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researcher

Jian Li

7 papers hereh-index 385 citations6 works total

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

author position
  • middle author5
  • last author1

Across the 6 of 7 papers where every author was matched, so the position is known.

fields
  • cs.CL5
  • cs.AI1
  • cs.LG1
same name
  • Jian Li — 53 papers, h 17
  • Jian Li — 50 papers, h 28
  • Jian Li — 47 papers, h 19
  • Jian Li — 33 papers, h 13
  • Jian Li — 30 papers, h 31
  • Jian Li — 19 papers, h 12

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 citedAre Large Language Models Good Prompt Optimizers?

1 citations · 2 across the 6 of their papers we have counts for

collaborators
Showing 2026Show all

4 papers · 1 filter

cs.AI2026

When Reasoning Traces Conflict with Evidence: How Answer Configuration Shapes Evidence Following

Shaoang Li, Yanhang Shi, Jian Li

A reasoning trace retained at answer time plays two roles: it can raise accuracy, and it can compete with the current evidence when the two disagree. We disentangle these roles by…

cs.LG2026

Dual-Adversarial Safety Alignment: Cultivating Intrinsic Threat Comprehension in LRMs

Hongli Shen, Shaopeng Fu, Qinbo Zhang +2

Large reasoning models (LRMs) achieve remarkable success on complex tasks but remain vulnerable to harmful prompts that induce unsafe outputs. Recent methods align LRMs using direc…

cs.CL2026

Context-Fidelity Boosting: Enhancing Faithful Generation through Watermark-Inspired Decoding

Weixu Zhang, Fanghua Ye, Qiang Gao +7

Large language models (LLMs) often produce content that contradicts or overlooks information provided in the input context, a phenomenon known as faithfulness hallucination. In thi…

cs.CL2026

Learning Evidence Highlighting for Frozen LLMs

Shaoang Li, Yanhang Shi, Yufei Li +10

Large Language Models (LLMs) can reason well, yet often miss decisive evidence when it is buried in long, noisy contexts. We introduce HiLight, an Evidence Emphasis framework that…

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