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2,503.14377 | Advancing Medical Representation Learning Through High-Quality Data | ['Negin Baghbanzadeh', 'Adibvafa Fallahpour', 'Yasaman Parhizkar', 'Franklin Ogidi', 'Shuvendu Roy', 'Sajad Ashkezari', 'Vahid Reza Khazaie', 'Michael Colacci', 'Ali Etemad', 'Arash Afkanpour', 'Elham Dolatabadi'] | ['eess.IV', 'cs.CV', 'cs.LG'] | Despite the growing scale of medical Vision-Language datasets, the impact of
dataset quality on model performance remains under-explored. We introduce
Open-PMC, a high-quality medical dataset from PubMed Central, containing 2.2
million image-text pairs, enriched with image modality annotations, subfigures,
and summariz... | 2025-03-18T16:10:11Z | null | null | null | Advancing Medical Representation Learning Through High-Quality Data | ['Negin Baghbanzadeh', 'Adibvafa Fallahpour', 'Yasaman Parhizkar', 'Franklin Ogidi', 'Shuvendu Roy', 'Sajad Ashkezari', 'Vahid Reza Khazaie', 'Michael Colacci', 'A. Etemad', 'Arash Afkanpour', 'Elham Dolatabadi'] | 2,025 | arXiv.org | 1 | 26 | ['Engineering', 'Computer Science'] |
2,503.14433 | Splintering Nonconcatenative Languages for Better Tokenization | ['Bar Gazit', 'Shaltiel Shmidman', 'Avi Shmidman', 'Yuval Pinter'] | ['cs.CL'] | Common subword tokenization algorithms like BPE and UnigramLM assume that
text can be split into meaningful units by concatenative measures alone. This
is not true for languages such as Hebrew and Arabic, where morphology is
encoded in root-template patterns, or Malay and Georgian, where split affixes
are common. We pr... | 2025-03-18T17:11:09Z | Findings of the ACL 2025 | null | null | Splintering Nonconcatenative Languages for Better Tokenization | ['Bar Gazit', 'Shaltiel Shmidman', 'Avi Shmidman', 'Yu. Lyubarsky Ben-Gurion University of the Negev', 'Dicta'] | 2,025 | arXiv.org | 0 | 29 | ['Computer Science'] |
2,503.14456 | RWKV-7 "Goose" with Expressive Dynamic State Evolution | ['Bo Peng', 'Ruichong Zhang', 'Daniel Goldstein', 'Eric Alcaide', 'Xingjian Du', 'Haowen Hou', 'Jiaju Lin', 'Jiaxing Liu', 'Janna Lu', 'William Merrill', 'Guangyu Song', 'Kaifeng Tan', 'Saiteja Utpala', 'Nathan Wilce', 'Johan S. Wind', 'Tianyi Wu', 'Daniel Wuttke', 'Christian Zhou-Zheng'] | ['cs.CL', 'cs.AI', 'cs.LG', 'I.2.0; I.2.7'] | We present RWKV-7 "Goose", a new sequence modeling architecture with constant
memory usage and constant inference time per token. Despite being trained on
dramatically fewer tokens than other top models, our 2.9 billion parameter
language model achieves a new 3B SoTA on multilingual tasks and matches the
current 3B SoT... | 2025-03-18T17:31:05Z | null | null | null | RWKV-7 "Goose" with Expressive Dynamic State Evolution | ['Bo Peng', 'Ruichong Zhang', 'Daniel Goldstein', 'Eric Alcaide', 'Xingjian Du', 'Haowen Hou', 'Jiaju Lin', 'Jiaxing Liu', 'Janna Lu', 'William Merrill', 'Guangyu Song', 'Kaifeng Tan', 'Saiteja Utpala', 'Nathan Wilce', 'J. S. Wind', 'Tianyi Wu', 'Daniel Wuttke', 'Christian Zhou-Zheng'] | 2,025 | arXiv.org | 23 | 0 | ['Computer Science'] |
2,503.14476 | DAPO: An Open-Source LLM Reinforcement Learning System at Scale | ['Qiying Yu', 'Zheng Zhang', 'Ruofei Zhu', 'Yufeng Yuan', 'Xiaochen Zuo', 'Yu Yue', 'Weinan Dai', 'Tiantian Fan', 'Gaohong Liu', 'Lingjun Liu', 'Xin Liu', 'Haibin Lin', 'Zhiqi Lin', 'Bole Ma', 'Guangming Sheng', 'Yuxuan Tong', 'Chi Zhang', 'Mofan Zhang', 'Wang Zhang', 'Hang Zhu', 'Jinhua Zhu', 'Jiaze Chen', 'Jiangjie C... | ['cs.LG', 'cs.CL'] | Inference scaling empowers LLMs with unprecedented reasoning ability, with
reinforcement learning as the core technique to elicit complex reasoning.
However, key technical details of state-of-the-art reasoning LLMs are concealed
(such as in OpenAI o1 blog and DeepSeek R1 technical report), thus the
community still stru... | 2025-03-18T17:49:06Z | Project Page: https://dapo-sia.github.io/ | null | null | null | null | null | null | null | null | null |
2,503.14489 | Stable Virtual Camera: Generative View Synthesis with Diffusion Models | ['Jensen Zhou', 'Hang Gao', 'Vikram Voleti', 'Aaryaman Vasishta', 'Chun-Han Yao', 'Mark Boss', 'Philip Torr', 'Christian Rupprecht', 'Varun Jampani'] | ['cs.CV'] | We present Stable Virtual Camera (Seva), a generalist diffusion model that
creates novel views of a scene, given any number of input views and target
cameras. Existing works struggle to generate either large viewpoint changes or
temporally smooth samples, while relying on specific task configurations. Our
approach over... | 2025-03-18T17:57:22Z | null | null | null | null | null | null | null | null | null | null |
2,503.14492 | Cosmos-Transfer1: Conditional World Generation with Adaptive Multimodal
Control | ['NVIDIA', ':', 'Hassan Abu Alhaija', 'Jose Alvarez', 'Maciej Bala', 'Tiffany Cai', 'Tianshi Cao', 'Liz Cha', 'Joshua Chen', 'Mike Chen', 'Francesco Ferroni', 'Sanja Fidler', 'Dieter Fox', 'Yunhao Ge', 'Jinwei Gu', 'Ali Hassani', 'Michael Isaev', 'Pooya Jannaty', 'Shiyi Lan', 'Tobias Lasser', 'Huan Ling', 'Ming-Yu Liu'... | ['cs.CV', 'cs.AI', 'cs.LG', 'cs.RO'] | We introduce Cosmos-Transfer, a conditional world generation model that can
generate world simulations based on multiple spatial control inputs of various
modalities such as segmentation, depth, and edge. In the design, the spatial
conditional scheme is adaptive and customizable. It allows weighting different
condition... | 2025-03-18T17:57:54Z | null | null | null | null | null | null | null | null | null | null |
2,503.14505 | MusicInfuser: Making Video Diffusion Listen and Dance | ['Susung Hong', 'Ira Kemelmacher-Shlizerman', 'Brian Curless', 'Steven M. Seitz'] | ['cs.CV', 'cs.AI', 'cs.LG'] | We introduce MusicInfuser, an approach for generating high-quality dance
videos that are synchronized to a specified music track. Rather than attempting
to design and train a new multimodal audio-video model, we show how existing
video diffusion models can be adapted to align with musical inputs by
introducing lightwei... | 2025-03-18T17:59:58Z | Project page: https://susunghong.github.io/MusicInfuser | null | null | MusicInfuser: Making Video Diffusion Listen and Dance | ['Susung Hong', 'Ira Kemelmacher-Shlizerman', 'Brian Curless', 'Steven M. Seitz'] | 2,025 | arXiv.org | 0 | 51 | ['Computer Science'] |
2,503.14603 | Command R7B Arabic: A Small, Enterprise Focused, Multilingual, and
Culturally Aware Arabic LLM | ['Yazeed Alnumay', 'Alexandre Barbet', 'Anna Bialas', 'William Darling', 'Shaan Desai', 'Joan Devassy', 'Kyle Duffy', 'Stephanie Howe', 'Olivia Lasche', 'Justin Lee', 'Anirudh Shrinivason', 'Jennifer Tracey'] | ['cs.CL', 'cs.LG'] | Building high-quality large language models (LLMs) for enterprise Arabic
applications remains challenging due to the limited availability of digitized
Arabic data. In this work, we present a data synthesis and refinement strategy
to help address this problem, namely, by leveraging synthetic data generation
and human-in... | 2025-03-18T18:03:49Z | null | null | null | null | null | null | null | null | null | null |
2,503.14637 | Reinforcement learning-based motion imitation for physiologically
plausible musculoskeletal motor control | ['Merkourios Simos', 'Alberto Silvio Chiappa', 'Alexander Mathis'] | ['cs.RO', 'cs.AI', 'cs.CV', 'cs.LG', 'q-bio.NC'] | How do humans move? The quest to understand human motion has broad
applications in numerous fields, ranging from computer animation and motion
synthesis to neuroscience, human prosthetics and rehabilitation. Although
advances in reinforcement learning (RL) have produced impressive results in
capturing human motion usin... | 2025-03-18T18:37:49Z | null | null | null | Reinforcement learning-based motion imitation for physiologically plausible musculoskeletal motor control | ['Merkourios Simos', 'A. Chiappa', 'Alexander Mathis'] | 2,025 | arXiv.org | 1 | 73 | ['Computer Science', 'Biology'] |
2,503.14734 | GR00T N1: An Open Foundation Model for Generalist Humanoid Robots | ['NVIDIA', ':', 'Johan Bjorck', 'Fernando Castañeda', 'Nikita Cherniadev', 'Xingye Da', 'Runyu Ding', 'Linxi "Jim" Fan', 'Yu Fang', 'Dieter Fox', 'Fengyuan Hu', 'Spencer Huang', 'Joel Jang', 'Zhenyu Jiang', 'Jan Kautz', 'Kaushil Kundalia', 'Lawrence Lao', 'Zhiqi Li', 'Zongyu Lin', 'Kevin Lin', 'Guilin Liu', 'Edith Llon... | ['cs.RO', 'cs.AI', 'cs.LG'] | General-purpose robots need a versatile body and an intelligent mind. Recent
advancements in humanoid robots have shown great promise as a hardware platform
for building generalist autonomy in the human world. A robot foundation model,
trained on massive and diverse data sources, is essential for enabling the
robots to... | 2025-03-18T21:06:21Z | Authors are listed alphabetically. Project leads are Linxi "Jim" Fan
and Yuke Zhu. For more information, see
https://developer.nvidia.com/isaac/gr00t | null | null | null | null | null | null | null | null | null |
2,503.14911 | Derm1M: A Million-scale Vision-Language Dataset Aligned with Clinical
Ontology Knowledge for Dermatology | ['Siyuan Yan', 'Ming Hu', 'Yiwen Jiang', 'Xieji Li', 'Hao Fei', 'Philipp Tschandl', 'Harald Kittler', 'Zongyuan Ge'] | ['cs.CV'] | The emergence of vision-language models has transformed medical AI, enabling
unprecedented advances in diagnostic capability and clinical applications.
