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Wei Xu

14 papers hereh-index 5134 citations18 works total

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

author position
  • middle author9
  • last author5

Across the 14 of 14 papers where every author was matched, so the position is known.

fields
  • cs.CL9
  • cs.CV2
  • cs.CR1
  • cs.HC1
  • cs.LG1
same name
  • Wei Xu — 54 papers, h 63
  • Wei Xu — 43 papers, h 31
  • Wei Xu — 41 papers, h 44
  • Wei Xu — 37 papers, h 45
  • Wei Xu — 30 papers, h 44
  • Wei Xu — 19 papers, h 10

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 citedNEO-BENCH: Evaluating Robustness of Large Language Models with Neologisms

7 citations · 12 across the 14 of their papers we have counts for

collaborators
Showing 2024Show all

4 papers · 1 filter

cs.CL2024

Granular Privacy Control for Geolocation with Vision Language Models

Ethan Mendes, Yang Chen, James Hays +3

Vision Language Models (VLMs) are rapidly advancing in their capability to answer information-seeking questions. As these models are widely deployed in consumer applications, they…

cs.CL2024

Stanceosaurus 2.0: Classifying Stance Towards Russian and Spanish Misinformation

Anton Lavrouk, Ian Ligon, Tarek Naous +3

The Stanceosaurus corpus (Zheng et al., 2022) was designed to provide high-quality, annotated, 5-way stance data extracted from Twitter, suitable for analyzing cross-cultural and c…

cs.CL2024

Constrained Decoding for Cross-lingual Label Projection

Duong Minh Le, Yang Chen, Alan Ritter +1

Zero-shot cross-lingual transfer utilizing multilingual LLMs has become a popular learning paradigm for low-resource languages with no labeled training data. However, for NLP tasks…

cs.CL2024★ 7 cited

NEO-BENCH: Evaluating Robustness of Large Language Models with Neologisms

Jonathan Zheng, Alan Ritter, Wei Xu

The performance of Large Language Models (LLMs) degrades from the temporal drift between data used for model training and newer text seen during inference. One understudied avenue…

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