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2,503.20752 | Reason-RFT: Reinforcement Fine-Tuning for Visual Reasoning | ['Huajie Tan', 'Yuheng Ji', 'Xiaoshuai Hao', 'Minglan Lin', 'Pengwei Wang', 'Zhongyuan Wang', 'Shanghang Zhang'] | ['cs.CV', 'cs.AI'] | Visual reasoning abilities play a crucial role in understanding complex
multimodal data, advancing both domain-specific applications and artificial
general intelligence (AGI). Existing methods improve VLM reasoning via
Chain-of-Thought (CoT) supervised fine-tuning, using meticulously annotated
training data to enhance ... | 2025-03-26T17:38:06Z | 35 pages, 22 figures | null | null | null | null | null | null | null | null | null |
2,503.20783 | Understanding R1-Zero-Like Training: A Critical Perspective | ['Zichen Liu', 'Changyu Chen', 'Wenjun Li', 'Penghui Qi', 'Tianyu Pang', 'Chao Du', 'Wee Sun Lee', 'Min Lin'] | ['cs.LG', 'cs.AI', 'cs.CL'] | DeepSeek-R1-Zero has shown that reinforcement learning (RL) at scale can
directly enhance the reasoning capabilities of LLMs without supervised
fine-tuning. In this work, we critically examine R1-Zero-like training by
analyzing its two core components: base models and RL. We investigate a wide
range of base models, inc... | 2025-03-26T17:59:14Z | null | null | null | null | null | null | null | null | null | null |
2,503.20853 | Unified Multimodal Discrete Diffusion | ['Alexander Swerdlow', 'Mihir Prabhudesai', 'Siddharth Gandhi', 'Deepak Pathak', 'Katerina Fragkiadaki'] | ['cs.CV', 'cs.AI', 'cs.LG', 'cs.RO'] | Multimodal generative models that can understand and generate across multiple
modalities are dominated by autoregressive (AR) approaches, which process
tokens sequentially from left to right, or top to bottom. These models jointly
handle images, text, video, and audio for various tasks such as image
captioning, questio... | 2025-03-26T17:59:51Z | Project Website: https://unidisc.github.io | null | null | null | null | null | null | null | null | null |
2,503.21069 | Efficient Multi-Instance Generation with Janus-Pro-Dirven Prompt Parsing | ['Fan Qi', 'Yu Duan', 'Changsheng Xu'] | ['cs.CV'] | Recent advances in text-guided diffusion models have revolutionized
conditional image generation, yet they struggle to synthesize complex scenes
with multiple objects due to imprecise spatial grounding and limited
scalability. We address these challenges through two key modules: 1)
Janus-Pro-driven Prompt Parsing, a pr... | 2025-03-27T00:59:14Z | null | null | null | null | null | null | null | null | null | null |
2,503.21219 | GenFusion: Closing the Loop between Reconstruction and Generation via
Videos | ['Sibo Wu', 'Congrong Xu', 'Binbin Huang', 'Andreas Geiger', 'Anpei Chen'] | ['cs.CV', 'cs.AI'] | Recently, 3D reconstruction and generation have demonstrated impressive novel
view synthesis results, achieving high fidelity and efficiency. However, a
notable conditioning gap can be observed between these two fields, e.g.,
scalable 3D scene reconstruction often requires densely captured views, whereas
3D generation ... | 2025-03-27T07:16:24Z | CVPR 2025, project page: https://genfusion.sibowu.com | null | null | GenFusion: Closing the Loop between Reconstruction and Generation via Videos | ['Sibo Wu', 'Congrong Xu', 'Binbin Huang', 'Andreas Geiger', 'Anpei Chen'] | 2,025 | Computer Vision and Pattern Recognition | 1 | 63 | ['Computer Science'] |
2,503.21295 | R-PRM: Reasoning-Driven Process Reward Modeling | ['Shuaijie She', 'Junxiao Liu', 'Yifeng Liu', 'Jiajun Chen', 'Xin Huang', 'Shujian Huang'] | ['cs.CL'] | Large language models (LLMs) inevitably make mistakes when performing
step-by-step mathematical reasoning. Process Reward Models (PRMs) have emerged
as a promising solution by evaluating each reasoning step. However, existing
PRMs typically output evaluation scores directly, limiting both learning
efficiency and evalua... | 2025-03-27T09:23:08Z | The project is available at https://github.com/NJUNLP/R-PRM | null | null | null | null | null | null | null | null | null |
2,503.21459 | RoadSocial: A Diverse VideoQA Dataset and Benchmark for Road Event
Understanding from Social Video Narratives | ['Chirag Parikh', 'Deepti Rawat', 'Rakshitha R. T.', 'Tathagata Ghosh', 'Ravi Kiran Sarvadevabhatla'] | ['cs.CV'] | We introduce RoadSocial, a large-scale, diverse VideoQA dataset tailored for
generic road event understanding from social media narratives. Unlike existing
datasets limited by regional bias, viewpoint bias and expert-driven
annotations, RoadSocial captures the global complexity of road events with
varied geographies, c... | 2025-03-27T12:49:09Z | Accepted at CVPR 2025; Project Page: https://roadsocial.github.io/ | null | null | RoadSocial: A Diverse VideoQA Dataset and Benchmark for Road Event Understanding from Social Video Narratives | ['Chirag Parikh', 'Deepti Rawat', 'T. RakshithaR.', 'Tathagata Ghosh', 'R. Sarvadevabhatla'] | 2,025 | arXiv.org | 0 | 0 | ['Computer Science'] |
2,503.2162 | UI-R1: Enhancing Efficient Action Prediction of GUI Agents by
Reinforcement Learning | ['Zhengxi Lu', 'Yuxiang Chai', 'Yaxuan Guo', 'Xi Yin', 'Liang Liu', 'Hao Wang', 'Han Xiao', 'Shuai Ren', 'Guanjing Xiong', 'Hongsheng Li'] | ['cs.AI'] | The recent DeepSeek-R1 has showcased the emergence of reasoning capabilities
in LLMs through reinforcement learning (RL) with rule-based rewards. Despite
its success in language models, its application in multi-modal domains,
particularly in graphic user interface (GUI) agent tasks, remains
under-explored. To address t... | 2025-03-27T15:39:30Z | Updated UI-R1-E-3B | null | null | UI-R1: Enhancing Efficient Action Prediction of GUI Agents by Reinforcement Learning | ['Zhengxi Lu', 'Yuxiang Chai', 'Yaxuan Guo', 'Xiaojing Yin', 'Liang Liu', 'Hao Wang', 'Guanjing Xiong', 'Hongsheng Li'] | 2,025 | null | 5 | 36 | ['Computer Science'] |
2,503.21694 | Progressive Rendering Distillation: Adapting Stable Diffusion for
Instant Text-to-Mesh Generation without 3D Data | ['Zhiyuan Ma', 'Xinyue Liang', 'Rongyuan Wu', 'Xiangyu Zhu', 'Zhen Lei', 'Lei Zhang'] | ['cs.GR', 'cs.AI', 'cs.CV'] | It is highly desirable to obtain a model that can generate high-quality 3D
meshes from text prompts in just seconds. While recent attempts have adapted
pre-trained text-to-image diffusion models, such as Stable Diffusion (SD), into
generators of 3D representations (e.g., Triplane), they often suffer from poor
quality d... | 2025-03-27T16:59:15Z | Accepted to CVPR 2025.
Code:https://github.com/theEricMa/TriplaneTurbo.
