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Tianlong Gu

5 papers hereh-index 321 citations13 works total

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

author position
  • middle author4
  • last author1

Across the 5 of 5 papers where every author was matched, so the position is known.

fields
  • cs.CL4
  • cs.LG1
same name
  • Tianlong Gu — 2 papers, h 4
  • Tianlong Gu — 2 papers, h 4
  • Tianlong Gu — 1 paper
  • Tianlong Gu — 1 paper, h 2
  • Tianlong Gu — 1 paper, h 2
  • Tianlong Gu — 1 paper, 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
20242026
most citedLearning from Mistakes: Self-correct Adversarial Training for Chinese Unnatural Text Correction

1 citations · 1 across the 5 of their papers we have counts for

collaborators
Showing cs.CLShow all

4 papers · 1 filter

cs.CL2026

Where Detectors Fail: Closing the Tail-Domain Gap with Expert-Guided Mutual Distillation

Xuan Feng, Guihong Liu, Tianlong Gu +5

Multimodal fake news detectors often generalize poorly across domains because they learn to trust unreliable evidence: domain-specific shortcuts amplified by imbalanced data and se…

cs.CL2026

Self-Debias: Self-correcting for Debiasing Large Language Models

Xuan Feng, Shuai Zhao, Luwei Xiao +2

Although Large Language Models (LLMs) demonstrate remarkable reasoning capabilities, inherent social biases often cascade throughout the Chain-of-Thought (CoT) process, leading to…

cs.CL2025

C2PO: Diagnosing and Disentangling Bias Shortcuts in LLMs

Xuan Feng, Bo An, Tianlong Gu +4

Bias in Large Language Models (LLMs) poses significant risks to trustworthiness, manifesting primarily as stereotypical biases (e.g., gender or racial stereotypes) and structural b…

cs.CL2024★ 1 cited

Learning from Mistakes: Self-correct Adversarial Training for Chinese Unnatural Text Correction

Xuan Feng, Tianlong Gu, Xiaoli Liu +1

Unnatural text correction aims to automatically detect and correct spelling errors or adversarial perturbation errors in sentences. Existing methods typically rely on fine-tuning o…

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