However, progress in dermatology has lagged behind other medical domains due to
the lack of standard image-text pairs. Existing dermatological datasets are
limited in b... | 2025-03-19T05:30:01Z | Our dataset and code will be publicly available at
https://github.com/SiyuanYan1/Derm1M | null | null | null | null | null | null | null | null | null |
2,503.15265 | DeepMesh: Auto-Regressive Artist-mesh Creation with Reinforcement
Learning | ['Ruowen Zhao', 'Junliang Ye', 'Zhengyi Wang', 'Guangce Liu', 'Yiwen Chen', 'Yikai Wang', 'Jun Zhu'] | ['cs.CV'] | Triangle meshes play a crucial role in 3D applications for efficient
manipulation and rendering. While auto-regressive methods generate structured
meshes by predicting discrete vertex tokens, they are often constrained by
limited face counts and mesh incompleteness. To address these challenges, we
propose DeepMesh, a f... | 2025-03-19T14:39:30Z | Project page: https://zhaorw02.github.io/DeepMesh/ | null | null | null | null | null | null | null | null | null |
2,503.15354 | Optimizing Decomposition for Optimal Claim Verification | ['Yining Lu', 'Noah Ziems', 'Hy Dang', 'Meng Jiang'] | ['cs.CL', 'cs.AI'] | Current research on the \textit{Decompose-Then-Verify} paradigm for
evaluating the factuality of long-form text typically treats decomposition and
verification in isolation, overlooking their interactions and potential
misalignment. We find that existing decomposition policies, typically
hand-crafted demonstrations, do... | 2025-03-19T15:56:21Z | null | null | null | Optimizing Decomposition for Optimal Claim Verification | ['Yining Lu', 'Noah Ziems', 'Hy Dang', 'Meng Jiang'] | 2,025 | arXiv.org | 1 | 52 | ['Computer Science'] |
2,503.15426 | Visual Position Prompt for MLLM based Visual Grounding | ['Wei Tang', 'Yanpeng Sun', 'Qinying Gu', 'Zechao Li'] | ['cs.CV', 'cs.AI'] | Although Multimodal Large Language Models (MLLMs) excel at various
image-related tasks, they encounter challenges in precisely aligning
coordinates with spatial information within images, particularly in
position-aware tasks such as visual grounding. This limitation arises from two
key factors. First, MLLMs lack explic... | 2025-03-19T17:08:13Z | null | null | null | null | null | null | null | null | null | null |
2,503.15438 | VenusFactory: A Unified Platform for Protein Engineering Data Retrieval
and Language Model Fine-Tuning | ['Yang Tan', 'Chen Liu', 'Jingyuan Gao', 'Banghao Wu', 'Mingchen Li', 'Ruilin Wang', 'Lingrong Zhang', 'Huiqun Yu', 'Guisheng Fan', 'Liang Hong', 'Bingxin Zhou'] | ['cs.CL', 'cs.AI', 'q-bio.QM'] | Natural language processing (NLP) has significantly influenced scientific
domains beyond human language, including protein engineering, where pre-trained
protein language models (PLMs) have demonstrated remarkable success. However,
interdisciplinary adoption remains limited due to challenges in data
collection, task be... | 2025-03-19T17:19:07Z | 12 pages, 1 figure, 8 tables | null | null | null | null | null | null | null | null | null |
2,503.15451 | MotionStreamer: Streaming Motion Generation via Diffusion-based
Autoregressive Model in Causal Latent Space | ['Lixing Xiao', 'Shunlin Lu', 'Huaijin Pi', 'Ke Fan', 'Liang Pan', 'Yueer Zhou', 'Ziyong Feng', 'Xiaowei Zhou', 'Sida Peng', 'Jingbo Wang'] | ['cs.CV'] | This paper addresses the challenge of text-conditioned streaming motion
generation, which requires us to predict the next-step human pose based on
variable-length historical motions and incoming texts. Existing methods
struggle to achieve streaming motion generation, e.g., diffusion models are
constrained by pre-define... | 2025-03-19T17:32:24Z | Project Page: https://zju3dv.github.io/MotionStreamer/ | null | null | MotionStreamer: Streaming Motion Generation via Diffusion-based Autoregressive Model in Causal Latent Space | ['Lixing Xiao', 'Shunlin Lu', 'Huaijin Pi', 'Ke Fan', 'Liang Pan', 'Yueer Zhou', 'Ziyong Feng', 'Xiaowei Zhou', 'Sida Peng', 'Jingbo Wang'] | 2,025 | arXiv.org | 7 | 63 | ['Computer Science'] |
2,503.15475 | Cube: A Roblox View of 3D Intelligence | ['Foundation AI Team', 'Kiran Bhat', 'Nishchaie Khanna', 'Karun Channa', 'Tinghui Zhou', 'Yiheng Zhu', 'Xiaoxia Sun', 'Charles Shang', 'Anirudh Sudarshan', 'Maurice Chu', 'Daiqing Li', 'Kangle Deng', 'Jean-Philippe Fauconnier', 'Tijmen Verhulsdonck', 'Maneesh Agrawala', 'Kayvon Fatahalian', 'Alexander Weiss', 'Christia... | ['cs.CV'] | Foundation models trained on vast amounts of data have demonstrated
remarkable reasoning and generation capabilities in the domains of text,
images, audio and video. Our goal at Roblox is to build such a foundation model
for 3D intelligence, a model that can support developers in producing all
aspects of a Roblox exper... | 2025-03-19T17:52:17Z | Our code and model weights can be found at:
https://github.com/Roblox/cube | null | null | Cube: A Roblox View of 3D Intelligence | ['Kiran Bhat', 'Nishchaie Khanna', 'Karun Channa', 'Tinghui Zhou', 'Yiheng Zhu', 'Xiaoxia Sun', 'Charles Shang', 'Anirudh Sudarshan', 'Maurice Chu', 'Daiqing Li', 'Kangle Deng', 'J. Fauconnier', 'Tijmen Verhulsdonck', 'Maneesh Agrawala', 'Kayvon Fatahalian', 'Alexander Weiss', 'Christian Reiser', 'Ravi Kiran Chirravuri... | 2,025 | arXiv.org | 1 | 39 | ['Computer Science'] |
2,503.15558 | Cosmos-Reason1: From Physical Common Sense To Embodied Reasoning | ['NVIDIA', ':', 'Alisson Azzolini', 'Junjie Bai', 'Hannah Brandon', 'Jiaxin Cao', 'Prithvijit Chattopadhyay', 'Huayu Chen', 'Jinju Chu', 'Yin Cui', 'Jenna Diamond', 'Yifan Ding', 'Liang Feng', 'Francesco Ferroni', 'Rama Govindaraju', 'Jinwei Gu', 'Siddharth Gururani', 'Imad El Hanafi', 'Zekun Hao', 'Jacob Huffman', 'Ji... | ['cs.AI', 'cs.CV', 'cs.LG', 'cs.RO'] | Physical AI systems need to perceive, understand, and perform complex actions
in the physical world. In this paper, we present the Cosmos-Reason1 models that
can understand the physical world and generate appropriate embodied decisions
(e.g., next step action) in natural language through long chain-of-thought
reasoning... | 2025-03-18T22:06:58Z | null | null | null | Cosmos-Reason1: From Physical Common Sense To Embodied Reasoning | ['Nvidia Alisson Azzolini', 'Hannah Brandon', 'Prithvijit Chattopadhyay', 'Huayu Chen', 'Jinju Chu', 'Yin Cui', 'Jenna Diamond', 'Yifan Ding', 'Francesco Ferroni', 'Rama Govindaraju', 'Jinwei Gu', 'Siddharth Gururani', 'Imad El Hanafi', 'Zekun Hao', 'J. Huffman', 'Jingyi Jin', 'Brendan Johnson', 'Rizwan Khan', 'George ... | 2,025 | arXiv.org | 12 | 64 | ['Computer Science'] |
2,503.15617 | CAM-Seg: A Continuous-valued Embedding Approach for Semantic Image
Generation | ['Masud Ahmed', 'Zahid Hasan', 'Syed Arefinul Haque', 'Abu Zaher Md Faridee', 'Sanjay Purushotham', 'Suya You', 'Nirmalya Roy'] | ['cs.CV', 'cs.AI'] | Traditional transformer-based semantic segmentation relies on quantized
embeddings. However, our analysis reveals that autoencoder accuracy on
segmentation mask using quantized embeddings (e.g. VQ-VAE) is 8% lower than
continuous-valued embeddings (e.g. KL-VAE). Motivated by this, we propose a
continuous-valued embeddi... | 2025-03-19T18:06:54Z | null | null | null | CAM-Seg: A Continuous-valued Embedding Approach for Semantic Image Generation | ['Masud Ahmed', 'Zahid Hasan', 'Syed Arefinul Haque', 'A. Faridee', 'Sanjay Purushotham', 'Suya You', 'Nirmalya Roy'] | 2,025 | arXiv.org | 0 | 50 | ['Computer Science'] |
2,503.15621 | LLaVA-MORE: A Comparative Study of LLMs and Visual Backbones for
Enhanced Visual Instruction Tuning | ['Federico Cocchi', 'Nicholas Moratelli', 'Davide Caffagni', 'Sara Sarto', 'Lorenzo Baraldi', 'Marcella Cornia', 'Rita Cucchiara'] | ['cs.CV', 'cs.AI', 'cs.CL', 'cs.MM'] | Recent progress in Multimodal Large Language Models (MLLMs) has highlighted
the critical roles of both the visual backbone and the underlying language
model. While prior work has primarily focused on scaling these components to
billions of parameters, the trade-offs between model size, architecture, and
performance rem... | 2025-03-19T18:10:12Z | null | null | null | null | null | null | null | null | null | null |
2,503.15633 | Vision-Speech Models: Teaching Speech Models to Converse about Images | ['Amélie Royer', 'Moritz Böhle', 'Gabriel de Marmiesse', 'Laurent Mazaré', 'Neil Zeghidour', 'Alexandre Défossez', 'Patrick Pérez'] | ['cs.CV'] | The recent successes of Vision-Language models raise the question of how to
equivalently imbue a pretrained speech model with vision understanding, an
