Tootfinder

Stitch: Training-Free Position Control in Multimodal Diffusion Transformers
Jessica Bader, Mateusz Pach, Maria A. Bravo, Serge Belongie, Zeynep Akata
https://arxiv.org/abs/2509.26644

Stitch: Training-Free Position Control in Multimodal Diffusion Transformers
Text-to-Image (T2I) generation models have advanced rapidly in recent years, but accurately capturing spatial relationships like "above" or "to the right of" poses a persistent challenge. Earlier methods improved spatial relationship following with external position control. However, as architectures evolved to enhance image quality, these techniques became incompatible with modern models. We propose Stitch, a training-free method for incorporating external position control into Multi-Modal Dif…

Linking Process to Outcome: Conditional Reward Modeling for LLM Reasoning
Zheng Zhang, Ziwei Shan, Kaitao Song, Yexin Li, Kan Ren
https://arxiv.org/abs/2509.26578 https://

Linking Process to Outcome: Conditional Reward Modeling for LLM Reasoning
Process Reward Models (PRMs) have emerged as a promising approach to enhance the reasoning capabilities of large language models (LLMs) by guiding their step-by-step reasoning toward a final answer. However, existing PRMs either treat each reasoning step in isolation, failing to capture inter-step dependencies, or struggle to align process rewards with the final outcome. Consequently, the reward signal fails to respect temporal causality in sequential reasoning and faces ambiguous credit assign…

Long but very good:
"An essay on wank"
It names and identifies one of my least favorite genre of posts – finally I have a proper term for it!
I'm sure I've been guilty of it too in the past, so it's useful for self-regulation, too.
https://deadsimpletech.com/blog/essay_

CineWild: Balancing Art and Robotics for Ethical Wildlife Documentary Filmmaking
Pablo Pueyo, Fernando Caballero, Ana Cristina Murillo, Eduardo Montijano
https://arxiv.org/abs/2509.24921

CineWild: Balancing Art and Robotics for Ethical Wildlife Documentary Filmmaking
Drones, or unmanned aerial vehicles (UAVs), have become powerful tools across domains-from industry to the arts. In documentary filmmaking, they offer dynamic, otherwise unreachable perspectives, transforming how stories are told. Wildlife documentaries especially benefit, yet drones also raise ethical concerns: the risk of disturbing the animals they aim to capture. This paper introduces CineWild, an autonomous UAV framework that combines robotics, cinematography, and ethics. Built on model pr…

AI-Based Stroke Rehabilitation Domiciliary Assessment System with ST_GCN Attention
Suhyeon Lim, Ye-eun Kim, Andrew J. Choi
https://arxiv.org/abs/2510.00049 https://

AI-Based Stroke Rehabilitation Domiciliary Assessment System with ST_GCN Attention
Effective stroke recovery requires continuous rehabilitation integrated with daily living. To support this need, we propose a home-based rehabilitation exercise and feedback system. The system consists of (1) hardware setup with RGB-D camera and wearable sensors to capture Stroke movements, (2) a mobile application for exercise guidance, and (3) an AI server for assessment and feedback. When Stroke user exercises following the application guidance, the system records skeleton sequences, which a…

MR$^2$-Bench: Going Beyond Matching to Reasoning in Multimodal Retrieval
Junjie Zhou, Ze Liu, Lei Xiong, Jin-Ge Yao, Yueze Wang, Shitao Xiao, Fenfen Lin, Miguel Hu Chen, Zhicheng Dou, Siqi Bao, Defu Lian, Yongping Xiong, Zheng Liu
https://arxiv.org/abs/2509.26378

MR$^2$-Bench: Going Beyond Matching to Reasoning in Multimodal Retrieval
Multimodal retrieval is becoming a crucial component of modern AI applications, yet its evaluation lags behind the demands of more realistic and challenging scenarios. Existing benchmarks primarily probe surface-level semantic correspondence (e.g., object-text matching) while failing to assess the deeper reasoning required to capture complex relationships between visual and textual information. To address this gap, we introduce MR$^2$-Bench, a reasoning-intensive benchmark for multimodal retrie…

A fast powerful X-ray transient from tidal disruption of a white dwarf
D. -Y. Li, J. Yang, W. -D. Zhang, the Einstein Probe collaborations
https://arxiv.org/abs/2509.25877 https…

A fast powerful X-ray transient from tidal disruption of a white dwarf
Stars captured by black holes (BHs) can be tore apart by strong tidal force, producing electromagnetic flares. Some 100 tidal disruption events (TDEs) have been observed, involving invariably normal gaseous stars whose debris falls onto the BH fueling the flares over years. White dwarfs (WDs)-the most prevalent compact stars a million times denser and thus tougher than gaseous stars-can only be disrupted by intermediate-mass black holes (IMBHs) of 10^2-10^5 solar masses. WD-TDEs are predicted t…

Stable Cinemetrics : Structured Taxonomy and Evaluation for Professional Video Generation
Agneet Chatterjee, Rahim Entezari, Maksym Zhuravinskyi, Maksim Lapin, Reshinth Adithyan, Amit Raj, Chitta Baral, Yezhou Yang, Varun Jampani
https://arxiv.org/abs/2509.26555

Stable Cinemetrics : Structured Taxonomy and Evaluation for Professional Video Generation
Recent advances in video generation have enabled high-fidelity video synthesis from user provided prompts. However, existing models and benchmarks fail to capture the complexity and requirements of professional video generation. Towards that goal, we introduce Stable Cinemetrics, a structured evaluation framework that formalizes filmmaking controls into four disentangled, hierarchical taxonomies: Setup, Event, Lighting, and Camera. Together, these taxonomies define 76 fine-grained control nodes…

A Greedy PDE Router for Blending Neural Operators and Classical Methods
Sahana Rayan, Yash Patel, Ambuj Tewari
https://arxiv.org/abs/2509.24814 https://arx…

A Greedy PDE Router for Blending Neural Operators and Classical Methods
When solving PDEs, classical numerical solvers are often computationally expensive, while machine learning methods can suffer from spectral bias, failing to capture high-frequency components. Designing an optimal hybrid iterative solver--where, at each iteration, a solver is selected from an ensemble of solvers to leverage their complementary strengths--poses a challenging combinatorial problem. While the greedy selection strategy is desirable for its constant-factor approximation guarantee to …

Persistent Autoregressive Mapping with Traffic Rules for Autonomous Driving
Shiyi Liang, Xinyuan Chang, Changjie Wu, Huiyuan Yan, Yifan Bai, Xinran Liu, Hang Zhang, Yujian Yuan, Shuang Zeng, Mu Xu, Xing Wei
https://arxiv.org/abs/2509.22756

Persistent Autoregressive Mapping with Traffic Rules for Autonomous Driving
Safe autonomous driving requires both accurate HD map construction and persistent awareness of traffic rules, even when their associated signs are no longer visible. However, existing methods either focus solely on geometric elements or treat rules as temporary classifications, failing to capture their persistent effectiveness across extended driving sequences. In this paper, we present PAMR (Persistent Autoregressive Mapping with Traffic Rules), a novel framework that performs autoregressive c…