Demo:https://huggingface.co/spaces/ZhiyuanthePony/TriplaneTurbo | null | null | null | null | null | null | null | null | null |
2,503.21729 | ReaRAG: Knowledge-guided Reasoning Enhances Factuality of Large
Reasoning Models with Iterative Retrieval Augmented Generation | ['Zhicheng Lee', 'Shulin Cao', 'Jinxin Liu', 'Jiajie Zhang', 'Weichuan Liu', 'Xiaoyin Che', 'Lei Hou', 'Juanzi Li'] | ['cs.CL', 'cs.AI'] | Large Reasoning Models (LRMs) exhibit remarkable reasoning abilities but rely
primarily on parametric knowledge, limiting factual accuracy. While recent
works equip reinforcement learning (RL)-based LRMs with retrieval capabilities,
they suffer from overthinking and lack robustness in reasoning, reducing their
effectiv... | 2025-03-27T17:44:18Z | null | null | null | null | null | null | null | null | null | null |
2,503.21732 | SparseFlex: High-Resolution and Arbitrary-Topology 3D Shape Modeling | ['Xianglong He', 'Zi-Xin Zou', 'Chia-Hao Chen', 'Yuan-Chen Guo', 'Ding Liang', 'Chun Yuan', 'Wanli Ouyang', 'Yan-Pei Cao', 'Yangguang Li'] | ['cs.CV'] | Creating high-fidelity 3D meshes with arbitrary topology, including open
surfaces and complex interiors, remains a significant challenge. Existing
implicit field methods often require costly and detail-degrading watertight
conversion, while other approaches struggle with high resolutions. This paper
introduces SparseFl... | 2025-03-27T17:46:42Z | Project page: https://xianglonghe.github.io/TripoSF | null | null | SparseFlex: High-Resolution and Arbitrary-Topology 3D Shape Modeling | ['Xianglong He', 'Zi-Xin Zou', 'Chia-Hao Chen', 'Yuan-Chen Guo', 'Ding Liang', 'Chun Yuan', 'Wanli Ouyang', 'Yan-Pei Cao', 'Yangguang Li'] | 2,025 | arXiv.org | 5 | 93 | ['Computer Science'] |
2,503.21749 | LeX-Art: Rethinking Text Generation via Scalable High-Quality Data
Synthesis | ['Shitian Zhao', 'Qilong Wu', 'Xinyue Li', 'Bo Zhang', 'Ming Li', 'Qi Qin', 'Dongyang Liu', 'Kaipeng Zhang', 'Hongsheng Li', 'Yu Qiao', 'Peng Gao', 'Bin Fu', 'Zhen Li'] | ['cs.CV'] | We introduce LeX-Art, a comprehensive suite for high-quality text-image
synthesis that systematically bridges the gap between prompt expressiveness and
text rendering fidelity. Our approach follows a data-centric paradigm,
constructing a high-quality data synthesis pipeline based on Deepseek-R1 to
curate LeX-10K, a dat... | 2025-03-27T17:56:15Z | Project page: https://zhaoshitian.github.io/lexart/ | null | null | null | null | null | null | null | null | null |
2,503.21751 | Reconstructing Humans with a Biomechanically Accurate Skeleton | ['Yan Xia', 'Xiaowei Zhou', 'Etienne Vouga', 'Qixing Huang', 'Georgios Pavlakos'] | ['cs.CV'] | In this paper, we introduce a method for reconstructing 3D humans from a
single image using a biomechanically accurate skeleton model. To achieve this,
we train a transformer that takes an image as input and estimates the
parameters of the model. Due to the lack of training data for this task, we
build a pipeline to pr... | 2025-03-27T17:56:24Z | CVPR 2025. Project Webpage: https://isshikihugh.github.io/HSMR/ | null | null | Reconstructing Humans with a Biomechanically Accurate Skeleton | ['Yan Xia', 'Xiaowei Zhou', 'Etienne Vouga', 'Qixing Huang', 'Georgios Pavlakos'] | 2,025 | Computer Vision and Pattern Recognition | 1 | 65 | ['Computer Science'] |
2,503.21758 | Lumina-Image 2.0: A Unified and Efficient Image Generative Framework | ['Qi Qin', 'Le Zhuo', 'Yi Xin', 'Ruoyi Du', 'Zhen Li', 'Bin Fu', 'Yiting Lu', 'Jiakang Yuan', 'Xinyue Li', 'Dongyang Liu', 'Xiangyang Zhu', 'Manyuan Zhang', 'Will Beddow', 'Erwann Millon', 'Victor Perez', 'Wenhai Wang', 'Conghui He', 'Bo Zhang', 'Xiaohong Liu', 'Hongsheng Li', 'Yu Qiao', 'Chang Xu', 'Peng Gao'] | ['cs.CV'] | We introduce Lumina-Image 2.0, an advanced text-to-image generation framework
that achieves significant progress compared to previous work, Lumina-Next.
Lumina-Image 2.0 is built upon two key principles: (1) Unification - it adopts
a unified architecture (Unified Next-DiT) that treats text and image tokens as
a joint s... | 2025-03-27T17:57:07Z | Tech Report, 21 pages, 12 figures | null | null | null | null | null | null | null | null | null |
2,503.21776 | Video-R1: Reinforcing Video Reasoning in MLLMs | ['Kaituo Feng', 'Kaixiong Gong', 'Bohao Li', 'Zonghao Guo', 'Yibing Wang', 'Tianshuo Peng', 'Junfei Wu', 'Xiaoying Zhang', 'Benyou Wang', 'Xiangyu Yue'] | ['cs.CV'] | Inspired by DeepSeek-R1's success in eliciting reasoning abilities through
rule-based reinforcement learning (RL), we introduce Video-R1 as the first
attempt to systematically explore the R1 paradigm for incentivizing video
reasoning within multimodal large language models (MLLMs). However, directly
applying RL trainin... | 2025-03-27T17:59:51Z | Project page: https://github.com/tulerfeng/Video-R1 | null | null | Video-R1: Reinforcing Video Reasoning in MLLMs | ['Kaituo Feng', 'Kaixiong Gong', 'Bohao Li', 'Zonghao Guo', 'Yibing Wang', 'Tianshuo Peng', 'Benyou Wang', 'Xiangyu Yue'] | 2,025 | arXiv.org | 62 | 44 | ['Computer Science'] |
2,503.2178 | Semantic Library Adaptation: LoRA Retrieval and Fusion for
Open-Vocabulary Semantic Segmentation | ['Reza Qorbani', 'Gianluca Villani', 'Theodoros Panagiotakopoulos', 'Marc Botet Colomer', 'Linus Härenstam-Nielsen', 'Mattia Segu', 'Pier Luigi Dovesi', 'Jussi Karlgren', 'Daniel Cremers', 'Federico Tombari', 'Matteo Poggi'] | ['cs.CV'] | Open-vocabulary semantic segmentation models associate vision and text to
label pixels from an undefined set of classes using textual queries, providing
versatile performance on novel datasets. However, large shifts between training
and test domains degrade their performance, requiring fine-tuning for effective
real-wo... | 2025-03-27T17:59:58Z | CVPR 2025. Project page: https://thegoodailab.org/semla Code:
https://github.com/rezaqorbani/SemLA | null | null | null | null | null | null | null | null | null |
2,503.21782 | Mobile-VideoGPT: Fast and Accurate Video Understanding Language Model | ['Abdelrahman Shaker', 'Muhammad Maaz', 'Chenhui Gou', 'Hamid Rezatofighi', 'Salman Khan', 'Fahad Shahbaz Khan'] | ['cs.CV'] | Video understanding models often struggle with high computational