important milestone towards building a multimodal speech model able to freely
converse about images. Building such a conversational Vision-Speech model
brings its unique... | 2025-03-19T18:40:45Z | null | null | null | Vision-Speech Models: Teaching Speech Models to Converse about Images | ["Am'elie Royer", 'Moritz Böhle', 'Gabriel de Marmiesse', "Laurent Mazar'e", 'Neil Zeghidour', "Alexandre D'efossez", "Patrick P'erez"] | 2,025 | arXiv.org | 0 | 39 | ['Computer Science'] |
2,503.15667 | DiffPortrait360: Consistent Portrait Diffusion for 360 View Synthesis | ['Yuming Gu', 'Phong Tran', 'Yujian Zheng', 'Hongyi Xu', 'Heyuan Li', 'Adilbek Karmanov', 'Hao Li'] | ['cs.CV'] | Generating high-quality 360-degree views of human heads from single-view
images is essential for enabling accessible immersive telepresence applications
and scalable personalized content creation. While cutting-edge methods for full
head generation are limited to modeling realistic human heads, the latest
diffusion-bas... | 2025-03-19T19:47:04Z | Page:https://freedomgu.github.io/DiffPortrait360
Code:https://github.com/FreedomGu/DiffPortrait360/ | null | null | DiffPortrait360: Consistent Portrait Diffusion for 360 View Synthesis | ['Yuming Gu', 'Phong Tran', 'Yujian Zheng', 'Hongyi Xu', 'Heyuan Li', 'Adilbek Karmanov', 'Hao Li'] | 2,025 | arXiv.org | 1 | 60 | ['Computer Science'] |
2,503.15683 | The Change You Want To Detect: Semantic Change Detection In Earth
Observation With Hybrid Data Generation | ['Yanis Benidir', 'Nicolas Gonthier', 'Clement Mallet'] | ['cs.CV'] | Bi-temporal change detection at scale based on Very High Resolution (VHR)
images is crucial for Earth monitoring. This remains poorly addressed so far:
methods either require large volumes of annotated data (semantic case), or are
limited to restricted datasets (binary set-ups). Most approaches do not exhibit
the versa... | 2025-03-19T20:32:37Z | null | null | null | null | null | null | null | null | null | null |
2,503.15686 | Multi-focal Conditioned Latent Diffusion for Person Image Synthesis | ['Jiaqi Liu', 'Jichao Zhang', 'Paolo Rota', 'Nicu Sebe'] | ['cs.CV'] | The Latent Diffusion Model (LDM) has demonstrated strong capabilities in
high-resolution image generation and has been widely employed for Pose-Guided
Person Image Synthesis (PGPIS), yielding promising results. However, the
compression process of LDM often results in the deterioration of details,
particularly in sensit... | 2025-03-19T20:50:10Z | CVPR 2025 Accepted | null | null | null | null | null | null | null | null | null |
2,503.15876 | DeepPsy-Agent: A Stage-Aware and Deep-Thinking Emotional Support Agent
System | ['Kai Chen', 'Zebing Sun'] | ['cs.AI'] | This paper introduces DeepPsy-Agent, an innovative psychological support
system that combines the three-stage helping theory in psychology with deep
learning techniques. The system consists of two core components: (1) a
multi-stage response-capable dialogue model (\textit{deeppsy-chat}), which
enhances reasoning capabi... | 2025-03-20T05:59:29Z | null | null | null | DeepPsy-Agent: A Stage-Aware and Deep-Thinking Emotional Support Agent System | ['Kai Chen', 'Zebing Sun'] | 2,025 | arXiv.org | 0 | 8 | ['Computer Science'] |
2,503.15937 | Advancing Mobile GUI Agents: A Verifier-Driven Approach to Practical
Deployment | ['Gaole Dai', 'Shiqi Jiang', 'Ting Cao', 'Yuanchun Li', 'Yuqing Yang', 'Rui Tan', 'Mo Li', 'Lili Qiu'] | ['cs.AI'] | We propose V-Droid, a mobile GUI task automation agent. Unlike previous
mobile agents that utilize Large Language Models (LLMs) as generators to
directly generate actions at each step, V-Droid employs LLMs as verifiers to
evaluate candidate actions before making final decisions. To realize this novel
paradigm, we intro... | 2025-03-20T08:25:00Z | 14 pages, 4 iterations, refine figs | null | null | Advancing Mobile GUI Agents: A Verifier-Driven Approach to Practical Deployment | ['Gaole Dai', 'Shiqi Jiang', 'Ting Cao', 'Yuanchun Li', 'Yuqing Yang', 'Rui Tan', 'Mo Li', 'Lili Qiu'] | 2,025 | arXiv.org | 4 | 40 | ['Computer Science'] |
2,503.16159 | Neural Combinatorial Optimization for Real-World Routing | ['Jiwoo Son', 'Zhikai Zhao', 'Federico Berto', 'Chuanbo Hua', 'Changhyun Kwon', 'Jinkyoo Park'] | ['cs.LG', 'cs.AI'] | Vehicle Routing Problems (VRPs) are a class of NP-hard problems ubiquitous in
several real-world logistics scenarios that pose significant challenges for
optimization. Neural Combinatorial Optimization (NCO) has emerged as a
promising alternative to classical approaches, as it can learn fast heuristics
to solve VRPs. H... | 2025-03-20T13:57:33Z | null | null | null | Neural Combinatorial Optimization for Real-World Routing | ['Jiwoo Son', 'Zhikai Zhao', 'Federico Berto', 'Chuanbo Hua', 'Changhyun Kwon', 'Jinkyoo Park'] | 2,025 | arXiv.org | 1 | 73 | ['Computer Science'] |
2,503.16212 | MathFusion: Enhancing Mathematical Problem-solving of LLM through
Instruction Fusion | ['Qizhi Pei', 'Lijun Wu', 'Zhuoshi Pan', 'Yu Li', 'Honglin Lin', 'Chenlin Ming', 'Xin Gao', 'Conghui He', 'Rui Yan'] | ['cs.CL', 'cs.AI'] | Large Language Models (LLMs) have shown impressive progress in mathematical
reasoning. While data augmentation is promising to enhance mathematical
problem-solving ability, current approaches are predominantly limited to
instance-level modifications-such as rephrasing or generating syntactic
variations-which fail to ca... | 2025-03-20T15:00:41Z | Accepted by ACL 2025 (main) | null | null | null | null | null | null | null | null | null |
2,503.16219 | Reinforcement Learning for Reasoning in Small LLMs: What Works and What
Doesn't | ['Quy-Anh Dang', 'Chris Ngo'] | ['cs.LG', 'cs.CL'] | Enhancing the reasoning capabilities of large language models (LLMs)
typically relies on massive computational resources and extensive datasets,
limiting accessibility for resource-constrained settings. Our study
investigates the potential of reinforcement learning (RL) to improve reasoning
in small LLMs, focusing on a... | 2025-03-20T15:13:23Z | null | null | null | Reinforcement Learning for Reasoning in Small LLMs: What Works and What Doesn't | ['Quy-Anh Dang', 'Chris Ngo'] | 2,025 | arXiv.org | 20 | 38 | ['Computer Science'] |
2,503.16252 | Fin-R1: A Large Language Model for Financial Reasoning through
Reinforcement Learning | ['Zhaowei Liu', 'Xin Guo', 'Fangqi Lou', 'Lingfeng Zeng', 'Jinyi Niu', 'Zixuan Wang', 'Jiajie Xu', 'Weige Cai', 'Ziwei Yang', 'Xueqian Zhao', 'Chao Li', 'Sheng Xu', 'Dezhi Chen', 'Yun Chen', 'Zuo Bai', 'Liwen Zhang'] | ['cs.CL'] | Reasoning large language models are rapidly evolving across various domains.
However, their capabilities in handling complex financial tasks still require
in-depth exploration. In this paper, we introduce Fin-R1, a reasoning large
language model specifically designed for the financial sector. Fin-R1 is built
using a tw... | 2025-03-20T15:46:18Z | null | null | null | Fin-R1: A Large Language Model for Financial Reasoning through Reinforcement Learning | ['Zhaowei Liu', 'Xin Guo', 'Fangqi Lou', 'Lingfeng Zeng', 'Jinyi Niu', 'Zixuan Wang', 'Jiajie Xu', 'Weige Cai', 'Ziwei Yang', 'Xueqian Zhao', 'Chaojun Li', 'Sheng Xu', 'Dezhi Chen', 'Yun Chen', 'Zuo Bai', 'Liwen Zhang'] | 2,025 | arXiv.org | 15 | 30 | ['Computer Science'] |
2,503.16278 | Uni-3DAR: Unified 3D Generation and Understanding via Autoregression on
Compressed Spatial Tokens | ['Shuqi Lu', 'Haowei Lin', 'Lin Yao', 'Zhifeng Gao', 'Xiaohong Ji', 'Weinan E', 'Linfeng Zhang', 'Guolin Ke'] | ['cs.LG', 'cond-mat.mtrl-sci', 'q-bio.BM'] | Recent advancements in large language models and their multi-modal extensions
have demonstrated the effectiveness of unifying generation and understanding
through autoregressive next-token prediction. However, despite the critical
role of 3D structural generation and understanding (3D GU) in AI for science,
these tasks... | 2025-03-20T16:07:04Z | null | null | null | null | null | null | null | null | null | null |
2,503.16282 | Generalized Few-shot 3D Point Cloud Segmentation with Vision-Language
Model | ['Zhaochong An', 'Guolei Sun', 'Yun Liu', 'Runjia Li', 'Junlin Han', 'Ender Konukoglu', 'Serge Belongie'] | ['cs.CV'] | Generalized few-shot 3D point cloud segmentation (GFS-PCS) adapts models to
new classes with few support samples while retaining base class segmentation.
Existing GFS-PCS methods enhance prototypes via interacting with support or
query features but remain limited by sparse knowledge from few-shot samples.
