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conference-on-computational-natural-language-learning

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Use when targeting Conference on Computational Natural Language Learning (CoNLL) or deciding whether a computer-science manuscript fits this venue. Encodes conference fit, framing, evidence bar, submission-cycle checks, rebuttal posture, and desk-reject risks for NLP learning.

Computer-Science-Conference-Skills/skills/conference-on-computational-natural-language-learning/SKILL.md

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# Conference on Computational Natural Language Learning (CoNLL)

## Conference positioning

Conference on Computational Natural Language Learning (CoNLL) is a top computer-science conference venue for machine learning for language, structured prediction, shared tasks, semantics, and multilingual modeling. It rewards an NLP learning paper with method novelty and careful comparison to strong learning baselines. Treat this skill as a **fit / venue-selection / re-framing** tool for conference submission strategy, not as a substitute for the current year's CFP, author kit, ethics policy, or submission portal.

Because CS conferences change deadlines, templates, page limits, review workflow, artifact rules, AI-use policy, and rebuttal formats every cycle, always verify the live official instructions before making a submission-ready recommendation. Start from the official source anchor recorded for this venue in `../../resources/conference-roster.md` and `../../resources/official-source-map.md`.

## When to trigger

- The author names CoNLL / Conference on Computational Natural Language Learning as the target venue.
- A manuscript in machine learning for language needs a conference-fit read before being formatted or submitted.
- The paper must be re-framed from journal style or arXiv style into a selective CS conference narrative.
- The author needs an evidence-gap, anonymity, artifact, rebuttal, or re-routing diagnosis for this venue.
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