requirements, extensive parameter counts, and slow inference speed, making them
inefficient for practical use. To tackle these challenges, we propose
Mobile-VideoGPT, an efficient multimodal framework designed to operate with
fewer than a billion paramet... | 2025-03-27T17:59:58Z | Technical Report. Project Page:
https://amshaker.github.io/Mobile-VideoGPT | null | null | null | null | null | null | null | null | null |
2,503.21819 | Optimizing Safe and Aligned Language Generation: A Multi-Objective GRPO
Approach | ['Xuying Li', 'Zhuo Li', 'Yuji Kosuga', 'Victor Bian'] | ['cs.CL'] | Aligning large language models (LLMs) with human values and safety
constraints is challenging, especially when objectives like helpfulness,
truthfulness, and avoidance of harm conflict. Reinforcement Learning from Human
Feedback (RLHF) has achieved notable success in steering models, but is complex
and can be unstable.... | 2025-03-26T05:50:33Z | null | null | null | Optimizing Safe and Aligned Language Generation: A Multi-Objective GRPO Approach | ['Xuying Li', 'Zhuo Li', 'Yuji Kosuga', 'Victor Bian'] | 2,025 | arXiv.org | 4 | 18 | ['Computer Science'] |
2,503.21841 | HyperFree: A Channel-adaptive and Tuning-free Foundation Model for
Hyperspectral Remote Sensing Imagery | ['Jingtao Li', 'Yingyi Liu', 'Xinyu Wang', 'Yunning Peng', 'Chen Sun', 'Shaoyu Wang', 'Zhendong Sun', 'Tian Ke', 'Xiao Jiang', 'Tangwei Lu', 'Anran Zhao', 'Yanfei Zhong'] | ['cs.CV'] | Advanced interpretation of hyperspectral remote sensing images benefits many
precise Earth observation tasks. Recently, visual foundation models have
promoted the remote sensing interpretation but concentrating on RGB and
multispectral images. Due to the varied hyperspectral channels,existing
foundation models would fa... | 2025-03-27T10:27:10Z | Accepted by CVPR2025 | null | null | HyperFree: A Channel-adaptive and Tuning-free Foundation Model for Hyperspectral Remote Sensing Imagery | ['Jingtao Li', 'Yingyi Liu', 'Xinyu Wang', 'Yunning Peng', 'Chen Sun', 'Shaoyu Wang', 'Zhendong Sun', 'Tian Ke', 'Xiao Jiang', 'Tangwei Lu', 'Anran Zhao', 'Yanfei Zhong'] | 2,025 | arXiv.org | 1 | 90 | ['Computer Science'] |
2,503.2186 | ManipTrans: Efficient Dexterous Bimanual Manipulation Transfer via
Residual Learning | ['Kailin Li', 'Puhao Li', 'Tengyu Liu', 'Yuyang Li', 'Siyuan Huang'] | ['cs.RO', 'cs.CV'] | Human hands play a central role in interacting, motivating increasing
research in dexterous robotic manipulation. Data-driven embodied AI algorithms
demand precise, large-scale, human-like manipulation sequences, which are
challenging to obtain with conventional reinforcement learning or real-world
teleoperation. To ad... | 2025-03-27T17:50:30Z | Accepted to CVPR 2025 | null | null | null | null | null | null | null | null | null |
2,503.21934 | Proof or Bluff? Evaluating LLMs on 2025 USA Math Olympiad | ['Ivo Petrov', 'Jasper Dekoninck', 'Lyuben Baltadzhiev', 'Maria Drencheva', 'Kristian Minchev', 'Mislav Balunović', 'Nikola Jovanović', 'Martin Vechev'] | ['cs.CL'] | Recent math benchmarks for large language models (LLMs) such as MathArena
indicate that state-of-the-art reasoning models achieve impressive performance
on mathematical competitions like AIME, with the leading model, Gemini-2.5-Pro,
achieving scores comparable to top human competitors. However, these benchmarks
evaluat... | 2025-03-27T19:21:05Z | null | null | null | null | null | null | null | null | null | null |
2,503.21979 | Harmonizing Visual Representations for Unified Multimodal Understanding
and Generation | ['Size Wu', 'Wenwei Zhang', 'Lumin Xu', 'Sheng Jin', 'Zhonghua Wu', 'Qingyi Tao', 'Wentao Liu', 'Wei Li', 'Chen Change Loy'] | ['cs.CV'] | Unifying visual understanding and generation within a single multimodal
framework remains a significant challenge, as the two inherently heterogeneous
tasks require representations at different levels of granularity. Current
approaches that utilize vector quantization (VQ) or variational autoencoders
(VAE) for unified ... | 2025-03-27T20:50:38Z | null | null | null | null | null | null | null | null | null | null |
2,503.22048 | ThinkEdit: Interpretable Weight Editing to Mitigate Overly Short
Thinking in Reasoning Models | ['Chung-En Sun', 'Ge Yan', 'Tsui-Wei Weng'] | ['cs.CL', 'cs.LG'] | Recent studies have shown that Large Language Models (LLMs) augmented with
chain-of-thought (CoT) reasoning demonstrate impressive problem-solving
abilities. However, in this work, we identify a recurring issue where these
models occasionally generate overly short reasoning, leading to degraded
performance on even simp... | 2025-03-27T23:53:45Z | null | null | null | null | null | null | null | null | null | null |
2,503.22262 | Mono2Stereo: A Benchmark and Empirical Study for Stereo Conversion | ['Songsong Yu', 'Yuxin Chen', 'Zhongang Qi', 'Zeke Xie', 'Yifan Wang', 'Lijun Wang', 'Ying Shan', 'Huchuan Lu'] | ['cs.CV'] | With the rapid proliferation of 3D devices and the shortage of 3D content,
stereo conversion is attracting increasing attention. Recent works introduce
pretrained Diffusion Models (DMs) into this task. However, due to the scarcity
of large-scale training data and comprehensive benchmarks, the optimal
methodologies for ... | 2025-03-28T09:25:58Z | Accepted by CVPR 2025 Project webpage:
https://mono2stereo-bench.github.io/ | null | null | null | null | null | null | null | null | null |
2,503.22357 | EchoFlow: A Foundation Model for Cardiac Ultrasound Image and Video
Generation | ['Hadrien Reynaud', 'Alberto Gomez', 'Paul Leeson', 'Qingjie Meng', 'Bernhard Kainz'] | ['cs.CV'] | Advances in deep learning have significantly enhanced medical image analysis,
yet the availability of large-scale medical datasets remains constrained by
patient privacy concerns. We present EchoFlow, a novel framework designed to
generate high-quality, privacy-preserving synthetic echocardiogram images and