Meanwhile, 3D... | 2025-03-20T16:10:33Z | Accepted to CVPR 2025 | null | null | null | null | null | null | null | null | null |
2,503.16309 | Rapid patient-specific neural networks for intraoperative X-ray to
volume registration | ['Vivek Gopalakrishnan', 'Neel Dey', 'David-Dimitris Chlorogiannis', 'Andrew Abumoussa', 'Anna M. Larson', 'Darren B. Orbach', 'Sarah Frisken', 'Polina Golland'] | ['eess.IV', 'cs.CV', 'physics.med-ph'] | The integration of artificial intelligence in image-guided interventions
holds transformative potential, promising to extract 3D geometric and
quantitative information from conventional 2D imaging modalities during complex
procedures. Achieving this requires the rapid and precise alignment of 2D
intraoperative images (... | 2025-03-20T16:33:45Z | null | null | null | Rapid patient-specific neural networks for intraoperative X-ray to volume registration | ['Vivek Gopalakrishnan', 'Neel Dey', 'D. Chlorogiannis', 'Andrew Abumoussa', 'Anna M. Larson', 'Darren B Orbach', 'S. Frisken', 'Polina Golland'] | 2,025 | arXiv.org | 1 | 83 | ['Medicine', 'Computer Science', 'Engineering', 'Physics'] |
2,503.16322 | Ultra-Resolution Adaptation with Ease | ['Ruonan Yu', 'Songhua Liu', 'Zhenxiong Tan', 'Xinchao Wang'] | ['cs.CV'] | Text-to-image diffusion models have achieved remarkable progress in recent
years. However, training models for high-resolution image generation remains
challenging, particularly when training data and computational resources are
limited. In this paper, we explore this practical problem from two key
perspectives: data a... | 2025-03-20T16:44:43Z | Technical Report. Codes are available
\href{https://github.com/Huage001/URAE}{here} | null | null | null | null | null | null | null | null | null |
2,503.16396 | SV4D 2.0: Enhancing Spatio-Temporal Consistency in Multi-View Video
Diffusion for High-Quality 4D Generation | ['Chun-Han Yao', 'Yiming Xie', 'Vikram Voleti', 'Huaizu Jiang', 'Varun Jampani'] | ['cs.CV'] | We present Stable Video 4D 2.0 (SV4D 2.0), a multi-view video diffusion model
for dynamic 3D asset generation. Compared to its predecessor SV4D, SV4D 2.0 is
more robust to occlusions and large motion, generalizes better to real-world
videos, and produces higher-quality outputs in terms of detail sharpness and
spatio-te... | 2025-03-20T17:53:38Z | Project page: https://sv4d20.github.io/ | null | null | SV4D 2.0: Enhancing Spatio-Temporal Consistency in Multi-View Video Diffusion for High-Quality 4D Generation | ['Chun-Han Yao', 'Yiming Xie', 'Vikram S. Voleti', 'Huaizu Jiang', 'Varun Jampani'] | 2,025 | arXiv.org | 1 | 87 | ['Computer Science'] |
2,503.16397 | Scale-wise Distillation of Diffusion Models | ['Nikita Starodubcev', 'Denis Kuznedelev', 'Artem Babenko', 'Dmitry Baranchuk'] | ['cs.CV'] | We present SwD, a scale-wise distillation framework for diffusion models
(DMs), which effectively employs next-scale prediction ideas for
diffusion-based few-step generators. In more detail, SwD is inspired by the
recent insights relating diffusion processes to the implicit spectral
autoregression. We suppose that DMs ... | 2025-03-20T17:54:02Z | null | null | null | Scale-wise Distillation of Diffusion Models | ['Nikita Starodubcev', 'Denis Kuznedelev', 'Artem Babenko', 'Dmitry Baranchuk'] | 2,025 | arXiv.org | 0 | 72 | ['Computer Science'] |
2,503.16418 | InfiniteYou: Flexible Photo Recrafting While Preserving Your Identity | ['Liming Jiang', 'Qing Yan', 'Yumin Jia', 'Zichuan Liu', 'Hao Kang', 'Xin Lu'] | ['cs.CV', 'cs.LG'] | Achieving flexible and high-fidelity identity-preserved image generation
remains formidable, particularly with advanced Diffusion Transformers (DiTs)
like FLUX. We introduce InfiniteYou (InfU), one of the earliest robust
frameworks leveraging DiTs for this task. InfU addresses significant issues of
existing methods, su... | 2025-03-20T17:59:34Z | Project page: https://bytedance.github.io/InfiniteYou/ Code and
model: https://github.com/bytedance/InfiniteYou | null | null | InfiniteYou: Flexible Photo Recrafting While Preserving Your Identity | ['Liming Jiang', 'Qing Yan', 'Yumin Jia', 'Zichuan Liu', 'Hao Kang', 'Xin Lu'] | 2,025 | arXiv.org | 4 | 59 | ['Computer Science'] |
2,503.16421 | MagicMotion: Controllable Video Generation with Dense-to-Sparse
Trajectory Guidance | ['Quanhao Li', 'Zhen Xing', 'Rui Wang', 'Hui Zhang', 'Qi Dai', 'Zuxuan Wu'] | ['cs.CV', 'cs.AI', 'cs.LG', 'cs.MM'] | Recent advances in video generation have led to remarkable improvements in
visual quality and temporal coherence. Upon this, trajectory-controllable video
generation has emerged to enable precise object motion control through
explicitly defined spatial paths. However, existing methods struggle with
complex object movem... | 2025-03-20T17:59:42Z | null | null | null | null | null | null | null | null | null | null |
2,503.16423 | GAEA: A Geolocation Aware Conversational Model | ['Ron Campos', 'Ashmal Vayani', 'Parth Parag Kulkarni', 'Rohit Gupta', 'Aritra Dutta', 'Mubarak Shah'] | ['cs.CV', 'cs.LG', 'I.4; I.2.7; I.5'] | Image geolocalization, in which, traditionally, an AI model predicts the
precise GPS coordinates of an image is a challenging task with many downstream
applications. However, the user cannot utilize the model to further their
knowledge other than the GPS coordinate; the model lacks an understanding of
the location and ... | 2025-03-20T17:59:47Z | The dataset and code used in this submission is available at:
https://ucf-crcv.github.io/GAEA/ | null | null | null | null | null | null | null | null | null |
2,503.16426 | DynamicVis: An Efficient and General Visual Foundation Model for Remote
Sensing Image Understanding | ['Keyan Chen', 'Chenyang Liu', 'Bowen Chen', 'Wenyuan Li', 'Zhengxia Zou', 'Zhenwei Shi'] | ['cs.CV'] | The advancement of remote sensing technology has improved the spatial
resolution of satellite imagery, facilitating more detailed visual
representations for diverse interpretations. However, existing methods exhibit
limited generalization capabilities across varied applications. While some
contemporary foundation model... | 2025-03-20T17:59:54Z | null | null | null | null | null | null | null | null | null | null |
2,503.1643 | Bridging Continuous and Discrete Tokens for Autoregressive Visual
Generation | ['Yuqing Wang', 'Zhijie Lin', 'Yao Teng', 'Yuanzhi Zhu', 'Shuhuai Ren', 'Jiashi Feng', 'Xihui Liu'] | ['cs.CV'] | Autoregressive visual generation models typically rely on tokenizers to
compress images into tokens that can be predicted sequentially. A fundamental
dilemma exists in token representation: discrete tokens enable straightforward
modeling with standard cross-entropy loss, but suffer from information loss and
tokenizer t... | 2025-03-20T17:59:59Z | Project page: https://yuqingwang1029.github.io/TokenBridge | null | null | null | null | null | null | null | null | null |
2,503.16944 | HyperLoRA: Parameter-Efficient Adaptive Generation for Portrait
Synthesis | ['Mengtian Li', 'Jinshu Chen', 'Wanquan Feng', 'Bingchuan Li', 'Fei Dai', 'Songtao Zhao', 'Qian He'] | ['cs.CV'] | Personalized portrait synthesis, essential in domains like social
entertainment, has recently made significant progress. Person-wise fine-tuning
based methods, such as LoRA and DreamBooth, can produce photorealistic outputs
but need training on individual samples, consuming time and resources and
posing an unstable ris... | 2025-03-21T08:44:27Z | null | null | null | null | null | null | null | null | null | null |
2,503.17076 | Halton Scheduler For Masked Generative Image Transformer | ['Victor Besnier', 'Mickael Chen', 'David Hurych', 'Eduardo Valle', 'Matthieu Cord'] | ['cs.CV'] | Masked Generative Image Transformers (MaskGIT) have emerged as a scalable and
efficient image generation framework, able to deliver high-quality visuals with
low inference costs. However, MaskGIT's token unmasking scheduler, an essential
component of the framework, has not received the attention it deserves. We
analyze... | 2025-03-21T12:00:59Z | null | null | null | null | null | null | null | null | null | null |
2,503.17237 | Strong Baseline: Multi-UAV Tracking via YOLOv12 with BoT-SORT-ReID | ['Yu-Hsi Chen'] | ['cs.CV', 'cs.AI'] | Detecting and tracking multiple unmanned aerial vehicles (UAVs) in thermal
infrared video is inherently challenging due to low contrast, environmental
noise, and small target sizes. This paper provides a straightforward approach
to address multi-UAV tracking in thermal infrared video, leveraging recent
advances in dete... | 2025-03-21T15:40:18Z | 10 pages, 5 figures, 5 tables | Proceedings of the Computer Vision and Pattern Recognition
Conference (CVPR) Workshops, 2025, pp. 6573-6582 | null | null | null | null | null | null | null | null |
2,503.17247 | KL3M Tokenizers: A Family of Domain-Specific and Character-Level
Tokenizers for Legal, Financial, and Preprocessing Applications | ['Michael J Bommarito', 'Daniel Martin Katz', 'Jillian Bommarito'] | ['cs.CL', 'cs.AI'] | We present the KL3M tokenizers, a family of specialized tokenizers for legal,
financial, and governmental text. Despite established work on tokenization,
specialized tokenizers for professional domains remain understudied. Our paper
offers two main contributions to this area.
First, we introduce domain-specific BPE t... | 2025-03-21T15:51:43Z | 12 pages, 7 tables, 3 figures; Source code available at
https://github.com/alea-institute/kl3m-tokenizer-paper | null | null | KL3M Tokenizers: A Family of Domain-Specific and Character-Level Tokenizers for Legal, Financial, and Preprocessing Applications | ['M. Bommarito', 'Daniel Martin Katz', 'Jillian Bommarito'] | 2,025 | arXiv.org | 1 | 20 | ['Computer Science'] |
2,503.17287 | FastCuRL: Curriculum Reinforcement Learning with Stage-wise Context
Scaling for Efficient Training R1-like Reasoning Models | ['Mingyang Song', 'Mao Zheng', 'Zheng Li', 'Wenjie Yang', 'Xuan Luo', 'Yue Pan', 'Feng Zhang'] | ['cs.CL'] | Improving training efficiency continues to be one of the primary challenges
in large-scale Reinforcement Learning (RL). In this paper, we investigate how
context length and the complexity of training data influence the RL scaling
training process of R1-distilled small reasoning models, e.g.,
DeepSeek-R1-Distill-Qwen-1.... | 2025-03-21T16:35:31Z | Ongoing Work | null | null | null | null | null | null | null | null | null |
2,503.17352 | OpenVLThinker: An Early Exploration to Complex Vision-Language Reasoning
via Iterative Self-Improvement | ['Yihe Deng', 'Hritik Bansal', 'Fan Yin', 'Nanyun Peng', 'Wei Wang', 'Kai-Wei Chang'] | ['cs.CV', 'cs.CL'] | Recent advancements demonstrated by DeepSeek-R1 have shown that complex
reasoning abilities in large language models (LLMs), including sophisticated
behaviors such as self-verification and self-correction, can be achieved by RL
with verifiable rewards and significantly improves model performance on
challenging tasks su... | 2025-03-21T17:52:43Z | 23 pages, 11 figures, 8 tables | null | null | OpenVLThinker: An Early Exploration to Complex Vision-Language Reasoning via Iterative Self-Improvement | ['Yihe Deng', 'Hritik Bansal', 'Fan Yin', 'Nanyun Peng', 'Wei Wang', 'Kai-Wei Chang'] | 2,025 | arXiv.org | 51 | 66 | ['Computer Science'] |
2,503.17439 | LEMMA: Learning from Errors for MatheMatical Advancement in LLMs | ['Zhuoshi Pan', 'Yu Li', 'Honglin Lin', 'Qizhi Pei', 'Zinan Tang', 'Wei Wu', 'Chenlin Ming', 'H. Vicky Zhao', 'Conghui He', 'Lijun Wu'] | ['cs.LG', 'cs.AI'] | Large language models (LLMs) have demonstrated remarkable reasoning
capability in solving mathematical problems. However, existing approaches
primarily focus on improving the quality of correct training data, e.g.,
distilling high-quality correct solutions from advanced models, neglecting the
value contained in error d... | 2025-03-21T17:59:10Z | ACL'25 Findings, Code is available at https://github.com/pzs19/LEMMA | null | null | LEMMA: Learning from Errors for MatheMatical Advancement in LLMs | ['Zhuoshi Pan', 'Yu Li', 'Honglin Lin', 'Qizhi Pei', 'Zinan Tang', 'Wei Wu', 'Chenlin Ming', 'H. V. Zhao', 'Conghui He', 'Lijun Wu'] | 2,025 | arXiv.org | 6 | 71 | ['Computer Science'] |
2,503.17577 | Measuring the Robustness of Audio Deepfake Detectors | ['Xiang Li', 'Pin-Yu Chen', 'Wenqi Wei'] | ['cs.CR', 'cs.AI', 'cs.SD'] | Deepfakes have become a universal and rapidly intensifying concern of
generative AI across various media types such as images, audio, and videos.
