at HPC Scale

32 citations · 49 across the 11 of their papers we have counts for

collaborators
Showing 2025Show all

4 papers · 1 filter

cs.LG2025

Large Language Model Scaling Laws for Neural Quantum States in Quantum Chemistry

Oliver Knitter, Dan Zhao, Stefan Leichenauer +1

Scaling laws have been used to describe how large language model (LLM) performance scales with model size, training data size, or amount of computational resources. Motivated by th…

cs.AI2025

The Challenge of Teaching Reasoning to LLMs Without RL or Distillation

Wei Du, Branislav Kisacanin, George Armstrong +22

Reasoning-capable language models achieve state-of-the-art performance in diverse complex tasks by generating long, explicit Chain-of-Thought (CoT) traces. While recent works show…

quant-ph2025

Comparative study of the ansätze in quantum language models

Jordi Del Castillo, Dan Zhao, Zongrui Pei

Quantum language models are the alternative to classical language models, which borrow concepts and methods from quantum machine learning and computational linguistics. While sever…

cs.LG2025★ 2 cited

Layer by Layer: Uncovering Hidden Representations in Language Models

Oscar Skean, Md Rifat Arefin, Dan Zhao +4

From extracting features to generating text, the outputs of large language models (LLMs) typically rely on the final layers, following the conventional wisdom that earlier layers c…

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