videos. Ech... | 2025-03-28T11:51:59Z | This work has been submitted to the IEEE for possible publication | null | null | EchoFlow: A Foundation Model for Cardiac Ultrasound Image and Video Generation | ['Hadrien Reynaud', 'Alberto Gomez', 'Paul Leeson', 'Qingjie Meng', 'Bernhard Kainz'] | 2,025 | arXiv.org | 2 | 59 | ['Computer Science'] |
2,503.22402 | EllieSQL: Cost-Efficient Text-to-SQL with Complexity-Aware Routing | ['Yizhang Zhu', 'Runzhi Jiang', 'Boyan Li', 'Nan Tang', 'Yuyu Luo'] | ['cs.DB', 'cs.AI', 'cs.CL'] | Text-to-SQL automatically translates natural language queries to SQL,
allowing non-technical users to retrieve data from databases without
specialized SQL knowledge. Despite the success of advanced LLM-based
Text-to-SQL approaches on leaderboards, their unsustainable computational
costs--often overlooked--stand as the ... | 2025-03-28T13:11:27Z | 19 pages, 8 figures, 3 tables | null | null | null | null | null | null | null | null | null |
2,503.22673 | ActionStudio: A Lightweight Framework for Data and Training of Large
Action Models | ['Jianguo Zhang', 'Thai Hoang', 'Ming Zhu', 'Zuxin Liu', 'Shiyu Wang', 'Tulika Awalgaonkar', 'Akshara Prabhakar', 'Haolin Chen', 'Weiran Yao', 'Zhiwei Liu', 'Juntao Tan', 'Juan Carlos Niebles', 'Shelby Heinecke', 'Huan Wang', 'Silvio Savarese', 'Caiming Xiong'] | ['cs.AI', 'cs.CL'] | Action models are essential for enabling autonomous agents to perform complex
tasks. However, training large action models remains challenging due to the
diversity of agent environments and the complexity of agentic data. Despite
growing interest, existing infrastructure provides limited support for
scalable, agent-spe... | 2025-03-28T17:58:33Z | 15 pages; large action models; xLAM | null | null | null | null | null | null | null | null | null |
2,503.22678 | Self-Evolving Multi-Agent Simulations for Realistic Clinical
Interactions | ['Mohammad Almansoori', 'Komal Kumar', 'Hisham Cholakkal'] | ['cs.CL'] | In this work, we introduce MedAgentSim, an open-source simulated clinical
environment with doctor, patient, and measurement agents designed to evaluate
and enhance LLM performance in dynamic diagnostic settings. Unlike prior
approaches, our framework requires doctor agents to actively engage with
patients through multi... | 2025-03-28T17:59:53Z | 14 page, 4 figures, 61 references | null | null | null | null | null | null | null | null | null |
2,503.22679 | Q-Insight: Understanding Image Quality via Visual Reinforcement Learning | ['Weiqi Li', 'Xuanyu Zhang', 'Shijie Zhao', 'Yabin Zhang', 'Junlin Li', 'Li Zhang', 'Jian Zhang'] | ['cs.CV'] | Image quality assessment (IQA) focuses on the perceptual visual quality of
images, playing a crucial role in downstream tasks such as image
reconstruction, compression, and generation. The rapid advancement of
multi-modal large language models (MLLMs) has significantly broadened the scope
of IQA, moving toward comprehe... | 2025-03-28T17:59:54Z | null | null | null | null | null | null | null | null | null | null |
2,503.22713 | Chirp Localization via Fine-Tuned Transformer Model: A Proof-of-Concept
Study | ['Nooshin Bahador', 'Milad Lankarany'] | ['eess.AS', 'cs.AI', 'cs.CV', 'cs.LG', 'cs.SD'] | Spectrograms are pivotal in time-frequency signal analysis, widely used in
audio processing and computational neuroscience. Chirp-like patterns in
electroencephalogram (EEG) spectrograms (marked by linear or exponential
frequency sweep) are key biomarkers for seizure dynamics, but automated tools
for their detection, l... | 2025-03-24T14:27:07Z | 19 pages, 8 figures | null | null | Chirp Localization via Fine-Tuned Transformer Model: A Proof-of-Concept Study | ['N. Bahador', 'M. Lankarany'] | 2,025 | arXiv.org | 1 | 34 | ['Engineering', 'Computer Science'] |
2,503.22952 | OmniMMI: A Comprehensive Multi-modal Interaction Benchmark in Streaming
Video Contexts | ['Yuxuan Wang', 'Yueqian Wang', 'Bo Chen', 'Tong Wu', 'Dongyan Zhao', 'Zilong Zheng'] | ['cs.CV'] | The rapid advancement of multi-modal language models (MLLMs) like GPT-4o has
propelled the development of Omni language models, designed to process and
proactively respond to continuous streams of multi-modal data. Despite their
potential, evaluating their real-world interactive capabilities in streaming
video contexts... | 2025-03-29T02:46:58Z | To appear at CVPR 2025 | null | null | null | null | null | null | null | null | null |
2,503.23135 | LSNet: See Large, Focus Small | ['Ao Wang', 'Hui Chen', 'Zijia Lin', 'Jungong Han', 'Guiguang Ding'] | ['cs.CV'] | Vision network designs, including Convolutional Neural Networks and Vision
Transformers, have significantly advanced the field of computer vision. Yet,
their complex computations pose challenges for practical deployments,
particularly in real-time applications. To tackle this issue, researchers have
explored various li... | 2025-03-29T16:00:54Z | CVPR 2025 Camera-ready Version | null | null | null | null | null | null | null | null | null |
2,503.23145 | CodeARC: Benchmarking Reasoning Capabilities of LLM Agents for Inductive
Program Synthesis | ['Anjiang Wei', 'Tarun Suresh', 'Jiannan Cao', 'Naveen Kannan', 'Yuheng Wu', 'Kai Yan', 'Thiago S. F. X. Teixeira', 'Ke Wang', 'Alex Aiken'] | ['cs.PL', 'cs.AI', 'cs.CL', 'cs.LG'] | Inductive program synthesis, or programming by example, requires synthesizing
functions from input-output examples that generalize to unseen inputs. While
large language model agents have shown promise in programming tasks guided by
natural language, their ability to perform inductive program synthesis is
underexplored... | 2025-03-29T16:50:39Z | null | null | null | CodeARC: Benchmarking Reasoning Capabilities of LLM Agents for Inductive Program Synthesis | ['Anjiang Wei', 'Tarun Suresh', 'Jiannan Cao', 'Naveen Kannan', 'Yuheng Wu', 'Kai Yan', 'Thiago S. F. X. Teixeira', 'Ke Wang', 'Alex Aiken'] | 2,025 | arXiv.org | 0 | 76 | ['Computer Science'] |
2,503.23204 | The Challenge of Achieving Attributability in Multilingual Table-to-Text
Generation with Question-Answer Blueprints | ['Aden Haussmann'] | ['cs.CL', 'cs.AI', 'cs.LG'] | Multilingual Natural Language Generation (NLG) is challenging due to the lack
of training data for low-resource languages. However, some low-resource
