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researcher

Qianli Wang

Technische Universität Berlin

20 papers hereh-index 697 citations23 works total

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

author position
  • first author10
  • middle author9

Across the 19 of 20 papers where every author was matched, so the position is known.

fields
  • cs.CL19
  • cs.AI1
affiliations
  • Technische Universität Berlin
Homepage
same name
  • Qianli Wang — 2 papers, h 9
  • Qianli Wang — 2 papers, h 2
  • Qianli Wang — 1 paper

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
collaborators
Showing 2025Show all

4 papers · 1 filter

cs.CL2025

Multilingual Datasets for Custom Input Extraction and Explanation Requests Parsing in Conversational XAI Systems

Qianli Wang, Tatiana Anikina, Nils Feldhus +6

Conversational explainable artificial intelligence (ConvXAI) systems based on large language models (LLMs) have garnered considerable attention for their ability to enhance user co…

cs.CL2025

Truth or Twist? Optimal Model Selection for Reliable Label Flipping Evaluation in LLM-based Counterfactuals

Qianli Wang, Van Bach Nguyen, Nils Feldhus +4

Counterfactual examples are widely employed to enhance the performance and robustness of large language models (LLMs) through counterfactual data augmentation (CDA). However, the s…

cs.CL2025

Through a Compressed Lens: Investigating The Impact of Quantization on Factual Knowledge Recall

Qianli Wang, Mingyang Wang, Nils Feldhus +5

Quantization methods are widely used to accelerate inference and streamline the deployment of large language models (LLMs). Although quantization's effects on various LLM capabilit…

cs.CL2025

FitCF: A Framework for Automatic Feature Importance-guided Counterfactual Example Generation

Qianli Wang, Nils Feldhus, Simon Ostermann +3

Counterfactual examples are widely used in natural language processing (NLP) as valuable data to improve models, and in explainable artificial intelligence (XAI) to understand mode…

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