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Haoran Sun

4 papers hereh-index 472 citations12 works total

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

author position
  • first author1
  • middle author2

Across the 3 of 4 papers where every author was matched, so the position is known.

fields
  • cs.GT3
  • cs.LG1
same name
  • Haoran Sun — 15 papers, h 34
  • Haoran Sun — 12 papers, h 4
  • Haoran Sun — 11 papers, h 2
  • Haoran Sun — 10 papers, h 8
  • Haoran Sun — 9 papers, h 2
  • Haoran Sun — 9 papers, h 4

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

most citedALPINE: Unveiling the Planning Capability of Autoregressive Learning in Language Models

1 citations · 1 across the 3 of their papers we have counts for

collaborators

4 papers

cs.GT2026

Enhancing Affine Maximizer Auctions with Correlation-Aware Payment

Haoran Sun, Xuanzhi Xia, Xu Chu +1

Affine Maximizer Auctions (AMAs), a generalized mechanism family from VCG, are widely used in automated mechanism design due to their inherent dominant-strategy incentive compatibi…

cs.GT2024

Mechanism Design for LLM Fine-tuning with Multiple Reward Models

Haoran Sun, Yurong Chen, Siwei Wang +3

Fine-tuning large language models (LLMs) to aggregate multiple preferences has attracted considerable research attention. With aggregation algorithms advancing, a potential economi…

cs.LG2024★ 1 cited

ALPINE: Unveiling the Planning Capability of Autoregressive Learning in Language Models

Siwei Wang, Yifei Shen, Shi Feng +3

Planning is a crucial element of both human intelligence and contemporary large language models (LLMs). In this paper, we initiate a theoretical investigation into the emergence of…

cs.GT2024

Automated Deterministic Auction Design with Objective Decomposition

Zhijian Duan, Haoran Sun, Yichong Xia +6

Identifying high-revenue mechanisms that are both dominant strategy incentive compatible (DSIC) and individually rational (IR) is a fundamental challenge in auction design. While t…

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