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From the 1 of 21 linked papers with an AI index.

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20242026
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21 papers

math.CA2026

Chebyshev polynomials on a Jordan arc

Benedikt Buchecker, Benjamin Eichinger, Olof Rubin +1

We describe the asymptotics of Chebyshev polynomials on an analytic Jordan arc in the plane. This gives an affirmative answer to a conjecture of Christiansen-Simon-Zinchenko, based…

cs.AI2026

ARAC: Benchmarking Auto-Research's Alignment and Completeness on End-to-End Researchs

Jiale Cui, Yueyao Yuan, Kaixi Zhong +3

The rapid advancement of Auto-Research has surfaced a fundamental evaluation challenge: how can we measure the alignment, logical coherence, and evolutionary completeness of its re…

cs.IR2026

CogRec: Structure-Cognitive Fast-and-Slow Reasoning for Generative Recommendation

Xiang Liu, Jingsong Su, Shuqi Zhao +7

Semantic-ID-based generative recommendation represents each item as a hierarchical discrete token sequence and reformulates next-item prediction as constrained sequence generation.…

cs.IR2026

Can We Steer the Black-Box? Towards Controllability-Centric Evaluation of Recommender Systems with Collaborative Agents

Jiwen Zhou, Xiang Liu, Mingming Li +5

The paper introduces CtrlBench-Rec, a collaborative multi‑agent framework for evaluating how controllable recommender systems are, focusing on tasks such as target content discover…

cs.CV2026

Towards Memory-Efficient Autoregressive Video Generation via Instance-Specific Parametric Absorption

Xiaomeng Fu, Jia Li, Yiming Hu +5

Autoregressive (AR) streaming models have emerged as a powerful paradigm for long video generation. However, the linearly growing Key-Value (KV) cache poses a significant bottlenec…

cs.IR2026

HoloRec: Holistic Encoding and Interleaved Reasoning for Generative Recommendation

Shuqi Zhao, Jingsong Su, Xiang Liu +9

Generative recommendation models that formulate the task as sequence generation overcome the objective fragmentation problem of traditional cascade architectures, yet existing appr…