NeuCoReClass AD integrates multi-task self-supervised learning with neural transformations, boosting time series anomaly detection by 15% on benchmarks.

Aitor Sánchez-Ferrera, Usue Mori, Borja Calvo et al.

Agentic Web leverages AI agents for automated web interactions, enhancing user experience.

Yingxuan Yang, Mulei Ma, Yuxuan Huang et al.

Deep learning-based endoscopic depth estimation employs monocular and stereo networks, utilizing synthetic and real datasets, achieving sub-millimeter accuracy.

Ke Niu, Zeyun Liu, Xue Feng et al.

This paper analyzes provable in-context learning of Transformers on nonlinear L-Lipschitz regression, highlighting the impact of Lipschitz constant L on convergence dynamics.

Hongbo Li, Lingjie Duan, Yingbin Liang

Proposes a data-driven multi-task learning (MTL) framework that enhances rare conversion prediction (<1%) in online advertising, achieving 0.69% AUC lift offline and 2% CPA reduction online.

Yuval Dishi, Ophir Friedler, Yonatan Karni et al.

Introduces SLDAgent, an evolution-based AI system that autonomously discovers scaling laws surpassing human expertise, validated on SLDBench with high accuracy.

Haowei Lin, Haotian Ye, Wenzheng Feng et al.

Introduced VLQA, a large Vietnamese legal QA dataset, evaluated with BERT, RoBERTa, GPT-4, revealing strengths and limitations in legal reasoning.

Tan-Minh Nguyen, Hoang-Trung Nguyen, Trong-Khoi Dao et al.

FROSS leverages 2D scene graphs and Gaussian models for real-time 3D semantic scene graph generation, achieving significant speedup over traditional methods.

Hao-Yu Hou, Chun-Yi Lee, Motoharu Sonogashira et al.

DynamiX integrates dynamic role switching and relationship evolution to simulate large-scale social networks accurately.

Yanhui Sun, Wu Liu, Wentao Wang et al.

Integrating RLHF and Constitutional AI, achieving 20% safety improvement over baseline, with high preference alignment and robustness.

Haoran Lu, Luyang Fang, Ruidong Zhang et al.

MCIF benchmark evaluates crosslingual, multimodal instruction-following across 4 tasks, 3 modalities, 4 languages, revealing key challenges in current models.

Sara Papi, Maike Züfle, Marco Gaido et al.

RGA3 integrates STOM and SAM2 for object-centric video reasoning, achieving state-of-the-art results in video QA and segmentation benchmarks.

Haochen Wang, Qirui Chen, Cilin Yan et al.

Hierarchical multi-platform GUI benchmark MMBench-GUI evaluates content understanding, element grounding, task automation, and collaboration, introducing EQA for efficiency.

Xuehui Wang, Zhenyu Wu, JingJing Xie et al.

The paper proposes RLVR, counterfactual events, and multi-source data; Polymarket training reduced R1-14B Brier score from 0.214 to 0.197.

Sang-Woo Lee, Sohee Yang, Donghyun Kwak et al.

Proposes DINO-world, a latent space video predictor trained on 60M videos, outperforming SOTA in prediction and physics understanding.

Federico Baldassarre, Marc Szafraniec, Basile Terver et al.

TAGC automatically tunes gamma from image color statistics to enhance low-light photos without manual settings.

Ghufran Abualhail Alhamzawi, Ali Saeed Alfoudi, Ali Hakem Alsaeedi et al.

GEPA combines natural language reflection with Pareto-based evolutionary search, achieving 6% average improvement with 35x fewer samples than GRPO.

Lakshya A Agrawal, Shangyin Tan, Dilara Soylu et al.

Using GPT-4-based generative agents in large-scale social simulations, evaluating their Theory of Mind and biases, with implications for AI-driven social modeling.

Patrick Taillandier, Jean Daniel Zucker, Arnaud Grignard et al.

Proposes utility-based passage selection via distillation, reducing large model costs while improving complex QA performance.

Hengran Zhang, Keping Bi, Jiafeng Guo et al.

NEAT adapts only normalization layers, resolving VLM negation shifts with under 0.01% trainable parameters.

Haochen Han, Alex Jinpeng Wang, Fangming Liu et al.