BackTranslation2.0 is a linguistically motivated evaluation metric for sign language production that uses an agentic tool pipeline and LLM cross-referencing to score four dimensions and shows strong human correlation on a BSL dataset.
What's the Point? Spatial Grammar & Index Resolution for Sign Language Processing
1 Pith paper cite this work. Polarity classification is still indexing.
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abstract
Sign language models are predominantly trained with gloss-sequence or text supervision, thereby under-modeling non-lexical and productive constructions. One comparatively tractable instance is spatial indexing: pointing gestures that assign discourse entities to spatial loci for subsequent co-reference, which lexicon-centric objectives largely fail to capture. We present a targeted evaluation of indexing in Sign Language Recognition, showing that despite comprising 10-15% of signing content, indexing is poorly recovered. We introduce a framework for training and evaluating indexing experts, establishing a baseline for index-aware sign language modeling. Our approach decomposes spatial reference resolution into index detection and discourse entity linking. The resulting mention representations enable automatic annotation and non-lexical structure modeling, and serve as an auxiliary indexing expert that augments a frozen SLR model at inference time.
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cs.CV 1years
2026 1verdicts
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BackTranslation2.0 -- A Linguistically Motivated Metric to Assess Sign Language Production
BackTranslation2.0 is a linguistically motivated evaluation metric for sign language production that uses an agentic tool pipeline and LLM cross-referencing to score four dimensions and shows strong human correlation on a BSL dataset.