languages have up to tens of millions of speakers globally, making it important
to improve NLG tools for them. Table-to-Text NLG is an excellent measure of
models' reason... | 2025-03-29T20:04:00Z | null | null | null | null | null | null | null | null | null | null |
2,503.23278 | Model Context Protocol (MCP): Landscape, Security Threats, and Future
Research Directions | ['Xinyi Hou', 'Yanjie Zhao', 'Shenao Wang', 'Haoyu Wang'] | ['cs.CR', 'cs.AI'] | The Model Context Protocol (MCP) is a standardized interface designed to
enable seamless interaction between AI models and external tools and resources,
breaking down data silos and facilitating interoperability across diverse
systems. This paper provides a comprehensive overview of MCP, focusing on its
core components... | 2025-03-30T01:58:22Z | null | null | null | Model Context Protocol (MCP): Landscape, Security Threats, and Future Research Directions | ['Xinyi Hou', 'Yanjie Zhao', 'Shenao Wang', 'Haoyu Wang'] | 2,025 | arXiv.org | 35 | 54 | ['Computer Science'] |
2,503.23282 | AnyCam: Learning to Recover Camera Poses and Intrinsics from Casual
Videos | ['Felix Wimbauer', 'Weirong Chen', 'Dominik Muhle', 'Christian Rupprecht', 'Daniel Cremers'] | ['cs.CV'] | Estimating camera motion and intrinsics from casual videos is a core
challenge in computer vision. Traditional bundle-adjustment based methods, such
as SfM and SLAM, struggle to perform reliably on arbitrary data. Although
specialized SfM approaches have been developed for handling dynamic scenes,
they either require i... | 2025-03-30T02:22:11Z | CVPR 2025 - For more details and code, please check out our project
page under https://fwmb.github.io/anycam | null | null | AnyCam: Learning to Recover Camera Poses and Intrinsics from Casual Videos | ['Felix Wimbauer', 'Weirong Chen', 'Dominik Muhle', 'Christian Rupprecht', 'Daniel Cremers'] | 2,025 | arXiv.org | 0 | 58 | ['Computer Science'] |
2,503.23284 | SketchVideo: Sketch-based Video Generation and Editing | ['Feng-Lin Liu', 'Hongbo Fu', 'Xintao Wang', 'Weicai Ye', 'Pengfei Wan', 'Di Zhang', 'Lin Gao'] | ['cs.GR', 'cs.CV'] | Video generation and editing conditioned on text prompts or images have
undergone significant advancements. However, challenges remain in accurately
controlling global layout and geometry details solely by texts, and supporting
motion control and local modification through images. In this paper, we aim to
achieve sketc... | 2025-03-30T02:44:09Z | CVPR 2025 | null | null | SketchVideo: Sketch-based Video Generation and Editing | ['Feng-Lin Liu', 'Hongbo Fu', 'Xintao Wang', 'Weicai Ye', 'Pengfei Wan', 'Dingxi Zhang', 'Lin Gao'] | 2,025 | arXiv.org | 0 | 91 | ['Computer Science'] |
2,503.23303 | SalesRLAgent: A Reinforcement Learning Approach for Real-Time Sales
Conversion Prediction and Optimization | ['Nandakishor M'] | ['cs.LG', 'cs.AI'] | Current approaches to sales conversation analysis and conversion prediction
typically rely on Large Language Models (LLMs) combined with basic retrieval
augmented generation (RAG). These systems, while capable of answering
questions, fail to accurately predict conversion probability or provide
strategic guidance in rea... | 2025-03-30T03:56:26Z | null | null | null | null | null | null | null | null | null | null |
2,503.2333 | EagleVision: Object-level Attribute Multimodal LLM for Remote Sensing | ['Hongxiang Jiang', 'Jihao Yin', 'Qixiong Wang', 'Jiaqi Feng', 'Guo Chen'] | ['cs.CV'] | Recent advances in multimodal large language models (MLLMs) have demonstrated
impressive results in various visual tasks. However, in remote sensing (RS),
high resolution and small proportion of objects pose challenges to existing
MLLMs, which struggle with object-centric tasks, particularly in precise
localization and... | 2025-03-30T06:13:13Z | Under Review | null | null | null | null | null | null | null | null | null |
2,503.23542 | Whisper-LM: Improving ASR Models with Language Models for Low-Resource
Languages | ['Xabier de Zuazo', 'Eva Navas', 'Ibon Saratxaga', 'Inma Hernáez Rioja'] | ['cs.CL', '68T50 (Primary), 62H30', 'I.2.7; I.2.6; J.5.2'] | Automatic speech recognition systems have undoubtedly advanced with the
integration of multilingual and multitask models such as Whisper, which have
shown a promising ability to understand and process speech across a wide range
of languages. Despite their robustness, these models often fall short in
handling the lingui... | 2025-03-30T18:03:52Z | 26 pages, 6 figures, includes supplementary materials. Will be
submitted to IEEE/ACM Transactions on Audio, Speech, and Language Processing | null | null | Whisper-LM: Improving ASR Models with Language Models for Low-Resource Languages | ['Xabier de Zuazo', 'Eva Navas', 'I. Saratxaga', 'I. Rioja'] | 2,025 | arXiv.org | 3 | 99 | ['Computer Science'] |
2,503.2358 | DiT4SR: Taming Diffusion Transformer for Real-World Image
Super-Resolution | ['Zheng-Peng Duan', 'Jiawei Zhang', 'Xin Jin', 'Ziheng Zhang', 'Zheng Xiong', 'Dongqing Zou', 'Jimmy S. Ren', 'Chun-Le Guo', 'Chongyi Li'] | ['cs.CV'] | Large-scale pre-trained diffusion models are becoming increasingly popular in
solving the Real-World Image Super-Resolution (Real-ISR) problem because of
their rich generative priors. The recent development of diffusion transformer
(DiT) has witnessed overwhelming performance over the traditional UNet-based
architectur... | 2025-03-30T20:27:22Z | null | null | null | null | null | null | null | null | null | null |
2,503.23714 | Building Instruction-Tuning Datasets from Human-Written Instructions
with Open-Weight Large Language Models | ['Youmi Ma', 'Sakae Mizuki', 'Kazuki Fujii', 'Taishi Nakamura', 'Masanari Ohi', 'Hinari Shimada', 'Taihei Shiotani', 'Koshiro Saito', 'Koki Maeda', 'Kakeru Hattori', 'Takumi Okamoto', 'Shigeki Ishida', 'Rio Yokota', 'Hiroya Takamura', 'Naoaki Okazaki'] | ['cs.CL'] | Instruction tuning is crucial for enabling Large Language Models (LLMs) to
solve real-world tasks. Prior work has shown the effectiveness of
instruction-tuning data synthesized solely from LLMs, raising a fundamental
question: Do we still need human-originated signals for instruction tuning?
