SLT
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Related Articles from SNS
SLU-2K: A Question-Based Benchmark for Semantic Evaluation of Sign Language Translation
arXiv:2606.03788v1 Announce Type: new Abstract: Sign Language Translation (SLT) is typically evaluated with surface-form metrics such as BLEU and ROUGE, which reward lexical overlap but do not directly measure whether a translation preserves the meaning of the source sign sequence. This is in contrast with the final objective of integrating SLT in assistive technology. In this work, we shift the focus from Sign Language Translation (SLT) to Sign Language Understanding (SLU), with particular...
Grounding or Guessing? Visual Signals for Detecting Hallucinations in Sign Language Translation
arXiv:2510.18439v3 Announce Type: replace Abstract: Hallucination, where models generate fluent text unsupported by visual evidence, remains a major flaw in vision-language models and is particularly critical in sign language translation (SLT). In SLT, meaning depends on precise grounding in video, and gloss-free models are especially vulnerable because they map continuous signer movements directly into natural language without intermediate gloss supervision that serves as alignment. We...
Target-Side Paraphrase Augmentation for Sign Language Translation with Large Language Models
arXiv:2605.31393v1 Announce Type: new Abstract: Sign language translation (SLT) remains constrained by limited paired sign-video/text corpora and heavy-tailed target vocabularies. We study target-side augmentation in which GPT-4o generates controlled paraphrase variants of reference sentences while the sign input remains unchanged. A Signformer-style pose-based Transformer is trained under a two-stage schedule: pre-training on the augmented corpus followed by fine-tuning on the original...
Two rupees for cancer: Inside India's smokeless tobacco epidemic that no one is stopping
None of us are strangers to the fact that nicotine is bad. In India you cannot even go to the movies without a tobacco awareness ad playing. Your cigarette boxes and tobacco sachets have the most horrifying graphics meant to dissuade you from buying them.
Structural Decoupling: A Scaffold-Flow Theory of Generalization and Alignment
arXiv:2506.20699v2 Announce Type: replace Abstract: Learning in non-stationary and multi-context environments requires more than ordinary within-task generalization. A system must also discover which contexts exist, route inputs to the correct context, preserve old contexts, and revise the context library when the environment changes. This paper presents Structural Learning Theory (StrLT) as a framework of filling this missing structural gap.