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Sungchul Kim

21 papers hereh-index 10447 citations32 works total

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

author position
  • middle author20

Across the 20 of 21 papers where every author was matched, so the position is known.

fields
  • cs.CL10
  • cs.AI5
  • cs.LG2
  • cs.CV1
  • cs.DS1
  • cs.HC1
same name
  • Sungchul Kim — 28 papers, h 25
  • Sungchul Kim — 20 papers, h 9
  • Sungchul Kim — 6 papers, h 4
  • Sungchul Kim — 1 paper, h 3
  • Sungchul Kim — 1 paper, h 5

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
20242026
most citedPersonalization of Large Language Models: A Survey

15 citations · 29 across the 20 of their papers we have counts for

collaborators
Showing 2026Show all

4 papers · 1 filter

cs.AI2026

Failure Is the Mother of Success: Recovering Supervision with Grounding Hindsight

Sheldon Yu, Tong Yu, Nikki Lijing Kuang +6

When every rollout for a problem fails, GRPO receives neither a successful exemplar nor a nonzero group-relative advantage, so it learns nothing from exactly the problems it most n…

cs.AI2026

Agent2UCB: Agentic System for Generative Engine Optimization

Sheldon Yu, Rui Wang, Tong Yu +4

Large language model driven search engines such as Google AI Overviews and Perplexity have created new opportunities for Generative Engine Optimization (GEO) the practice of refini…

cs.AI2026

Can We Break LLMs Out of Self-Loops? Fine-Grained Reasoning Control with Activation Steering

Sheldon Yu, Tong Yu, Xunyi Jiang +6

Extended reasoning has become standard for frontier Large Language Models (LLMs), yet the trajectories these models produce remain largely uncontrollable. Existing methods for shap…

cs.CL2026

Reasoning-Based Personalized Generation for Users with Sparse Data

Bo Ni, Branislav Kveton, Samyadeep Basu +14

Large Language Model (LLM) personalization holds great promise for tailoring responses by leveraging personal context and history. However, real-world users usually possess sparse…

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