This work answers the quest... | 2025-03-31T04:28:38Z | 15 pages, 5 figures | null | null | Building Instruction-Tuning Datasets from Human-Written Instructions with Open-Weight Large Language Models | ['Youmi Ma', 'Sakae Mizuki', 'Kazuki Fujii', 'Taishi Nakamura', 'Masanari Ohi', 'Hinari Shimada', 'Taihei Shiotani', 'Koshiro Saito', 'Koki Maeda', 'Kakeru Hattori', 'Takumi Okamoto', 'Shigeki Ishida', 'Rio Yokota', 'Hiroya Takamura', 'Naoaki Okazaki'] | 2,025 | arXiv.org | 0 | 31 | ['Computer Science'] |
2,503.23794 | Force-Free Molecular Dynamics Through Autoregressive Equivariant
Networks | ['Fabian L. Thiemann', 'Thiago Reschützegger', 'Massimiliano Esposito', 'Tseden Taddese', 'Juan D. Olarte-Plata', 'Fausto Martelli'] | ['physics.comp-ph', 'cond-mat.mtrl-sci', 'cs.LG', 'physics.chem-ph'] | Molecular dynamics (MD) simulations play a crucial role in scientific
research. Yet their computational cost often limits the timescales and system
sizes that can be explored. Most data-driven efforts have been focused on
reducing the computational cost of accurate interatomic forces required for
solving the equations ... | 2025-03-31T07:14:32Z | 25 pages total (19 manuscript, 6 SI). 5 figures in manuscript, 3
figures and 2 tables in SI | null | null | Force-Free Molecular Dynamics Through Autoregressive Equivariant Networks | ['Fabian L. Thiemann', 'Thiago Reschützegger', 'Massimiliano Esposito', 'Tseden Taddese', 'Juan D. Olarte-Plata', 'Fausto Martelli'] | 2,025 | arXiv.org | 1 | 89 | ['Computer Science', 'Physics'] |
2,503.23798 | Adaptive Layer-skipping in Pre-trained LLMs | ['Xuan Luo', 'Weizhi Wang', 'Xifeng Yan'] | ['cs.CL', 'cs.AI'] | Various layer-skipping methods have been proposed to accelerate token
generation in large language models (LLMs). However, they have overlooked a
fundamental question: How do computational demands vary across the generation
of different tokens? In this work, we introduce FlexiDepth, a method that
dynamically adjusts th... | 2025-03-31T07:20:58Z | null | null | null | Adaptive Layer-skipping in Pre-trained LLMs | ['Xuan Luo', 'Weizhi Wang', 'Xifeng Yan'] | 2,025 | arXiv.org | 1 | 44 | ['Computer Science'] |
2,503.23829 | Crossing the Reward Bridge: Expanding RL with Verifiable Rewards Across
Diverse Domains | ['Yi Su', 'Dian Yu', 'Linfeng Song', 'Juntao Li', 'Haitao Mi', 'Zhaopeng Tu', 'Min Zhang', 'Dong Yu'] | ['cs.CL'] | Reinforcement learning with verifiable rewards (RLVR) has demonstrated
significant success in enhancing mathematical reasoning and coding performance
of large language models (LLMs), especially when structured reference answers
are accessible for verification. However, its extension to broader, less
structured domains ... | 2025-03-31T08:22:49Z | null | null | null | null | null | null | null | null | null | null |
2,503.23859 | Evaluating small vision-language models as AI assistants for radio
astronomical source analysis tasks | ['S. Riggi', 'T. Cecconello', 'A. Pilzer', 'S. Palazzo', 'N. Gupta', 'A. M. Hopkins', 'C. Trigilio', 'G. Umana'] | ['astro-ph.IM'] | The advent of next-generation radio telescopes is set to transform radio
astronomy by producing massive data volumes that challenge traditional
processing methods. Deep learning techniques have shown strong potential in
automating radio analysis tasks, yet are often constrained by the limited
availability of large anno... | 2025-03-31T09:06:23Z | 17 pages, 6 figures | null | null | null | null | null | null | null | null | null |
2,503.24102 | Is LLM the Silver Bullet to Low-Resource Languages Machine Translation? | ['Yewei Song', 'Lujun Li', 'Cedric Lothritz', 'Saad Ezzini', 'Lama Sleem', 'Niccolo Gentile', 'Radu State', 'Tegawendé F. Bissyandé', 'Jacques Klein'] | ['cs.CL'] | Low-Resource Languages (LRLs) present significant challenges in natural
language processing due to their limited linguistic resources and
underrepresentation in standard datasets. While recent advances in Large
Language Models (LLMs) and Neural Machine Translation have substantially
improved translation capabilities fo... | 2025-03-31T13:56:03Z | null | null | null | null | null | null | null | null | null | null |
2,503.24121 | IMPACT: A Generic Semantic Loss for Multimodal Medical Image
Registration | ['Valentin Boussot', 'Cédric Hémon', 'Jean-Claude Nunes', 'Jason Dowling', 'Simon Rouzé', 'Caroline Lafond', 'Anaïs Barateau', 'Jean-Louis Dillenseger'] | ['cs.CV', 'cs.LG'] | Image registration is fundamental in medical imaging, enabling precise
alignment of anatomical structures for diagnosis, treatment planning,
image-guided interventions, and longitudinal monitoring. This work introduces
IMPACT (Image Metric with Pretrained model-Agnostic Comparison for
Transmodality registration), a nov... | 2025-03-31T14:08:21Z | Submitted to IEEE Transactions on Pattern Analysis and Machine
Intelligence (TPAMI). This is a preprint version and has not been
peer-reviewed | null | null | IMPACT: A Generic Semantic Loss for Multimodal Medical Image Registration | ['Valentin Boussot', "C'edric H'emon", 'Jean-Claude Nunes', 'Jason Downling', "Simon Rouz'e", 'C. Lafond', 'A. Barateau', 'J. Dillenseger'] | 2,025 | arXiv.org | 0 | 63 | ['Computer Science'] |
2,503.2429 | Open-Reasoner-Zero: An Open Source Approach to Scaling Up Reinforcement
Learning on the Base Model | ['Jingcheng Hu', 'Yinmin Zhang', 'Qi Han', 'Daxin Jiang', 'Xiangyu Zhang', 'Heung-Yeung Shum'] | ['cs.LG', 'cs.CL'] | We introduce Open-Reasoner-Zero, the first open source implementation of
large-scale reasoning-oriented RL training on the base model focusing on
scalability, simplicity and accessibility. Through extensive experiments, we
demonstrate that a minimalist approach, vanilla PPO with GAE ($\lambda=1$,
$\gamma=1$) and straig... | 2025-03-31T16:36:05Z | null | null | null | null | null | null | null | null | null | null |
2,503.24345 | PathOrchestra: A Comprehensive Foundation Model for Computational
Pathology with Over 100 Diverse Clinical-Grade Tasks | ['Fang Yan', 'Jianfeng Wu', 'Jiawen Li', 'Wei Wang', 'Jiaxuan Lu', 'Wen Chen', 'Zizhao Gao', 'Jianan Li', 'Hong Yan', 'Jiabo Ma', 'Minda Chen', 'Yang Lu', 'Qing Chen', 'Yizhi Wang', 'Xitong Ling', 'Xuenian Wang', 'Zihan Wang', 'Qiang Huang', 'Shengyi Hua', 'Mianxin Liu', 'Lei Ma', 'Tian Shen', 'Xiaofan Zhang', 'Yonghon... | ['cs.CV'] | The complexity and variability inherent in high-resolution pathological
images present significant challenges in computational pathology. While
pathology foundation models leveraging AI have catalyzed transformative
advancements, their development demands large-scale datasets, considerable
storage capacity, and substan... | 2025-03-31T17:28:02Z | null | null | null | null | null | null | null | null | null | null |
2,503.24358 | SQuat: Subspace-orthogonal KV Cache Quantization | ['Hao Wang', 'Ligong Han', 'Kai Xu', 'Akash Srivastava'] | ['cs.LG', 'cs.AI', 'cs.CL', 'cs.IT', 'math.IT'] | The key-value (KV) cache accelerates LLMs decoding by storing KV tensors from
previously generated tokens. It reduces redundant computation at the cost of
increased memory usage. To mitigate this overhead, existing approaches compress
KV tensors into lower-bit representations; however, quantization errors can
accumulat... | 2025-03-31T17:37:32Z | null | null | null | SQuat: Subspace-orthogonal KV Cache Quantization | ['Hao Wang', 'Ligong Han', 'Kai Xu', 'Akash Srivastava'] | 2,025 | arXiv.org | 1 | 80 | ['Computer Science', 'Mathematics'] |
2,504.0005 | JudgeLRM: Large Reasoning Models as a Judge | ['Nuo Chen', 'Zhiyuan Hu', 'Qingyun Zou', 'Jiaying Wu', 'Qian Wang', 'Bryan Hooi', 'Bingsheng He'] | ['cs.CL', 'cs.AI'] | The rise of Large Language Models (LLMs) as evaluators offers a scalable
alternative to human annotation, yet existing Supervised Fine-Tuning (SFT) for
judges approaches often fall short in domains requiring complex reasoning. In
this work, we investigate whether LLM judges truly benefit from enhanced
reasoning capabil... | 2025-03-31T02:18:51Z | preprint | null | null | JudgeLRM: Large Reasoning Models as a Judge | ['Nuo Chen', 'Zhiyuan Hu', 'Qingyun Zou', 'Jiaying Wu', 'Qian Wang', 'Bryan Hooi', 'Bingsheng He'] | 2,025 | arXiv.org | 15 | 18 | ['Computer Science'] |
2,504.00072 | Chapter-Llama: Efficient Chaptering in Hour-Long Videos with LLMs | ['Lucas Ventura', 'Antoine Yang', 'Cordelia Schmid', 'Gül Varol'] | ['cs.CV'] | We address the task of video chaptering, i.e., partitioning a long video
timeline into semantic units and generating corresponding chapter titles. While
relatively underexplored, automatic chaptering has the potential to enable
efficient navigation and content retrieval in long-form videos. In this paper,
we achieve st... | 2025-03-31T17:41:29Z | CVPR 2025 Camera ready. Project page:
https://imagine.enpc.fr/~lucas.ventura/chapter-llama/ | null | null | null | null | null | null | null | null | null |
2,504.00487 | FortisAVQA and MAVEN: a Benchmark Dataset and Debiasing Framework for
Robust Multimodal Reasoning | ['Jie Ma', 'Zhitao Gao', 'Qi Chai', 'Jun Liu', 'Pinghui Wang', 'Jing Tao', 'Zhou Su'] | ['cs.MM', 'cs.CL', 'cs.CV', 'H.5.1; I.2.4'] | Audio-Visual Question Answering (AVQA) is a challenging multimodal reasoning
task requiring intelligent systems to answer natural language queries based on
paired audio-video inputs accurately. However, existing AVQA approaches often
suffer from overfitting to dataset biases, leading to poor robustness.
