Tootfinder

Replaced article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new
[2/5]:
- METIS: Fast Quality-Aware RAG Systems with Configuration Adaptation
Ray, Pan, Gu, Du, Feng, Ananthanarayanan, Netravali, Jiang

Quantize More, Lose Less: Autoregressive Generation from Residually Quantized Speech Representations
Yichen Han, Xiaoyang Hao, Keming Chen, Weibo Xiong, Jun He, Ruonan Zhang, Junjie Cao, Yue Liu, Bowen Li, Dongrui Zhang, Hui Xia, Huilei Fu, Kai Jia, Kaixuan Guo, Mingli Jin, Qingyun Meng, Ruidong Ma, Ruiqian Fang, Shaotong Guo, Xuhui Li, Yang Xiang, Ying Zhang, Yulong Liu, Yunfeng Li, Yuyi Zhang, Yuze Zhou, Zhen Wang, Zhaowen Chen

Quantize More, Lose Less: Autoregressive Generation from Residually Quantized Speech Representations
Text-to-speech (TTS) synthesis has seen renewed progress under the discrete modeling paradigm. Existing autoregressive approaches often rely on single-codebook representations, which suffer from significant information loss. Even with post-hoc refinement techniques such as flow matching, these methods fail to recover fine-grained details (e.g., prosodic nuances, speaker-specific timbres), especially in challenging scenarios like singing voice or music synthesis. We propose QTTS, a novel TTS fra…

OneRec Technical Report
Guorui Zhou, Jiaxin Deng, Jinghao Zhang, Kuo Cai, Lejian Ren, Qiang Luo, Qianqian Wang, Qigen Hu, Rui Huang, Shiyao Wang, Weifeng Ding, Wuchao Li, Xinchen Luo, Xingmei Wang, Zexuan Cheng, Zixing Zhang, Bin Zhang, Boxuan Wang, Chaoyi Ma, Chengru Song, Chenhui Wang, Di Wang, Dongxue Meng, Fan Yang, Fangyu Zhang, Feng Jiang, Fuxing Zhang, Gang Wang, Guowang Zhang, Han Li, Hengrui Hu, Hezheng Lin, Hongtao Cheng, Hongyang Cao, Huanjie Wang, Jiaming Huang, Jiapeng Che…

OneRec Technical Report
Recommender systems have been widely used in various large-scale user-oriented platforms for many years. However, compared to the rapid developments in the AI community, recommendation systems have not achieved a breakthrough in recent years. For instance, they still rely on a multi-stage cascaded architecture rather than an end-to-end approach, leading to computational fragmentation and optimization inconsistencies, and hindering the effective application of key breakthrough technologies from …

Hora de me arrumar para ir ao trabalho pela última vez antes das férias. Em situação normal estaria super animado. Mas como o período não acabou por conta desse calendšrio maluco, estarei com všrias pendências para resolver durante as férias, como preparar as provas finais (que jš acontecem assim que voltarmos).
De maneira geral, eu jamais paro completamente durante as férias, só diminuo (bastante) o ritmo. Mas receio que neste período vai ser difícil reduzir do mesmo modo.

MLM: Learning Multi-task Loco-Manipulation Whole-Body Control for Quadruped Robot with Arm
Xin Liu, Bida Ma, Chenkun Qi, Yan Ding, Zhaxizhuoma, Guorong Zhang, Pengan Chen, Kehui Liu, Zhongjie Jia, Chuyue Guan, Yule Mo, Jiaqi Liu, Feng Gao, Jiangwei Zhong, Bin Zhao, Xuelong Li
https://arxiv.org/abs/2508.10538…

MLM: Learning Multi-task Loco-Manipulation Whole-Body Control for Quadruped Robot with Arm
Whole-body loco-manipulation for quadruped robots with arm remains a challenging problem, particularly in achieving multi-task control. To address this, we propose MLM, a reinforcement learning framework driven by both real-world and simulation data. It enables a six-DoF robotic arm--equipped quadruped robot to perform whole-body loco-manipulation for multiple tasks autonomously or under human teleoperation. To address the problem of balancing multiple tasks during the learning of loco-manipula…

VGR: Visual Grounded Reasoning
Jiacong Wang, Zijiang Kang, Haochen Wang, Haiyong Jiang, Jiawen Li, Bohong Wu, Ya Wang, Jiao Ran, Xiao Liang, Chao Feng, Jun Xiao
https://arxiv.org/abs/2506.11991

VGR: Visual Grounded Reasoning
In the field of multimodal chain-of-thought (CoT) reasoning, existing approaches predominantly rely on reasoning on pure language space, which inherently suffers from language bias and is largely confined to math or science domains. This narrow focus limits their ability to handle complex visual reasoning tasks that demand comprehensive understanding of image details. To address these limitations, this paper introduces VGR, a novel reasoning multimodal large language model (MLLM) with enhanced …

Exploring Gender Bias in Alzheimer's Disease Detection: Insights from Mandarin and Greek Speech Perception
Liu He, Yuanchao Li, Rui Feng, XinRan Han, Yin-Long Liu, Yuwei Yang, Zude Zhu, Jiahong Yuan
https://arxiv.org/abs/2507.12356

Exploring Gender Bias in Alzheimer's Disease Detection: Insights from Mandarin and Greek Speech Perception
Gender bias has been widely observed in speech perception tasks, influenced by the fundamental voicing differences between genders. This study reveals a gender bias in the perception of Alzheimer's Disease (AD) speech. In a perception experiment involving 16 Chinese listeners evaluating both Chinese and Greek speech, we identified that male speech was more frequently identified as AD, with this bias being particularly pronounced in Chinese speech. Acoustic analysis showed that shimmer values in…

Replaced article(s) found for cs.CL. https://arxiv.org/list/cs.CL/new
[1/3]:
- Fine-grained Stateful Knowledge Exploration: Effective and Efficient Graph Retrieval with Large L...
Dehao Tao, Congqi Wang, Feng Huang, Junhao Chen, Yongfeng Huang, Minghu Jiang

Fast Non-Episodic Adaptive Tuning of Robot Controllers with Online Policy Optimization
James A. Preiss, Fengze Xie, Yiheng Lin, Adam Wierman, Yisong Yue
https://arxiv.org/abs/2507.10914

Fast Non-Episodic Adaptive Tuning of Robot Controllers with Online Policy Optimization
We study online algorithms to tune the parameters of a robot controller in a setting where the dynamics, policy class, and optimality objective are all time-varying. The system follows a single trajectory without episodes or state resets, and the time-varying information is not known in advance. Focusing on nonlinear geometric quadrotor controllers as a test case, we propose a practical implementation of a single-trajectory model-based online policy optimization algorithm, M-GAPS,along with rep…

Diffusion-Based Imaginative Coordination for Bimanual Manipulation
Huilin Xu, Jian Ding, Jiakun Xu, Ruixiang Wang, Jun Chen, Jinjie Mai, Yanwei Fu, Bernard Ghanem, Feng Xu, Mohamed Elhoseiny
https://arxiv.org/abs/2507.11296

Diffusion-Based Imaginative Coordination for Bimanual Manipulation
Bimanual manipulation is crucial in robotics, enabling complex tasks in industrial automation and household services. However, it poses significant challenges due to the high-dimensional action space and intricate coordination requirements. While video prediction has been recently studied for representation learning and control, leveraging its ability to capture rich dynamic and behavioral information, its potential for enhancing bimanual coordination remains underexplored. To bridge this gap, …