Proposes a claim-based cross-lingual biography enrichment framework leveraging non-English Wikipedia, achieving 75.17 F1 in claim extraction and 86.2% claim coverage.

Yifei Song, Ziyang Chen, Emil Sayilov et al.

JoyAI-Echo-1.5 enhances long-form audio-visual generation with memory and geometric control, improving consistency and visual quality.

Nan Duan, Haoyang Huang, Weiyang Jin et al.

FormuEvo employs LLM-guided evolutionary algorithms to optimize MIP formulations, achieving up to 5.5× speedup over baselines.

Haofeng Yuan, Jianing Peng, Jieyi Bi et al.

This work adapts Hugging Face's SmolVLA for industrial lightweight robots (UR10e), enabling edge-based real-time vision-language-action control.

Nils Mandischer, Noah Böckmann, Ludwig Holl et al.

Introduces LLM-SPICEMixer with IGEL, boosting circuit synthesis rewards by 8.4%.

Stefan Uhlich, Yağız Gençer, Andrea Bonetti et al.

Biomimetic layered skin with sensor integration achieves ~3° joint angle estimation; multimodal fusion improves accuracy.

Akihiro Miki, Shun Hasegawa, Yoshimoto Ribayashi et al.

Introduces causal leave-one-out measurement and closed-loop scheduling to improve evidence utilization and context allocation, scalable up to 32B parameters.

Peiyang Liu, Xi Wang, Di Liang et al.

Introduces Credal Large Language Models (CLLM) using LoRA ensembles to quantify uncertainty via credal sets, improving QA accuracy and hallucination detection.

Shireen Kudukkil Manchingal, Sofiia Nikolenko, Fabio Cuzzolin

Analyzes multiple fixed points in discrete hysteresis neural networks; introduces entropy to control basin size distribution.

Yuta Arai, Seigo Nakamura, Ryoga Nakamura et al.

EchoWM generates 720p video, environmental sound, music, and speech, supporting continuous navigation.

Songchun Zhang, Yaowei Li, Junhao Zhuang et al.

Using a capability-based framework, the study assesses how close generative world models are to being true simulators, highlighting gaps in physical laws and state feedback.

Tong Wang, Huan Deng, Mucheng Yang et al.

AquaFlow achieves efficient underwater streaming reconstruction with monocular Gaussian Splatting SLAM, reducing localization error by 13.2% and improving PSNR by 4.74 dB.

Yingxiang Xu, Kerui Ren, Wenqi Guo et al.

Proposed a lightweight audit method that successfully localized 192 causal break layers.

Taebong Kim, Youngsik Hong, Minsik Kim et al.

GSAR combines self-evolving data synthesis and goal-state anchoring to improve GUI agent training with over 90% accuracy in trajectory verification.

Long Zhang, Yuhan Chen, Chaoran Zhang et al.

DRY method adjusts logits at sampling to reduce loops by 47% and improve lexical diversity.

Philipp Emanuel Weidmann, Allen Roush, Judah Goldfeder et al.

XTC improves generation diversity by excluding top choices, achieving 15% Distinct-2 increase, 47% trigram repetition reduction.

Philipp Emanuel Weidmann, Allen Roush, Judah Goldfeder et al.

Introduced Physical Agentic AI framework to coordinate heterogeneous robot teams using LLMs, reducing error dispatch rates from 23%-29% to 0%.

Xinyuan Liu, Eren Sadikoglu, Riana Chatterjee et al.

NOVA combines 4F^2 VCT DRAM and dual-tier NMP architecture, boosting LLM inference by 4.5x.

In-Jun Jung, Jaeha Min, Joo-Young Kim

Kernel Token Contradiction (KTC) offers a fast, efficient LLM claim uncertainty quantification, achieving 8.2x speedup.

Jérémie Dentan, Alexi Canesse, Mahammed El Sharkawy et al.

Study on block encoding conversion of quantum states, revealing fundamental conversion limits.

Manaki Arihara, Mio Murao