Neuro-Relational Programs (NRPs) unify relational query languages with neural computation by extending Datalog rules to process embedded vector facts, enabling expressive, trainable relational reasoning.

Arie Soeteman, Balder ten Cate, Maurice Funk et al.

Proposes Arbor framework with Hypothesis-Tree Refinement for autonomous research, achieving over 2.5× improvement across tasks.

Jiajie Jin, Yuyang Hu, Kai Qiu et al.

StreamMUSE achieves real-time music accompaniment generation by optimizing synchronization performance.

Bowen Zheng, Andrew H. Yang, Jiaqi Ruan et al.

BACON improves multimodal KV-cache compression by 7.5% on average, up to 30.9% under aggressive budgets.

Tianhao Chen, Yuheng Wu, Kelu Yao et al.

This paper introduces two calibration strategies—post-hoc calibration and in-training adaptation—for Bayesian prediction under label shift, validated through synthetic experiments.

Seungjin Choi

SG-PVR model enhances text-to-video generation semantic alignment using spatio-temporal scene graphs.

Hyomin Kim, Junghye Kim, Joanie Hayoun Chung et al.

UniReason-Med enhances 2D-to-3D medical VQA via a shared reasoning interface.

Mengzhuo Chen, Yan Shu, Chi Liu et al.

RLCSD combines contrastive learning with reinforcement on-policy self-distillation, effectively mitigating style drift and improving reasoning model performance.

Leyi Pan, Shuchang Tao, Yunpeng Zhai et al.

Orchestra-o1 framework enhances multimodal agent collaboration, achieving 10.3% accuracy improvement on the OmniGAIA benchmark.

Fan Zhang, Vireo Zhang, Shengju Qian et al.

Proposes a target-wise model adequacy test to evaluate spectral uncertainty intervals in lattice QCD, validated via empirical coverage and stress tests.

Haozheng Li

Proposed a spectral knowledge transfer framework with two-step embedding, improving low-dimensional representations in rare disease EHRs.

Feiqing Huang, Zongqi Xia, Rong Ma et al.

Proposes GLACIER, a multimodal foundation model using contrastive learning and Finsler geometry for molecular property prediction, achieving SOTA results.

Emily Nguyen, Yongchan Hong, Harsh Toshniwal et al.

Next Forcing introduces multi-chunk prediction to accelerate training and improve accuracy in high-frame-rate video generation, achieving 94.1% success on RoboTwin.

Gangwei Xu, Qihang Zhang, Jiaming Zhou et al.

AMNet introduces modality-agnostic inference for low-light video enhancement, maintaining high performance even with missing auxiliary modalities, outperforming state-of-the-art methods.

Hangfeng Liang, Yutao Hu, Yanhan Hu et al.

EEVEE framework employs a router-conditioned prompt set with co-evolution to enhance LLM robustness across heterogeneous task streams, improving scores by 10.38-24.32 points.

Weixian Xu, Shilong Liu, Mengdi Wang

Introduces Data2Story, a multi-agent framework transforming data into verifiable multimodal stories with evidence traceability and interactive content.

Kevin Qinghong Lin, Batu EI, Yuhong Shi et al.

This paper introduces feedback alignment in self-distillation, comparing three feedback types; structure-aligned critique outperforms others with +16.11% accuracy.

Semih Kara, Oğuzhan Ersoy

Unified analysis of GP-UCB and DEC in RKHS bandits via MAIR framework, revealing their fundamental differences and advantages.

Yunbei Xu

Piper decouples training strategies via IR, enabling flexible multi-strategy scheduling with performance parity and efficiency gains.

Megan Frisella, Shubham Tiwari, Andy Ruan et al.

COGENT integrates Graph Neural Networks with Neural ODEs for continuous long-term physical forecasting on irregular meshes, outperforming traditional autoregressive models.

Zesheng Liu, Maryam Rahnemoonfar