Among these, audio deepfakes have been of particular concern due to the ease of
high-quality voice synthesis and distribution via platforms such as social
media and robocalls... | 2025-03-21T23:21:17Z | null | null | null | Measuring the Robustness of Audio Deepfake Detectors | ['Xiang Li', 'Pin-Yu Chen', 'Wenqi Wei'] | 2,025 | arXiv.org | 0 | 44 | ['Computer Science'] |
2,503.1776 | CODA: Repurposing Continuous VAEs for Discrete Tokenization | ['Zeyu Liu', 'Zanlin Ni', 'Yeguo Hua', 'Xin Deng', 'Xiao Ma', 'Cheng Zhong', 'Gao Huang'] | ['cs.CV', 'cs.AI'] | Discrete visual tokenizers transform images into a sequence of tokens,
enabling token-based visual generation akin to language models. However, this
process is inherently challenging, as it requires both compressing visual
signals into a compact representation and discretizing them into a fixed set of
codes. Traditiona... | 2025-03-22T12:59:00Z | Project page: https://lzy-tony.github.io/coda | null | null | null | null | null | null | null | null | null |
2,503.17793 | Every Sample Matters: Leveraging Mixture-of-Experts and High-Quality
Data for Efficient and Accurate Code LLM | ['Codefuse', 'Ling Team', ':', 'Wenting Cai', 'Yuchen Cao', 'Chaoyu Chen', 'Chen Chen', 'Siba Chen', 'Qing Cui', 'Peng Di', 'Junpeng Fang', 'Zi Gong', 'Ting Guo', 'Zhengyu He', 'Yang Huang', 'Cong Li', 'Jianguo Li', 'Zheng Li', 'Shijie Lian', 'BingChang Liu', 'Songshan Luo', 'Shuo Mao', 'Min Shen', 'Jian Wu', 'Jiaolong... | ['cs.LG', 'cs.AI', 'cs.CL', 'I.2.7'] | Recent advancements in code large language models (LLMs) have demonstrated
remarkable capabilities in code generation and understanding. It is still
challenging to build a code LLM with comprehensive performance yet ultimate
efficiency. Many attempts have been released in the open source community to
break the trade-of... | 2025-03-22T15:00:18Z | 20 pages, 6 figures | null | null | null | null | null | null | null | null | null |
2,503.17963 | Won: Establishing Best Practices for Korean Financial NLP | ['Guijin Son', 'Hyunwoo Ko', 'Haneral Jung', 'Chami Hwang'] | ['cs.CL'] | In this work, we present the first open leaderboard for evaluating Korean
large language models focused on finance. Operated for about eight weeks, the
leaderboard evaluated 1,119 submissions on a closed benchmark covering five
MCQA categories: finance and accounting, stock price prediction, domestic
company analysis, ... | 2025-03-23T06:52:38Z | The training dataset is uploaded here:
https://huggingface.co/datasets/KRX-Data/Won-Instruct. The model will be
updated shortly | null | null | null | null | null | null | null | null | null |
2,503.18013 | Vision-R1: Evolving Human-Free Alignment in Large Vision-Language Models
via Vision-Guided Reinforcement Learning | ['Yufei Zhan', 'Yousong Zhu', 'Shurong Zheng', 'Hongyin Zhao', 'Fan Yang', 'Ming Tang', 'Jinqiao Wang'] | ['cs.CV', 'cs.AI'] | Large Vision-Language Models (LVLMs) typically follow a two-stage training
paradigm-pretraining and supervised fine-tuning. Recently, preference
optimization, derived from the language domain, has emerged as an effective
post-training reinforcement strategy to enhance capabilities of LVLMs. However,
constructing high-q... | 2025-03-23T10:21:14Z | Project in development. Github:
https://github.com/jefferyZhan/Griffon/tree/master/Vision-R1 | null | null | null | null | null | null | null | null | null |
2,503.18069 | Long Is More Important Than Difficult for Training Reasoning Models | ['Si Shen', 'Fei Huang', 'Zhixiao Zhao', 'Chang Liu', 'Tiansheng Zheng', 'Danhao Zhu'] | ['cs.CL'] | Difficult problems, which often result in long reasoning traces, are widely
recognized as key factors for enhancing the performance of reasoning models.
However, such high-challenge problems are scarce, limiting the size of
available datasets. In this paper, we propose a simple method to decouple the
reliance on proble... | 2025-03-23T13:33:59Z | 15 pages,6 figures | null | null | Long Is More Important Than Difficult for Training Reasoning Models | ['Si Shen', 'Fei Huang', 'Zhixiao Zhao', 'Chang Liu', 'Tiansheng Zheng', 'Danhao Zhu'] | 2,025 | arXiv.org | 0 | 24 | ['Computer Science'] |
2,503.18406 | Instruct-CLIP: Improving Instruction-Guided Image Editing with Automated
Data Refinement Using Contrastive Learning | ['Sherry X. Chen', 'Misha Sra', 'Pradeep Sen'] | ['cs.CV'] | Although natural language instructions offer an intuitive way to guide
automated image editing, deep-learning models often struggle to achieve
high-quality results, largely due to the difficulty of creating large,
high-quality training datasets. To do this, previous approaches have typically
relied on text-to-image (T2... | 2025-03-24T07:25:44Z | Computer Vision and Pattern Recognition 2025 | null | null | null | null | null | null | null | null | null |
2,503.18435 | On the Perception Bottleneck of VLMs for Chart Understanding | ['Junteng Liu', 'Weihao Zeng', 'Xiwen Zhang', 'Yijun Wang', 'Zifei Shan', 'Junxian He'] | ['cs.CV', 'cs.CL'] | Chart understanding requires models to effectively analyze and reason about
numerical data, textual elements, and complex visual components. Our
observations reveal that the perception capabilities of existing large
vision-language models (LVLMs) constitute a critical bottleneck in this
process. In this study, we delve... | 2025-03-24T08:33:58Z | null | null | null | On the Perception Bottleneck of VLMs for Chart Understanding | ['Junteng Liu', 'Weihao Zeng', 'Xiwen Zhang', 'Yijun Wang', 'Zifei Shan', 'Junxian He'] | 2,025 | arXiv.org | 0 | 38 | ['Computer Science'] |
2,503.18478 | Video-XL-Pro: Reconstructive Token Compression for Extremely Long Video
Understanding | ['Xiangrui Liu', 'Yan Shu', 'Zheng Liu', 'Ao Li', 'Yang Tian', 'Bo Zhao'] | ['cs.CV'] | Despite advanced token compression techniques, existing multimodal large
language models (MLLMs) still struggle with hour-long video understanding. In
this work, we propose Video-XL-Pro, an efficient method for extremely long
video understanding, built upon Reconstructive Compression of Tokens (ReCoT), a
learnable modu... | 2025-03-24T09:21:48Z | null | null | null | Video-XL-Pro: Reconstructive Token Compression for Extremely Long Video Understanding | ['Xiangrui Liu', 'Yan Shu', 'Zheng Liu', 'Ao Li', 'Yang Tian', 'Bo Zhao'] | 2,025 | arXiv.org | 9 | 62 | ['Computer Science'] |
2,503.18594 | ClinText-SP and RigoBERTa Clinical: a new set of open resources for
Spanish Clinical NLP | ['Guillem García Subies', 'Álvaro Barbero Jiménez', 'Paloma Martínez Fernández'] | ['cs.CL', 'cs.AI'] | We present a novel contribution to Spanish clinical natural language
processing by introducing the largest publicly available clinical corpus,
ClinText-SP, along with a state-of-the-art clinical encoder language model,
RigoBERTa Clinical. Our corpus was meticulously curated from diverse open
sources, including clinical... | 2025-03-24T11:52:17Z | null | null | null | ClinText-SP and RigoBERTa Clinical: a new set of open resources for Spanish Clinical NLP | ['Guillem García Subies', 'Álvaro Barbero Jiménez', 'Paloma Martínez'] | 2,025 | arXiv.org | 0 | 52 | ['Computer Science'] |
2,503.18712 | LLaVAction: evaluating and training multi-modal large language models
for action recognition | ['Shaokai Ye', 'Haozhe Qi', 'Alexander Mathis', 'Mackenzie W. Mathis'] | ['cs.CV'] | Understanding human behavior requires measuring behavioral actions. Due to
its complexity, behavior is best mapped onto a rich, semantic structure such as
language. The recent development of multi-modal large language models (MLLMs)
is a promising candidate for a wide range of action understanding tasks. In
this work, ... | 2025-03-24T14:24:17Z | https://github.com/AdaptiveMotorControlLab/LLaVAction | null | null | LLaVAction: evaluating and training multi-modal large language models for action recognition | ['Shaokai Ye', 'Haozhe Qi', 'Alexander Mathis', 'Mackenzie W. Mathis'] | 2,025 | arXiv.org | 1 | 79 | ['Computer Science'] |
2,503.18738 | RoboEngine: Plug-and-Play Robot Data Augmentation with Semantic Robot
Segmentation and Background Generation | ['Chengbo Yuan', 'Suraj Joshi', 'Shaoting Zhu', 'Hang Su', 'Hang Zhao', 'Yang Gao'] | ['cs.RO'] | Visual augmentation has become a crucial technique for enhancing the visual
robustness of imitation learning. However, existing methods are often limited
by prerequisites such as camera calibration or the need for controlled
environments (e.g., green screen setups). In this work, we introduce
RoboEngine, the first plug... | 2025-03-24T14:46:14Z | Project Page: https://roboengine.github.io/ | null | null | null | null | null | null | null | null | null |
2,503.18769 | AlphaSpace: Enabling Robotic Actions through Semantic Tokenization and
Symbolic Reasoning | ['Alan Dao', 'Dinh Bach Vu', 'Bui Quang Huy'] | ['cs.CL', 'cs.RO'] | This paper presents AlphaSpace, a novel methodology designed to enhance the
spatial reasoning capabilities of language models for robotic manipulation in
3D Cartesian space. AlphaSpace employs a hierarchical semantics-based
tokenization strategy that encodes spatial information at both coarse and
fine-grained levels. O... | 2025-03-24T15:16:51Z | null | null | null | null | null | null | null | null | null | null |
2,503.18794 | NexusGS: Sparse View Synthesis with Epipolar Depth Priors in 3D Gaussian
Splatting | ['Yulong Zheng', 'Zicheng Jiang', 'Shengfeng He', 'Yandu Sun', 'Junyu Dong', 'Huaidong Zhang', 'Yong Du'] | ['cs.CV'] | Neural Radiance Field (NeRF) and 3D Gaussian Splatting (3DGS) have noticeably
advanced photo-realistic novel view synthesis using images from densely spaced
camera viewpoints. However, these methods struggle in few-shot scenarios due to
limited supervision. In this paper, we present NexusGS, a 3DGS-based approach
that ... | 2025-03-24T15:40:17Z | This paper is accepted by CVPR 2025 | null | null | null | null | null | null | null | null | null |
2,503.18817 | Enhanced OoD Detection through Cross-Modal Alignment of Multi-Modal
Representations | ['Jeonghyeon Kim', 'Sangheum Hwang'] | ['cs.CV', 'cs.AI'] | Prior research on out-of-distribution detection (OoDD) has primarily focused
on single-modality models. Recently, with the advent of large-scale pretrained
vision-language models such as CLIP, OoDD methods utilizing such multi-modal
representations through zero-shot and prompt learning strategies have emerged.
