collaborators

6 papers

cs.CL2026

Evaluation Revisited: A Taxonomy of Evaluation Concerns in Natural Language Processing

Ruchira Dhar, Anders Søgaard

Recent advances in large language models (LLMs) have prompted a growing body of work that questions the methodology of prevailing evaluation practices. However, many such critiques…

cs.CL2026

Evaluating Adjective-Noun Compositionality in LLMs: Functional vs Representational Perspectives

Ruchira Dhar, Qiwei Peng, Anders Søgaard

Compositionality is considered central to language abilities. As performant language systems, how do large language models (LLMs) do on compositional tasks? We evaluate adjective-n…

cs.CL2025

Understanding Subword Compositionality of Large Language Models

Qiwei Peng, Yekun Chai, Anders Søgaard

Large language models (LLMs) take sequences of subwords as input, requiring them to effective compose subword representations into meaningful word-level representations. In this pa…

cs.CL2025

Debiasing Multilingual LLMs in Cross-lingual Latent Space

Qiwei Peng, Guimin Hu, Yekun Chai +1

Debiasing techniques such as SentDebias aim to reduce bias in large language models (LLMs). Previous studies have evaluated their cross-lingual transferability by directly applying…

cs.CL2025

SemEval-2025 Task 7: Multilingual and Crosslingual Fact-Checked Claim Retrieval

Qiwei Peng, Robert Moro, Michal Gregor +7

The rapid spread of online disinformation presents a global challenge, and machine learning has been widely explored as a potential solution. However, multilingual settings and low…

cs.CL2025

Revisiting the Othello World Model Hypothesis

Yifei Yuan, Anders Søgaard

Li et al. (2023) used the Othello board game as a test case for the ability of GPT-2 to induce world models, and were followed up by Nanda et al. (2023b). We briefly discuss the or…