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Showing papers from Snap Inc. Show all papers

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NeurIPS 2026Universidad Rey Juan CarlosRobloxThe University of Hong KongSnap Inc.Universidad Rey Juan Carlos. VATVideo generation

Coarse-to-Real: Generative Rendering for Populated Dynamic Scenes

C2R generates realistic, temporally consistent urban crowd videos from coarse 3D simulations via a neural renderer guided by text and a synthetic-real domain-hedging strategy.

Gonzalo Gomez-Nogales, Yicong Hong, Chongjian GE, Peiye Zhuang and 3 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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AI panel: 9 of 20 reviewers recommend it
lenient 5/5
medium 4/10
strict 0/5
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NeurIPS 2026U CambridgeIsomorphic labsGoogle DeepMindImperial College LondonELLIS Institute Tübingen, MPI-ISReward models & LLM-as-a-judge

Rethinking Rubric Generation for Improving LLM Judge and Reward Modeling for Open-ended Tasks

RRD refines rubrics via recursive decomposition and filtering to improve LLM judge accuracy and reinforcement training rewards on open-ended tasks.

William Shen, Xinchi Qiu, Chenxi Whitehouse, Lisa Alazraki and 5 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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17/20 AI panelreviewers recommend it

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AI panel: 17 of 20 reviewers recommend it
lenient 5/5
medium 10/10
strict 2/5