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Papers for March 26, 2026

10 papers found

Arthur Jacot 3/25/2026 arxiv

machine learning

We introduce the Multilevel Euler-Maruyama (ML-EM) method compute solutions of SDEs and ODEs using a range of approximators $f^1,\dots,f^k$ to the drift $f$ with increasing accuracy and computational cost, only requiring a few evaluations of the most accurate $f^k$ and many evaluations of the less c...

Keywords: diffusion models, Euler-Maruyama, multilevel methods, SDE, UNet, HTMC, sampling, polynomial speedup

Pengxuan Yang, Yupeng Zheng, Deheng Qian, Zebin Xing, Qichao Zhang, Linbo Wang, Yichen Zhang, Shaoyu Guo, Zhongpu Xia, Qiang Chen, Junyu Han, Lingyun Xu, Yifeng Pan, Dongbin Zhao 3/25/2026 arxiv

machine learning

We introduce DreamerAD, the first latent world model framework that enables efficient reinforcement learning for autonomous driving by compressing diffusion sampling from 100 steps to 1 - achieving 80x speedup while maintaining visual interpretability. Training RL policies on real-world driving data...

Keywords: DreamerAD, latent world model, diffusion compression, reinforcement learning, autonomous driving, NavSim v2, autoregressive dense reward, Gaussian vocabulary sampling

Aditya Mittal, Ryan Shar, Zichu Wu, Shyam Agarwal, Tongshuang Wu, Chris Donahue, Ameet Talwalkar, Wayne Chi, Valerie Chen 3/25/2026 arxiv

machine learning

As LLMs are increasingly used as judges in code applications, they should be evaluated in realistic interactive settings that capture partial context and ambiguous intent. We present TRACE (Tool for Rubric Analysis in Code Evaluation), a framework that evaluates LLM judges' ability to predict human ...

Keywords: TRACE, LLM judges, code evaluation, rubric extraction, developer preferences, alignment, software engineering, bias analysis

Jiaying Zhou, Zhihao Zhan, Ruifeng Zhai, Qinhan Lyu, Hao Liu, Keze Wang, Liang Lin, Guangrun Wang 3/25/2026 arxiv

robotics

Vision--Language--Action (VLA) policies have shown strong progress in mapping language instructions and visual observations to robotic actions, yet their reliability degrades in cluttered scenes with distractors. By analyzing failure cases, we find that many errors do not arise from infeasible motio...

Keywords: Target-Agnostic Guidance, TAG, vision-language-action, classifier-free guidance, robotic manipulation, object grounding, distractor robustness, LIBERO

Linbo Wang, Yupeng Zheng, Qiang Chen, Shiwei Li, Yichen Zhang, Zebin Xing, Qichao Zhang, Xiang Li, Deheng Qian, Pengxuan Yang, Yihang Dong, Ce Hao, Xiaoqing Ye, Junyu han, Yifeng Pan, Dongbin Zhao 3/25/2026 arxiv

machine learning

We introduce Latent-WAM, an efficient end-to-end autonomous driving framework that achieves strong trajectory planning through spatially-aware and dynamics-informed latent world representations. Existing world-model-based planners suffer from inadequately compressed representations, limited spatial ...

Keywords: Latent-WAM, Spatial-Aware Compressive World Encoder (SCWE), Dynamic Latent World Model (DLWM), latent world model, end-to-end autonomous driving, causal Transformer, scene tokens, NAVSIM v2

Zhuo Li, Yupeng Zhang, Pengyu Cheng, Jiajun Song, Mengyu Zhou, Hao Li, Shujie Hu, Yu Qin, Erchao Zhao, Xiaoxi Jiang, Guanjun Jiang 3/25/2026 arxiv

natural language processing

Hallucination remains a critical bottleneck for large language models (LLMs), undermining their reliability in real-world applications, especially in Retrieval-Augmented Generation (RAG) systems. While existing hallucination detection methods employ LLM-as-a-judge to verify LLM outputs against retri...

Keywords: hallucination, LLM, RAG, multi-agent RL, self-check, information asymmetry, proposer, checker

Falong Fan, Yi Xie, Arnis Lektauers, Bo Liu, Jerzy Rozenblit 3/25/2026 arxiv

machine learning

Accurate 3D reconstruction of deformable soft tissues is essential for surgical robotic perception. However, low-texture surfaces, specular highlights, and instrument occlusions often fragment geometric continuity, posing a challenge for existing fixed-topology approaches. To address this, we propos...

Keywords: EndoVGGT, DeGAT, graph attention, feature-space graphs, depth estimation, 3D reconstruction, surgical robotics, non-rigid deformation

Qijia He, Xunmei Liu, Hammaad Memon, Ziang Li, Zixian Ma, Jaemin Cho, Jason Ren, Daniel S Weld, Ranjay Krishna 3/25/2026 arxiv

computer vision

Scalable Vector Graphics (SVG) are an essential format for technical illustration and digital design, offering precise resolution independence and flexible semantic editability. In practice, however, original vector source files are frequently lost or inaccessible, leaving only "flat" rasterized ver...

Keywords: VFIG, SVG, vectorization, vision-language models, VFIG-DATA, VFIG-BENCH, coarse-to-fine, reinforcement learning

Yubo Li, Xugong Qin, Peng Zhang, Hailun Lin, Gangyan Zeng, Kexin Zhang 3/25/2026 arxiv

computer vision

Scene text editing seeks to modify textual content in natural images while maintaining visual realism and semantic consistency. Existing methods often require task-specific training or paired data, limiting their scalability and adaptability. In this paper, we propose TextFlow, a training-free scene...

Keywords: TextFlow, AttnBoost, Flow Manifold Steering, scene text editing, training-free, visual realism, semantic consistency, plug-and-play

Quentin Cohen-Solal 3/25/2026 arxiv

reinforcement learning

In this article, we focus on search algorithms for two-player perfect information games, whose objective is to determine the best possible strategy, and ideally a winning strategy. Unfortunately, some search algorithms for games in the literature are not able to always determine a winning strategy...

Keywords: unbounded best-first minimax, descent minimax, completion technique, completeness, game search, perfect information games, knowledge-free reinforcement learning, theoretical guarantees
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