However,... | 2025-03-24T16:00:21Z | CVPR 2025 | null | null | null | null | null | null | null | null | null |
2,503.1886 | HunyuanPortrait: Implicit Condition Control for Enhanced Portrait
Animation | ['Zunnan Xu', 'Zhentao Yu', 'Zixiang Zhou', 'Jun Zhou', 'Xiaoyu Jin', 'Fa-Ting Hong', 'Xiaozhong Ji', 'Junwei Zhu', 'Chengfei Cai', 'Shiyu Tang', 'Qin Lin', 'Xiu Li', 'Qinglin Lu'] | ['cs.CV'] | We introduce HunyuanPortrait, a diffusion-based condition control method that
employs implicit representations for highly controllable and lifelike portrait
animation. Given a single portrait image as an appearance reference and video
clips as driving templates, HunyuanPortrait can animate the character in the
referenc... | 2025-03-24T16:35:41Z | Accepted to CVPR 2025 | null | null | null | null | null | null | null | null | null |
2,503.18872 | Curriculum Coarse-to-Fine Selection for High-IPC Dataset Distillation | ['Yanda Chen', 'Gongwei Chen', 'Miao Zhang', 'Weili Guan', 'Liqiang Nie'] | ['cs.CV'] | Dataset distillation (DD) excels in synthesizing a small number of images per
class (IPC) but struggles to maintain its effectiveness in high-IPC settings.
Recent works on dataset distillation demonstrate that combining distilled and
real data can mitigate the effectiveness decay. However, our analysis of the
combinati... | 2025-03-24T16:47:40Z | Accepted by CVPR2025 | null | null | null | null | null | null | null | null | null |
2,503.18878 | I Have Covered All the Bases Here: Interpreting Reasoning Features in
Large Language Models via Sparse Autoencoders | ['Andrey Galichin', 'Alexey Dontsov', 'Polina Druzhinina', 'Anton Razzhigaev', 'Oleg Y. Rogov', 'Elena Tutubalina', 'Ivan Oseledets'] | ['cs.CL'] | Large Language Models (LLMs) have achieved remarkable success in natural
language processing. Recent advances have led to the developing of a new class
of reasoning LLMs; for example, open-source DeepSeek-R1 has achieved
state-of-the-art performance by integrating deep thinking and complex
reasoning. Despite these impr... | 2025-03-24T16:54:26Z | null | null | null | null | null | null | null | null | null | null |
2,503.18908 | FFN Fusion: Rethinking Sequential Computation in Large Language Models | ['Akhiad Bercovich', 'Mohammad Dabbah', 'Omri Puny', 'Ido Galil', 'Amnon Geifman', 'Yonatan Geifman', 'Izhak Golan', 'Ehud Karpas', 'Itay Levy', 'Zach Moshe', 'Najeeb Nabwani', 'Tomer Ronen', 'Itamar Schen', 'Elad Segal', 'Ido Shahaf', 'Oren Tropp', 'Ran Zilberstein', 'Ran El-Yaniv'] | ['cs.LG'] | We introduce FFN Fusion, an architectural optimization technique that reduces
sequential computation in large language models by identifying and exploiting
natural opportunities for parallelization. Our key insight is that sequences of
Feed-Forward Network (FFN) layers, particularly those remaining after the
removal of... | 2025-03-24T17:20:35Z | null | null | null | null | null | null | null | null | null | null |
2,503.18931 | CoMP: Continual Multimodal Pre-training for Vision Foundation Models | ['Yitong Chen', 'Lingchen Meng', 'Wujian Peng', 'Zuxuan Wu', 'Yu-Gang Jiang'] | ['cs.CV'] | Pre-trained Vision Foundation Models (VFMs) provide strong visual
representations for a wide range of applications. In this paper, we continually
pre-train prevailing VFMs in a multimodal manner such that they can
effortlessly process visual inputs of varying sizes and produce visual
representations that are more align... | 2025-03-24T17:52:47Z | Code is available in https://github.com/SliMM-X/CoMP-MM | null | null | null | null | null | null | null | null | null |
2,503.18938 | AdaWorld: Learning Adaptable World Models with Latent Actions | ['Shenyuan Gao', 'Siyuan Zhou', 'Yilun Du', 'Jun Zhang', 'Chuang Gan'] | ['cs.AI', 'cs.CV', 'cs.LG', 'cs.RO'] | World models aim to learn action-controlled future prediction and have proven
essential for the development of intelligent agents. However, most existing
world models rely heavily on substantial action-labeled data and costly
training, making it challenging to adapt to novel environments with
heterogeneous actions thro... | 2025-03-24T17:58:15Z | ICML 2025. Project page: https://adaptable-world-model.github.io/,
code: https://github.com/Little-Podi/AdaWorld, model:
https://huggingface.co/Little-Podi/AdaWorld | null | null | null | null | null | null | null | null | null |
2,503.18945 | Aether: Geometric-Aware Unified World Modeling | ['Aether Team', 'Haoyi Zhu', 'Yifan Wang', 'Jianjun Zhou', 'Wenzheng Chang', 'Yang Zhou', 'Zizun Li', 'Junyi Chen', 'Chunhua Shen', 'Jiangmiao Pang', 'Tong He'] | ['cs.CV', 'cs.AI', 'cs.LG', 'cs.RO'] | The integration of geometric reconstruction and generative modeling remains a
critical challenge in developing AI systems capable of human-like spatial
reasoning. This paper proposes Aether, a unified framework that enables
geometry-aware reasoning in world models by jointly optimizing three core
capabilities: (1) 4D d... | 2025-03-24T17:59:51Z | Project Page: https://aether-world.github.io/ | null | null | null | null | null | null | null | null | null |
2,503.18948 | Equivariant Image Modeling | ['Ruixiao Dong', 'Mengde Xu', 'Zigang Geng', 'Li Li', 'Han Hu', 'Shuyang Gu'] | ['cs.CV'] | Current generative models, such as autoregressive and diffusion approaches,
decompose high-dimensional data distribution learning into a series of simpler
subtasks. However, inherent conflicts arise during the joint optimization of
these subtasks, and existing solutions fail to resolve such conflicts without
sacrificin... | 2025-03-24T17:59:57Z | null | null | null | null | null | null | null | null | null | null |
2,503.19062 | Color Transfer with Modulated Flows | ['Maria Larchenko', 'Alexander Lobashev', 'Dmitry Guskov', 'Vladimir Vladimirovich Palyulin'] | ['cs.CV'] | In this work, we introduce Modulated Flows (ModFlows), a novel approach for
color transfer between images based on rectified flows. The primary goal of the
color transfer is to adjust the colors of a target image to match the color
distribution of a reference image. Our technique is based on optimal transport
and execu... | 2025-03-24T18:39:54Z | AAAI 2025 | Proceedings of the AAAI Conference on Artificial Intelligence,
39(4), 4464-4472 (2025) | 10.1609/aaai.v39i4.32470 | Color Transfer with Modulated Flows | ['Maria Larchenko', 'Alexander Lobashev', 'Dmitry Guskov', 'V. V. Palyulin'] | 2,025 | AAAI Conference on Artificial Intelligence | 0 | 35 | ['Computer Science'] |
2,503.19325 | Long-Context Autoregressive Video Modeling with Next-Frame Prediction | ['Yuchao Gu', 'Weijia Mao', 'Mike Zheng Shou'] | ['cs.CV'] | Long-context video modeling is essential for enabling generative models to
function as world simulators, as they must maintain temporal coherence over
extended time spans. However, most existing models are trained on short clips,
limiting their ability to capture long-range dependencies, even with test-time
extrapolati... | 2025-03-25T03:38:06Z | Project page at https://farlongctx.github.io/ | null | null | Long-Context Autoregressive Video Modeling with Next-Frame Prediction | ['Yuchao Gu', 'Weijia Mao', 'Mike Zheng Shou'] | 2,025 | arXiv.org | 11 | 75 | ['Computer Science'] |
2,503.19462 | AccVideo: Accelerating Video Diffusion Model with Synthetic Dataset | ['Haiyu Zhang', 'Xinyuan Chen', 'Yaohui Wang', 'Xihui Liu', 'Yunhong Wang', 'Yu Qiao'] | ['cs.CV'] | Diffusion models have achieved remarkable progress in the field of video
generation. However, their iterative denoising nature requires a large number
of inference steps to generate a video, which is slow and computationally
expensive. In this paper, we begin with a detailed analysis of the challenges
present in existi... | 2025-03-25T08:52:07Z | Project Page: https://aejion.github.io/accvideo/ | null | null | AccVideo: Accelerating Video Diffusion Model with Synthetic Dataset | ['Haiyu Zhang', 'Xinyuan Chen', 'Yaohui Wang', 'Xihui Liu', 'Yunhong Wang', 'Yu Qiao'] | 2,025 | arXiv.org | 1 | 64 | ['Computer Science'] |
2,503.1947 | ReSearch: Learning to Reason with Search for LLMs via Reinforcement
Learning | ['Mingyang Chen', 'Tianpeng Li', 'Haoze Sun', 'Yijie Zhou', 'Chenzheng Zhu', 'Haofen Wang', 'Jeff Z. Pan', 'Wen Zhang', 'Huajun Chen', 'Fan Yang', 'Zenan Zhou', 'Weipeng Chen'] | ['cs.AI', 'cs.CL'] | Large Language Models (LLMs) have shown remarkable capabilities in reasoning,
exemplified by the success of OpenAI-o1 and DeepSeek-R1. However, integrating
reasoning with external search processes remains challenging, especially for
complex multi-hop questions requiring multiple retrieval steps. We propose
ReSearch, a ... | 2025-03-25T09:00:58Z | Work in progress | null | null | null | null | null | null | null | null | null |
2,503.1948 | GenHancer: Imperfect Generative Models are Secretly Strong
