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20242026
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cs.CL2026

Controlling Implicit Shortcut Reliance in L2 Spoken English Auto-markers

Shilin Gao, Mark J. F. Gales, Kate M. Knill

Increasingly, speech and language processing tasks take either audio or text directly rather than extracting features from these as the input to the classifier or regressor. Often…

cs.CL2026

To Be Multimodal or Not to Be: Query-Adaptive Audio-Visual Person Retrieval via Active Modality Detection

Erfan Loweimi, Mengjie Qian, Kate Knill +7

When retrieving a person from a video archive by voice and face, should the system be multimodal or not? In real-world broadcast archives, unlike curated benchmarks, a target may b…

cs.CL2026

Who can we trust? LLM-as-a-jury for Comparative Assessment

Mengjie Qian, Guangzhi Sun, Mark J. F. Gales +1

Large language models (LLMs) are increasingly applied as automatic evaluators for natural language generation assessment often using pairwise comparative judgements. Existing appro…

cs.CL2026

Dual-Space Knowledge Distillation with Key-Query Matching for Large Language Models with Vocabulary Mismatch

Stella Eva Tsiapali, Cong-Thanh Do, Kate Knill

Large language models (LLMs) achieve state-of-the-art (SOTA) performance across language tasks, but are costly to deploy due to their size and resource demands. Knowledge Distillat…

cs.CL2026

The Impact of Editorial Intervention on Detecting Native Language Traces

Ahmet Yavuz Uluslu, Mark Gales, Kate Knill +1

Native Language Identification (NLI) is the task of determining an author's native language (L1) from their non-native writing. With the advent of human-AI co-authorship, learner t…

cs.CL2026

Towards Self-Referential Analytic Assessment: A Profile-Based Approach to L2 Writing Evaluation with LLMs

Stefano Bannò, Kate Knill, Mark Gales

Automated essay scoring (AES) research often relies on rank-based correlation metrics to validate analytic assessment. However, such metrics obscure both intrinsic intercorrelation…