WSLP-2026 hosted three shared tasks on Indian Sign Language: sentence-level translation from video or pose into English (SLT), isolated recognition over a large one-shot vocabulary (ISLR), and word/sign presence prediction in continuous sentence video (WPP). Shared tasks were hosted on Codabench. Twenty-three teams registered for translation and five submitted; thirteen registered for WPP and five submitted; twenty-two registered for recognition and nine submitted. On the lexical tracks, the systems that report usable official scores treat the problem as retrieval or temporal alignment within a pose-embedding space, often with an external exemplar bank. Translation submissions almost uniformly map pose sequences into a pretrained T5 decoder. They obtain fluent English more readily than scores that can be trusted at the current accuracy level: official BLEU can sit at zero, while chrF remains small and sensitive to output length. The edition shows that ISL can be measured by automatic evaluation metrics, but that current scores still say more about retrieval recipes and decoder fluency than about signed grammar. A later edition should mark pose-tracker failures and place native-signer judgments alongside BLEU and chrF.

We organized the Second Workshop on Sign Language Processing (WSLP-2026), co-located with EMNLP 2026 in Budapest, Hungary, on 29 October 2026. The workshop continues the programme begun at WSLP 2025: to give under-resourced sign languages a dedicated computational venue, and to treat sign language processing as a set of related problems rather than a single translation benchmark. We received 40 submissions and accepted 22 papers. This overview concentrates on the 15 accepted main-workshop research papers. Those papers cover new corpora for Catalan, Uruguayan, Icelandic, Russian, and Bangla sign languages; compact gloss-free translation; isolated recognition and fingerspelling; and a cluster of diagnostic studies on what actually transfers when a model is moved from a high-resource sign language to a low-resource one. As part of the workshop, we hosted three shared tasks on Indian Sign Language, namely translation, isolated recognition, and word/sign presence prediction, which together attracted 58 registered teams, and 19 teams actively participated. The open questions have shifted from whether sign languages can be modeled at all to how annotation budgets should be allocated, which parts of a pretrained checkpoint are worth transferring, and how to evaluate systems when automatic metrics remain only weakly correlated with grammatical correctness.