Moreover, curre... | 2025-04-01T07:23:50Z | Under Review | null | null | null | null | null | null | null | null | null |
2,504.00527 | SMILE: Infusing Spatial and Motion Semantics in Masked Video Learning | ['Fida Mohammad Thoker', 'Letian Jiang', 'Chen Zhao', 'Bernard Ghanem'] | ['cs.CV'] | Masked video modeling, such as VideoMAE, is an effective paradigm for video
self-supervised learning (SSL). However, they are primarily based on
reconstructing pixel-level details on natural videos which have substantial
temporal redundancy, limiting their capability for semantic representation and
sufficient encoding ... | 2025-04-01T08:20:55Z | Accepted to CVPR 2025 | null | null | null | null | null | null | null | null | null |
2,504.00595 | Open-Qwen2VL: Compute-Efficient Pre-Training of Fully-Open Multimodal
LLMs on Academic Resources | ['Weizhi Wang', 'Yu Tian', 'Linjie Yang', 'Heng Wang', 'Xifeng Yan'] | ['cs.CL'] | The reproduction of state-of-the-art multimodal LLM pre-training faces
barriers at every stage of the pipeline, including high-quality data filtering,
multimodal data mixture strategies, sequence packing techniques, and training
frameworks. We introduce Open-Qwen2VL, a fully open-source 2B-parameter
Multimodal Large La... | 2025-04-01T09:54:00Z | null | null | null | Open-Qwen2VL: Compute-Efficient Pre-Training of Fully-Open Multimodal LLMs on Academic Resources | ['Weizhi Wang', 'Yu Tian', 'Linjie Yang', 'Heng Wang', 'Xifeng Yan'] | 2,025 | arXiv.org | 0 | 53 | ['Computer Science'] |
2,504.00676 | GLiNER-BioMed: A Suite of Efficient Models for Open Biomedical Named
Entity Recognition | ['Anthony Yazdani', 'Ihor Stepanov', 'Douglas Teodoro'] | ['cs.CL'] | Biomedical named entity recognition (NER) presents unique challenges due to
specialized vocabularies, the sheer volume of entities, and the continuous
emergence of novel entities. Traditional NER models, constrained by fixed
taxonomies and human annotations, struggle to generalize beyond predefined
entity types. To add... | 2025-04-01T11:40:50Z | null | null | null | GLiNER-biomed: A Suite of Efficient Models for Open Biomedical Named Entity Recognition | ['A. Yazdani', 'Ihor Stepanov', 'Douglas Teodoro'] | 2,025 | arXiv.org | 0 | 51 | ['Computer Science'] |
2,504.00698 | Command A: An Enterprise-Ready Large Language Model | ['Team Cohere', ':', 'Aakanksha', 'Arash Ahmadian', 'Marwan Ahmed', 'Jay Alammar', 'Milad Alizadeh', 'Yazeed Alnumay', 'Sophia Althammer', 'Arkady Arkhangorodsky', 'Viraat Aryabumi', 'Dennis Aumiller', 'Raphaël Avalos', 'Zahara Aviv', 'Sammie Bae', 'Saurabh Baji', 'Alexandre Barbet', 'Max Bartolo', 'Björn Bebensee', 'N... | ['cs.CL', 'cs.AI', 'cs.LG'] | In this report we describe the development of Command A, a powerful large
language model purpose-built to excel at real-world enterprise use cases.
Command A is an agent-optimised and multilingual-capable model, with support
for 23 languages of global business, and a novel hybrid architecture balancing
efficiency with ... | 2025-04-01T12:08:07Z | 55 pages | null | null | null | null | null | null | null | null | null |
2,504.0081 | Z1: Efficient Test-time Scaling with Code | ['Zhaojian Yu', 'Yinghao Wu', 'Yilun Zhao', 'Arman Cohan', 'Xiao-Ping Zhang'] | ['cs.CL'] | Large Language Models (LLMs) can achieve enhanced complex problem-solving
through test-time computing scaling, yet this often entails longer contexts and
numerous reasoning token costs. In this paper, we propose an efficient
test-time scaling method that trains LLMs on code-related reasoning
trajectories, facilitating ... | 2025-04-01T14:01:50Z | null | null | null | null | null | null | null | null | null | null |
2,504.00824 | ScholarCopilot: Training Large Language Models for Academic Writing with
Accurate Citations | ['Yubo Wang', 'Xueguang Ma', 'Ping Nie', 'Huaye Zeng', 'Zhiheng Lyu', 'Yuxuan Zhang', 'Benjamin Schneider', 'Yi Lu', 'Xiang Yue', 'Wenhu Chen'] | ['cs.CL'] | Academic writing requires both coherent text generation and precise citation
of relevant literature. Although recent Retrieval-Augmented Generation (RAG)
systems have significantly improved factual accuracy in general-purpose text
generation, their ability to support professional academic writing remains
limited. In th... | 2025-04-01T14:12:14Z | null | null | null | null | null | null | null | null | null | null |
2,504.00891 | GenPRM: Scaling Test-Time Compute of Process Reward Models via
Generative Reasoning | ['Jian Zhao', 'Runze Liu', 'Kaiyan Zhang', 'Zhimu Zhou', 'Junqi Gao', 'Dong Li', 'Jiafei Lyu', 'Zhouyi Qian', 'Biqing Qi', 'Xiu Li', 'Bowen Zhou'] | ['cs.CL'] | Recent advancements in Large Language Models (LLMs) have shown that it is
promising to utilize Process Reward Models (PRMs) as verifiers to enhance the
performance of LLMs. However, current PRMs face three key challenges: (1)
limited process supervision and generalization capabilities, (2) dependence on
scalar value pr... | 2025-04-01T15:21:05Z | null | null | null | null | null | null | null | null | null | null |
2,504.00954 | IDMR: Towards Instance-Driven Precise Visual Correspondence in
Multimodal Retrieval | ['Bangwei Liu', 'Yicheng Bao', 'Shaohui Lin', 'Xuhong Wang', 'Xin Tan', 'Yingchun Wang', 'Yuan Xie', 'Chaochao Lu'] | ['cs.CV', 'cs.AI'] | Multimodal retrieval systems are becoming increasingly vital for cutting-edge
AI technologies, such as embodied AI and AI-driven digital content industries.