Vision-Centric Enhancers | ['Shijie Ma', 'Yuying Ge', 'Teng Wang', 'Yuxin Guo', 'Yixiao Ge', 'Ying Shan'] | ['cs.CV'] | The synergy between generative and discriminative models receives growing
attention. While discriminative Contrastive Language-Image Pre-Training (CLIP)
excels in high-level semantics, it struggles with perceiving fine-grained
visual details. Generally, to enhance representations, generative models take
CLIP's visual f... | 2025-03-25T09:15:34Z | Project released at: https://mashijie1028.github.io/GenHancer/ | null | null | null | null | null | null | null | null | null |
2,503.19633 | 1.4 Million Open-Source Distilled Reasoning Dataset to Empower Large
Language Model Training | ['Han Zhao', 'Haotian Wang', 'Yiping Peng', 'Sitong Zhao', 'Xiaoyu Tian', 'Shuaiting Chen', 'Yunjie Ji', 'Xiangang Li'] | ['cs.CL'] | The AM-DeepSeek-R1-Distilled is a large-scale dataset with thinking traces
for general reasoning tasks, composed of high-quality and challenging reasoning
problems. These problems are collected from a multitude of open-source
datasets, subjected to semantic deduplication and meticulous cleaning to
eliminate test set co... | 2025-03-25T13:19:46Z | null | null | null | null | null | null | null | null | null | null |
2,503.19653 | OpenSDI: Spotting Diffusion-Generated Images in the Open World | ['Yabin Wang', 'Zhiwu Huang', 'Xiaopeng Hong'] | ['cs.CV', 'cs.AI'] | This paper identifies OpenSDI, a challenge for spotting diffusion-generated
images in open-world settings. In response to this challenge, we define a new
benchmark, the OpenSDI dataset (OpenSDID), which stands out from existing
datasets due to its diverse use of large vision-language models that simulate
open-world dif... | 2025-03-25T13:43:16Z | null | null | null | OpenSDI: Spotting Diffusion-Generated Images in the Open World | ['Yabin Wang', 'Zhiwu Huang', 'Xiaopeng Hong'] | 2,025 | Computer Vision and Pattern Recognition | 0 | 0 | ['Computer Science'] |
2,503.19683 | Unlocking the Hidden Potential of CLIP in Generalizable Deepfake
Detection | ['Andrii Yermakov', 'Jan Cech', 'Jiri Matas'] | ['cs.CV'] | This paper tackles the challenge of detecting partially manipulated facial
deepfakes, which involve subtle alterations to specific facial features while
retaining the overall context, posing a greater detection difficulty than fully
synthetic faces. We leverage the Contrastive Language-Image Pre-training (CLIP)
model, ... | 2025-03-25T14:10:54Z | null | null | null | Unlocking the Hidden Potential of CLIP in Generalizable Deepfake Detection | ['Andrii Yermakov', 'Jan Cech', 'Jiri Matas'] | 2,025 | arXiv.org | 1 | 38 | ['Computer Science'] |
2,503.19739 | FUSE: Label-Free Image-Event Joint Monocular Depth Estimation via
Frequency-Decoupled Alignment and Degradation-Robust Fusion | ['Pihai Sun', 'Junjun Jiang', 'Yuanqi Yao', 'Youyu Chen', 'Wenbo Zhao', 'Kui Jiang', 'Xianming Liu'] | ['cs.CV'] | Image-event joint depth estimation methods leverage complementary modalities
for robust perception, yet face challenges in generalizability stemming from
two factors: 1) limited annotated image-event-depth datasets causing
insufficient cross-modal supervision, and 2) inherent frequency mismatches
between static images ... | 2025-03-25T15:04:53Z | 8 pages, 6 figures | null | null | FUSE: Label-Free Image-Event Joint Monocular Depth Estimation via Frequency-Decoupled Alignment and Degradation-Robust Fusion | ['Pihai Sun', 'Junjun Jiang', 'Yuanqi Yao', 'Youyu Chen', 'Wenbo Zhao', 'Kui Jiang', 'Xianming Liu'] | 2,025 | arXiv.org | 0 | 36 | ['Computer Science'] |
2,503.1974 | Surg-3M: A Dataset and Foundation Model for Perception in Surgical
Settings | ['Chengan Che', 'Chao Wang', 'Tom Vercauteren', 'Sophia Tsoka', 'Luis C. Garcia-Peraza-Herrera'] | ['cs.CV'] | Advancements in computer-assisted surgical procedures heavily rely on
accurate visual data interpretation from camera systems used during surgeries.
Traditional open-access datasets focusing on surgical procedures are often
limited by their small size, typically consisting of fewer than 100 videos with
less than 100K i... | 2025-03-25T15:05:00Z | 15 pages | null | null | null | null | null | null | null | null | null |
2,503.19786 | Gemma 3 Technical Report | ['Gemma Team', 'Aishwarya Kamath', 'Johan Ferret', 'Shreya Pathak', 'Nino Vieillard', 'Ramona Merhej', 'Sarah Perrin', 'Tatiana Matejovicova', 'Alexandre Ramé', 'Morgane Rivière', 'Louis Rouillard', 'Thomas Mesnard', 'Geoffrey Cideron', 'Jean-bastien Grill', 'Sabela Ramos', 'Edouard Yvinec', 'Michelle Casbon', 'Etienne... | ['cs.CL', 'cs.AI'] | We introduce Gemma 3, a multimodal addition to the Gemma family of
lightweight open models, ranging in scale from 1 to 27 billion parameters. This
version introduces vision understanding abilities, a wider coverage of
languages and longer context - at least 128K tokens. We also change the
architecture of the model to r... | 2025-03-25T15:52:34Z | null | null | null | null | null | null | null | null | null | null |
2,503.19794 | PAVE: Patching and Adapting Video Large Language Models | ['Zhuoming Liu', 'Yiquan Li', 'Khoi Duc Nguyen', 'Yiwu Zhong', 'Yin Li'] | ['cs.CV', 'cs.AI', 'cs.LG'] | Pre-trained video large language models (Video LLMs) exhibit remarkable
reasoning capabilities, yet adapting these models to new tasks involving
additional modalities or data types (e.g., audio or 3D information) remains
challenging. In this paper, we present PAVE, a flexible framework for adapting
pre-trained Video LL... | 2025-03-25T16:02:37Z | CVPR2025 Camera Ready | null | null | PAVE: Patching and Adapting Video Large Language Models | ['Zhuoming Liu', 'Yiquan Li', 'Khoi Duc Nguyen', 'Yiwu Zhong', 'Yin Li'] | 2,025 | Computer Vision and Pattern Recognition | 1 | 81 | ['Computer Science'] |
2,503.19821 | IgCraft: A versatile sequence generation framework for antibody
discovery and engineering | ['Matthew Greenig', 'Haowen Zhao', 'Vladimir Radenkovic', 'Aubin Ramon', 'Pietro Sormanni'] | ['q-bio.BM', 'cs.LG', 'q-bio.QM'] | Designing antibody sequences to better resemble those observed in natural
human repertoires is a key challenge in biologics development. We introduce
IgCraft: a multi-purpose model for paired human antibody sequence generation,
built on Bayesian Flow Networks. IgCraft presents one of the first unified
generative modeli... | 2025-03-25T16:32:03Z | null | null | null | IgCraft: A versatile sequence generation framework for antibody discovery and engineering | ['Matthew Greenig', 'Haowen Zhao', 'Vladimir Radenkovic', 'Aubin Ramon', 'P. Sormanni'] | 2,025 | arXiv.org | 2 | 45 | ['Computer Science', 'Biology'] |
2,503.19868 | GENIUS: A Generative Framework for Universal Multimodal Search | ['Sungyeon Kim', 'Xinliang Zhu', 'Xiaofan Lin', 'Muhammet Bastan', 'Douglas Gray', 'Suha Kwak'] | ['cs.IR', 'cs.AI', 'cs.CV', 'cs.LG'] | Generative retrieval is an emerging approach in information retrieval that
generates identifiers (IDs) of target data based on a query, providing an
efficient alternative to traditional embedding-based retrieval methods.
However, existing models are task-specific and fall short of embedding-based
retrieval in performan... | 2025-03-25T17:32:31Z | Accepted to CVPR 2025 | null | null | GENIUS: A Generative Framework for Universal Multimodal Search | ['Sungyeon Kim', 'Xinliang Zhu', 'Xiaofan Lin', 'Muhammet Bastan', 'Douglas Gray', 'Suha Kwak'] | 2,025 | arXiv.org | 0 | 62 | ['Computer Science'] |
2,503.19901 | TokenHSI: Unified Synthesis of Physical Human-Scene Interactions through
Task Tokenization | ['Liang Pan', 'Zeshi Yang', 'Zhiyang Dou', 'Wenjia Wang', 'Buzhen Huang', 'Bo Dai', 'Taku Komura', 'Jingbo Wang'] | ['cs.CV'] | Synthesizing diverse and physically plausible Human-Scene Interactions (HSI)
is pivotal for both computer animation and embodied AI. Despite encouraging
progress, current methods mainly focus on developing separate controllers, each
specialized for a specific interaction task. This significantly hinders the
ability to ... | 2025-03-25T17:57:46Z | CVPR 2025 | null | null | TokenHSI: Unified Synthesis of Physical Human-Scene Interactions through Task Tokenization | ['Liang Pan', 'Zeshi Yang', 'Zhiyang Dou', 'Wenjia Wang', 'Buzhen Huang', 'Bo Dai', 'Taku Komura', 'Jingbo Wang'] | 2,025 | Computer Vision and Pattern Recognition | 5 | 131 | ['Computer Science'] |
2,503.19903 | Scaling Vision Pre-Training to 4K Resolution | ['Baifeng Shi', 'Boyi Li', 'Han Cai', 'Yao Lu', 'Sifei Liu', 'Marco Pavone', 'Jan Kautz', 'Song Han', 'Trevor Darrell', 'Pavlo Molchanov', 'Hongxu Yin'] | ['cs.CV'] | High-resolution perception of visual details is crucial for daily tasks.
Current vision pre-training, however, is still limited to low resolutions
(e.g., 378 x 378 pixels) due to the quadratic cost of processing larger images.
