Pingjun Hong — accepted AI-conference papers

2025

Evaluating Large Language Models for Cross-Lingual Retrieval

Longfei Zuo, Pingjun Hong, Oliver Kraus, Barbara Plank, Robert Litschko

EMNLP 2025

Multi-stage information retrieval (IR) has become a widely-adopted paradigm in search. While Large Language Models (LLMs) have been extensively evaluated as second-stage reranking models for monolingual IR, a systematic large-scale comparison is still lacking for cross-lingual IR (CLIR). Moreover, w

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2025

LiTEx: A Linguistic Taxonomy of Explanations for Understanding Within-Label Variation in Natural Language Inference

Pingjun Hong, Beiduo Chen, Siyao Peng, Marie-Catherine de Marneffe, Barbara Plank

EMNLP 2025

There is increasing evidence of Human Label Variation (HLV) in Natural Language Inference (NLI), where annotators assign different labels to the same premise-hypothesis pair. However, *within-label variation* — cases where annotators agree on the same label but provide divergent reasoning — poses an

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