Proposes a dual-objective surrogate model guiding neural ensemble search, improving accuracy and diversity simultaneously.

Alexandr Udeneev, Petr Babkin, Oleg Bakhteev

Proposes 'horizon residual' metric, comparing full-task success with short-stage predictions to diagnose long-horizon failures.

Chao Peng, Zhiheng Lyu, Peijie Dong et al.

DuPLeR employs dual-path structural reasoning combined with multimodal LLM priors to improve few-shot knowledge graph completion, achieving significant performance gains.

Jinlan Liu, Zhiying Tu, Yongchao Xing et al.

DASH integrates cross-domain histories and thinking traces, enhancing decision-aware user simulation for online advertising.

Zipeng Chen, Jiaer Zheng, Xiangyang Xu et al.

StructureGS integrates structure-aware guidance with Gaussian Splatting for high-quality articulated object reconstruction, using OBB constraints to improve part boundaries and motion accuracy.

Gahye Lee, Gyoonseo Kim, Wonjong Jang et al.

Metis integrates native memory into foundation models, using a parametric memory state and self-supervised training to enhance long-term reasoning.

Zeyu Zhang, Ziliang Guo, Yihang Sun et al.

MPEcho extends SongEcho with a phoneme encoder and length regulator, reducing phoneme error rate to 18.65%.

Wei-Jaw Lee, Hsuan-Yu Yeh, Ting-Yi Hu et al.

This review summarizes 34 papers on LLM-based literature retrieval and screening, emphasizing architectures and evaluation metrics.

Eleni Adamidi, Serafeim Chatzopoulos, Thanasis Vergoulis

This paper systematically analyzes lossy verification in speculative decoding, classifying into truncation and collaborative methods, revealing their mechanisms, pitfalls, and control principles.

Tianyu Wang, Yuxuan Zhou, Wenbin Wang et al.

CineWeaver uses inference-time positional encoding, attention, routing, and memory to generate long, reference-controlled multi-shot videos without retraining; supplied text reports no numeric metrics.

Yuyang Huang, Yabo Chen, Wenrui Dai et al.

Introduced MO-SB-NESR method to improve physical consistency in multi-output symbolic regression.

Manuel Rodriguez

Gradient, evolutionary, and one-shot NAS methods improve traffic prediction model automation, achieving up to 8% RMSE reduction.

Truong Giang Vu, Li Yang, Richard W. Pazzi

Introduces MultivationBench, a benchmark based on Maslow and Reiss models, to evaluate multimodal sequential motivation reasoning; models perform poorly.

Kawai Chung, Chunkit Chan, Yauwai Yim et al.

StrataCL enables user-buffer direct communication via registration-on-allocation, boosting bandwidth by 1.6x and inference throughput by 1.9x.

Tiancheng Hu, Jin Qin, Yuzheng Wang et al.

Introduces cross-branch semantic steering to test if understanding and generation share a unified semantic space; transfer from understanding to generation is effective, reverse is limited.

Yu Wang, Sharon Li

MoSAIC achieves part-local motion style transfer using aligned intervention supervision, reducing errors and enhancing response.

Nazanin Amini, Kevin Desai

OpenMarket releases a millisecond-level paired dataset of Polymarket and Binance BTC data, showing no significant out-of-sample prediction advantage.

Gregory Young

Proposes a four-layer system framework and trustworthiness hierarchy, defining sustained safe success for embodied AI deployment.

Xinyu Yang, Tianxing Chen, Honghao Su et al.

MODUS is a decoder-only multimodal model supporting arbitrary input-output combinations, enabling multi-task and cross-modal applications.

Mingqiao Ye, Zhaochong An, Zhitong Gao et al.

Meshy T2 uses flow matching for fast native mesh generation, completing image-to-mesh conversion in 6 seconds with leading geometric fidelity.

Jiale Xu, Rendong Liang, Yuhao Long et al.