We introduce PS3 that scales CLIP-style vision pre-training to 4K resolution
with a near-cons... | 2025-03-25T17:58:37Z | CVPR 2025. Project Page: https://nvlabs.github.io/PS3 | null | null | null | null | null | null | null | null | null |
2,503.19906 | AvatarArtist: Open-Domain 4D Avatarization | ['Hongyu Liu', 'Xuan Wang', 'Ziyu Wan', 'Yue Ma', 'Jingye Chen', 'Yanbo Fan', 'Yujun Shen', 'Yibing Song', 'Qifeng Chen'] | ['cs.CV'] | This work focuses on open-domain 4D avatarization, with the purpose of
creating a 4D avatar from a portrait image in an arbitrary style. We select
parametric triplanes as the intermediate 4D representation and propose a
practical training paradigm that takes advantage of both generative adversarial
networks (GANs) and ... | 2025-03-25T17:59:03Z | Accepted to CVPR 2025. Project page:
https://kumapowerliu.github.io/AvatarArtist | null | null | AvatarArtist: Open-Domain 4D Avatarization | ['Hongyu Liu', 'Xuan Wang', 'Ziyu Wan', 'Yue Ma', 'Jingye Chen', 'Yanbo Fan', 'Yujun Shen', 'Yibing Song', 'Qifeng Chen'] | 2,025 | arXiv.org | 3 | 86 | ['Computer Science'] |
2,503.19988 | ExCoT: Optimizing Reasoning for Text-to-SQL with Execution Feedback | ['Bohan Zhai', 'Canwen Xu', 'Yuxiong He', 'Zhewei Yao'] | ['cs.LG', 'cs.AI', 'cs.DB'] | Text-to-SQL demands precise reasoning to convert natural language questions
into structured queries. While large language models (LLMs) excel in many
reasoning tasks, their ability to leverage Chain-of-Thought (CoT) reasoning for
text-to-SQL remains underexplored. We identify critical limitations: zero-shot
CoT offers ... | 2025-03-25T18:17:36Z | null | null | null | ExCoT: Optimizing Reasoning for Text-to-SQL with Execution Feedback | ['Bohan Zhai', 'Canwen Xu', 'Yuxiong He', 'Zhewei Yao'] | 2,025 | arXiv.org | 2 | 28 | ['Computer Science'] |
2,503.2 | The Coralscapes Dataset: Semantic Scene Understanding in Coral Reefs | ['Jonathan Sauder', 'Viktor Domazetoski', 'Guilhem Banc-Prandi', 'Gabriela Perna', 'Anders Meibom', 'Devis Tuia'] | ['cs.CV', 'cs.LG'] | Coral reefs are declining worldwide due to climate change and local
stressors. To inform effective conservation or restoration, monitoring at the
highest possible spatial and temporal resolution is necessary. Conventional
coral reef surveying methods are limited in scalability due to their reliance
on expert labor time... | 2025-03-25T18:33:59Z | null | null | null | null | null | null | null | null | null | null |
2,503.20083 | Universal Cross-Tokenizer Distillation via Approximate Likelihood
Matching | ['Benjamin Minixhofer', 'Ivan Vulić', 'Edoardo Maria Ponti'] | ['cs.CL'] | Distillation has shown remarkable success in transferring knowledge from a
Large Language Model (LLM) teacher to a student LLM. However, current
distillation methods require similar tokenizers between the teacher and the
student, restricting their applicability to only a small subset of
teacher-student pairs. In this w... | 2025-03-25T21:44:10Z | Preprint, 21 pages | null | null | Universal Cross-Tokenizer Distillation via Approximate Likelihood Matching | ['Benjamin Minixhofer', 'E. Ponti', "Ivan Vuli'c"] | 2,025 | null | 3 | 57 | ['Computer Science'] |
2,503.20212 | Dolphin: A Large-Scale Automatic Speech Recognition Model for Eastern
Languages | ['Yangyang Meng', 'Jinpeng Li', 'Guodong Lin', 'Yu Pu', 'Guanbo Wang', 'Hu Du', 'Zhiming Shao', 'Yukai Huang', 'Ke Li', 'Wei-Qiang Zhang'] | ['cs.CL', 'eess.AS'] | This report introduces Dolphin, a large-scale multilingual automatic speech
recognition (ASR) model that extends the Whisper architecture to support a
wider range of languages. Our approach integrates in-house proprietary and
open-source datasets to refine and optimize Dolphin's performance. The model is
specifically d... | 2025-03-26T04:14:03Z | null | null | null | null | null | null | null | null | null | null |
2,503.20215 | Qwen2.5-Omni Technical Report | ['Jin Xu', 'Zhifang Guo', 'Jinzheng He', 'Hangrui Hu', 'Ting He', 'Shuai Bai', 'Keqin Chen', 'Jialin Wang', 'Yang Fan', 'Kai Dang', 'Bin Zhang', 'Xiong Wang', 'Yunfei Chu', 'Junyang Lin'] | ['cs.CL', 'cs.CV', 'cs.SD', 'eess.AS'] | In this report, we present Qwen2.5-Omni, an end-to-end multimodal model
designed to perceive diverse modalities, including text, images, audio, and
video, while simultaneously generating text and natural speech responses in a
streaming manner. To enable the streaming of multimodal information inputs,
both audio and vis... | 2025-03-26T04:17:55Z | null | null | null | null | null | null | null | null | null | null |
2,503.20314 | Wan: Open and Advanced Large-Scale Video Generative Models | ['Team Wan', 'Ang Wang', 'Baole Ai', 'Bin Wen', 'Chaojie Mao', 'Chen-Wei Xie', 'Di Chen', 'Feiwu Yu', 'Haiming Zhao', 'Jianxiao Yang', 'Jianyuan Zeng', 'Jiayu Wang', 'Jingfeng Zhang', 'Jingren Zhou', 'Jinkai Wang', 'Jixuan Chen', 'Kai Zhu', 'Kang Zhao', 'Keyu Yan', 'Lianghua Huang', 'Mengyang Feng', 'Ningyi Zhang', 'Pa... | ['cs.CV'] | This report presents Wan, a comprehensive and open suite of video foundation
models designed to push the boundaries of video generation. Built upon the
mainstream diffusion transformer paradigm, Wan achieves significant
advancements in generative capabilities through a series of innovations,
including our novel VAE, sc... | 2025-03-26T08:25:43Z | 60 pages, 33 figures | null | null | null | null | null | null | null | null | null |
2,503.20376 | Dewey Long Context Embedding Model: A Technical Report | ['Dun Zhang', 'Panxiang Zou', 'Yudong Zhou'] | ['cs.IR'] | This technical report presents the training methodology and evaluation
results of the open-source dewey_en_beta embedding model. The increasing demand
for retrieval-augmented generation (RAG) systems and the expanding context
window capabilities of large language models (LLMs) have created critical
challenges for conve... | 2025-03-26T09:55:00Z | 5 pages, 1 figure | null | null | null | null | null | null | null | null | null |
2,503.20417 | CFunModel: A "Funny" Language Model Capable of Chinese Humor Generation
and Processing | ['Zhenghan Yu', 'Xinyu Hu', 'Xiaojun Wan'] | ['cs.CL'] | Humor plays a significant role in daily language communication. With the
rapid development of large language models (LLMs), natural language processing
has made significant strides in understanding and generating various genres of
texts. However, most LLMs exhibit poor performance in generating and processing
Chinese h... | 2025-03-26T10:44:51Z | 9 pages | null | null | null | null | null | null | null | null | null |
2,503.20429 | Latent Beam Diffusion Models for Decoding Image Sequences | ['Guilherme Fernandes', 'Vasco Ramos', 'Regev Cohen', 'Idan Szpektor', 'João Magalhães'] | ['cs.CV'] | While diffusion models excel at generating high-quality images from text
prompts, they struggle with visual consistency in image sequences. Existing
methods generate each image independently, leading to disjointed narratives - a
challenge further exacerbated in non-linear storytelling, where scenes must
connect beyond ... | 2025-03-26T11:01:10Z | null | null | null | Latent Beam Diffusion Models for Decoding Image Sequences | ['Guilherme Fernandes', 'Vasco Ramos', 'Regev Cohen', 'Idan Szpektor', 'Joao Magalhaes'] | 2,025 | arXiv.org | 1 | 57 | ['Computer Science'] |
2,503.20491 | VPO: Aligning Text-to-Video Generation Models with Prompt Optimization | ['Jiale Cheng', 'Ruiliang Lyu', 'Xiaotao Gu', 'Xiao Liu', 'Jiazheng Xu', 'Yida Lu', 'Jiayan Teng', 'Zhuoyi Yang', 'Yuxiao Dong', 'Jie Tang', 'Hongning Wang', 'Minlie Huang'] | ['cs.CV', 'cs.CL', 'cs.LG'] | Video generation models have achieved remarkable progress in text-to-video
tasks. These models are typically trained on text-video pairs with highly
detailed and carefully crafted descriptions, while real-world user inputs
during inference are often concise, vague, or poorly structured. This gap makes
prompt optimizati... | 2025-03-26T12:28:20Z | null | null | null | VPO: Aligning Text-to-Video Generation Models with Prompt Optimization | ['Jiale Cheng', 'Ruiliang Lyu', 'Xiaotao Gu', 'Xiao Liu', 'Jiazheng Xu', 'Yida Lu', 'Jiayan Teng', 'Zhuoyi Yang', 'Yuxiao Dong', 'Jie Tang', 'Hongning Wang', 'Minlie Huang'] | 2,025 | arXiv.org | 2 | 30 | ['Computer Science'] |
2,503.20672 | BizGen: Advancing Article-level Visual Text Rendering for Infographics
Generation | ['Yuyang Peng', 'Shishi Xiao', 'Keming Wu', 'Qisheng Liao', 'Bohan Chen', 'Kevin Lin', 'Danqing Huang', 'Ji Li', 'Yuhui Yuan'] | ['cs.CV'] | Recently, state-of-the-art text-to-image generation models, such as Flux and
Ideogram 2.0, have made significant progress in sentence-level visual text
rendering. In this paper, we focus on the more challenging scenarios of
article-level visual text rendering and address a novel task of generating
high-quality business... | 2025-03-26T16:04:57Z | Accepted by CVPR 2025. Project Page: https://bizgen-msra.github.io | null | null | null | null | null | null | null | null | null |
2,503.2068 | Vision as LoRA | ['Han Wang', 'Yongjie Ye', 'Bingru Li', 'Yuxiang Nie', 'Jinghui Lu', 'Jingqun Tang', 'Yanjie Wang', 'Can Huang'] | ['cs.CV', 'cs.CL'] | We introduce Vision as LoRA (VoRA), a novel paradigm for transforming an LLM
into an MLLM. Unlike prevalent MLLM architectures that rely on external vision
modules for vision encoding, VoRA internalizes visual capabilities by
integrating vision-specific LoRA layers directly into the LLM. This design
allows the added pa... | 2025-03-26T16:15:42Z | null | null | null | Vision as LoRA | ['Hang Wang', 'Yongjie Ye', 'Bingru Li', 'Yuxiang Nie', 'Jinghui Lu', 'Jingqun Tang', 'Yanjie Wang', 'Can Huang'] | 2,025 | arXiv.org | 2 | 53 | ['Computer Science'] |
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