StrideDiffusion accelerates time-series generation with spectral-aware sampling, reducing evaluations to 14-66.

Du Yin, Estrid He, Julián Jerónimo Bañuelos et al.

Lumo-2 leverages latent space reasoning and multi-modal alignment to enhance predictive control and generalization in robotic learning.

Peijun Tang, Shangjin Xie, Baifu Huang et al.

ProgramTab leverages Python-guided code generation to enhance large table reasoning, outperforming baselines on WikiTQ and TabFact.

Pei Guo, Enjie Liu, Yunzhi Tan et al.

DynEval enhances T2I model evaluation by dynamically assessing text-image alignment and quality using GenDB and DynEvalInstruct datasets.

Shyam Marjit, Dheeraj Baiju, Anuj Shikarkhane et al.

RepTran combines neuron-aware localization with Differential Evolution, repairing 74.7% of targeted faults across 18 ViT benchmarks.

Yuta Ishimoto, Paolo Arcaini, Fuyuki Ishikawa et al.

Proposes environment-augmented self-evolving medical agents, enhancing autonomy and reliability in clinical settings.

Chunzheng Zhu, Lei Tian, Bohan Tan et al.

Study on inference economics of cloud vs. on-premise LLMs: Claude Opus vs. GLM.

Sheng-Wei Peng, Yi-Hsun Lin, Yi-Pei Lee

Proposed QFES task and QFESum dataset; combined RAT and SHC frameworks outperform baselines in event-focused summarization.

Chenyu Hu, Bang Wang

MusicMark embeds watermarks during generation, significantly enhancing robustness against neural codec re-synthesis attacks.

Seohwan Yun, Jeeyoung Yun, Yongjin Kim et al.

Study finds PA replacement metrics are robust at N=1 but inflate at N>1; recommends PR metrics.

Zongye Lyu

Quantized LLM reliability varies with bitwidth; 4-bit models offer the best efficiency-reliability trade-off.

Sirine Ayadi, Sándor Daróczi, Stephan Günnemann et al.

Introduced QIMG-7 benchmark and SATR method to enhance multimodal RAG reliability in polluted settings, improving balanced score by 11.7 points.

Saadeldine Eletter, Owais Aijaz, Preslav Nakov

Unlocking parallelism in autoregressive models with Progressive Tree Drafting, achieving up to 2x decoding speedup.

Zipeng Gao, Zhi Zheng, Qingrong Xia et al.

Introduces E-P-R framework to diagnose how AI agents consume conflicting memory, revealing the 'compliance trap' phenomenon.

Yixiong Chen, Xinyi Bai, Alan Yuille

Agentic-DPO leverages expert trajectories with preference contrast for offline policy optimization, doubling accuracy from 21.7% to 41.4%.

Yixiong Chen, Alan Yuille

This paper derives exponential approximation bounds for analytic functions using ReLU networks, highlighting depth's dominance over width in the (N,L) parameterization.

Yanming Lai, Defeng Sun, Yang Wang

SynthDocBench uses synthetic long documents with controlled factors to reveal three key failure modes of vision-language models in long-context understanding.

Abhigya Verma, Khyati Mahajan, Amit Kumar Saha et al.

ABot-N1 employs a dual slow-fast architecture combining Chain-of-Thought reasoning with pixel anchors, enabling multi-task general visual navigation with high interpretability.

Ruiyan Gong, Yingnan Guo, Junjun Hu et al.

This paper improves convergence rates of single-loop AID and ITD for bilevel optimization from O(κ^6/K) to O(κ^5/K) and error from κ^3 to κ^2, using decoupled norm analysis.

Yubo Zhou, Jun Shu, Luo Luo et al.

This study evaluates multilingual keyword and content variant injection attacks on LLM relevance judgments, revealing persistent inflation and evasion of defenses.

Nguyen Khoi Vo, Duy Duong Tuong, Oleg Zendel et al.