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NeurIPS 2026U WarwickSpotifyU TartuSpotify & University CollegeRecommender systems

Causal Representation Learning for Generalisable Recommendation

A causal disentanglement objective improves recommender out-of-distribution generalization by isolating invariant causal components, yielding substantial online engagement gains in Spotify A/B tests.

Yorgos Felekis, Michael O'Riordan, Oriol Corcoll Andreu, Ciarán Gilligan-Lee

Paris Poster Session 4, Thu, Dec 10, 5:30 PM–7:30 PM, Paris Poster Hall · Published 2026

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AI panel: 17 of 20 reviewers recommend it
lenient 5/5
medium 9/10
strict 3/5
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NeurIPS 2026King's College London, UnivKing's College LondonU TartuStanfordLLM evaluation & benchmarks

CAREBench: Evaluating LLMs' Emotion Understanding by Assessing Cognitive Appraisal Reasoning

CAREBench evaluates LLM emotion understanding via appraisal reasoning chains, finding stronger models surpass humans on some tasks but lack reasoning and positive emotion recognition.

ZHAOYUE SUN, Hainiu Xu, Andero Uusberg, James Gross and 2 more

Paris Poster Session 6, Fri, Dec 11, 2:30 PM–4:30 PM, Paris Poster Hall · Published 2026

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15/20 AI panelreviewers recommend it

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AI panel: 15 of 20 reviewers recommend it
lenient 5/5
medium 8/10
strict 2/5