However, current multimodal retrieval tasks lack sufficient complexity and
demonstrate limited practical application value. It spires us to design
Instance-Driven ... | 2025-04-01T16:47:20Z | null | null | null | IDMR: Towards Instance-Driven Precise Visual Correspondence in Multimodal Retrieval | ['Bangwei Liu', 'Yicheng Bao', 'Shaohui Lin', 'Xuhong Wang', 'Xin Tan', 'Yingchun Wang', 'Yuan Xie', 'Chaochao Lu'] | 2,025 | arXiv.org | 1 | 40 | ['Computer Science'] |
2,504.00993 | MedReason: Eliciting Factual Medical Reasoning Steps in LLMs via
Knowledge Graphs | ['Juncheng Wu', 'Wenlong Deng', 'Xingxuan Li', 'Sheng Liu', 'Taomian Mi', 'Yifan Peng', 'Ziyang Xu', 'Yi Liu', 'Hyunjin Cho', 'Chang-In Choi', 'Yihan Cao', 'Hui Ren', 'Xiang Li', 'Xiaoxiao Li', 'Yuyin Zhou'] | ['cs.CL', 'cs.AI'] | Medical tasks such as diagnosis and treatment planning require precise and
complex reasoning, particularly in life-critical domains. Unlike mathematical
reasoning, medical reasoning demands meticulous, verifiable thought processes
to ensure reliability and accuracy. However, there is a notable lack of
datasets that pro... | 2025-04-01T17:31:44Z | 18 pages, 11 figures, 6 tables. Project page:
https://github.com/UCSC-VLAA/MedReason | null | null | null | null | null | null | null | null | null |
2,504.01005 | When To Solve, When To Verify: Compute-Optimal Problem Solving and
Generative Verification for LLM Reasoning | ['Nishad Singhi', 'Hritik Bansal', 'Arian Hosseini', 'Aditya Grover', 'Kai-Wei Chang', 'Marcus Rohrbach', 'Anna Rohrbach'] | ['cs.CL', 'cs.AI', 'cs.LG'] | Scaling test-time compute has emerged as a key strategy for enhancing the
reasoning capabilities of large language models (LLMs), particularly in tasks
like mathematical problem-solving. A traditional approach, Self-Consistency
(SC), generates multiple solutions to a problem and selects the most common
answer via major... | 2025-04-01T17:41:57Z | 29 pages | null | null | When To Solve, When To Verify: Compute-Optimal Problem Solving and Generative Verification for LLM Reasoning | ['Nishad Singhi', 'Hritik Bansal', 'Arian Hosseini', 'Aditya Grover', 'Kai-Wei Chang', 'Marcus Rohrbach', 'Anna Rohrbach'] | 2,025 | arXiv.org | 6 | 45 | ['Computer Science'] |
2,504.01014 | AnimeGamer: Infinite Anime Life Simulation with Next Game State
Prediction | ['Junhao Cheng', 'Yuying Ge', 'Yixiao Ge', 'Jing Liao', 'Ying Shan'] | ['cs.CV'] | Recent advancements in image and video synthesis have opened up new promise
in generative games. One particularly intriguing application is transforming
characters from anime films into interactive, playable entities. This allows
players to immerse themselves in the dynamic anime world as their favorite
characters for ... | 2025-04-01T17:57:18Z | Project released at: https://howe125.github.io/AnimeGamer.github.io/ | null | null | AnimeGamer: Infinite Anime Life Simulation with Next Game State Prediction | ['Junhao Cheng', 'Yuying Ge', 'Yixiao Ge', 'Jing Liao', 'Ying Shan'] | 2,025 | arXiv.org | 4 | 85 | ['Computer Science'] |
2,504.01016 | GeometryCrafter: Consistent Geometry Estimation for Open-world Videos
with Diffusion Priors | ['Tian-Xing Xu', 'Xiangjun Gao', 'Wenbo Hu', 'Xiaoyu Li', 'Song-Hai Zhang', 'Ying Shan'] | ['cs.GR', 'cs.AI', 'cs.CV'] | Despite remarkable advancements in video depth estimation, existing methods
exhibit inherent limitations in achieving geometric fidelity through the
affine-invariant predictions, limiting their applicability in reconstruction
and other metrically grounded downstream tasks. We propose GeometryCrafter, a
novel framework ... | 2025-04-01T17:58:03Z | Project webpage: https://geometrycrafter.github.io/ | null | null | null | null | null | null | null | null | null |
2,504.01017 | Scaling Language-Free Visual Representation Learning | ['David Fan', 'Shengbang Tong', 'Jiachen Zhu', 'Koustuv Sinha', 'Zhuang Liu', 'Xinlei Chen', 'Michael Rabbat', 'Nicolas Ballas', 'Yann LeCun', 'Amir Bar', 'Saining Xie'] | ['cs.CV'] | Visual Self-Supervised Learning (SSL) currently underperforms Contrastive
Language-Image Pretraining (CLIP) in multimodal settings such as Visual
Question Answering (VQA). This multimodal gap is often attributed to the
semantics introduced by language supervision, even though visual SSL and CLIP
models are often traine... | 2025-04-01T17:59:15Z | Project page at https://davidfan.io/webssl/ | null | null | null | null | null | null | null | null | null |
2,504.01081 | ShieldGemma 2: Robust and Tractable Image Content Moderation | ['Wenjun Zeng', 'Dana Kurniawan', 'Ryan Mullins', 'Yuchi Liu', 'Tamoghna Saha', 'Dirichi Ike-Njoku', 'Jindong Gu', 'Yiwen Song', 'Cai Xu', 'Jingjing Zhou', 'Aparna Joshi', 'Shravan Dheep', 'Mani Malek', 'Hamid Palangi', 'Joon Baek', 'Rick Pereira', 'Karthik Narasimhan'] | ['cs.CV', 'cs.CL', 'eess.IV'] | We introduce ShieldGemma 2, a 4B parameter image content moderation model
built on Gemma 3. This model provides robust safety risk predictions across the
following key harm categories: Sexually Explicit, Violence \& Gore, and
Dangerous Content for synthetic images (e.g. output of any image generation
model) and natural... | 2025-04-01T18:00:20Z | null | null | null | ShieldGemma 2: Robust and Tractable Image Content Moderation | ['Wenjun Zeng', 'Dana Kurniawan', 'Ryan Mullins', 'Yuchi Liu', 'Tamoghna Saha', 'Dirichi Ike-Njoku', 'Jindong Gu', 'Yiwen Song', 'Cai Xu', 'Jingjing Zhou', 'Aparna Joshi', 'Shravan Dheep', 'Mani Malek', 'Hamid Palangi', 'Joon Baek', 'Rick Pereira', 'Karthik Narasimhan'] | 2,025 | arXiv.org | 1 | 33 | ['Computer Science', 'Engineering'] |
2,504.01234 | First Field-Trial Demonstration of L4 Autonomous Optical Network for
Distributed AI Training Communication: An LLM-Powered Multi-AI-Agent Solution | ['Yihao Zhang', 'Qizhi Qiu', 'Xiaomin Liu', 'Dianxuan Fu', 'Xingyu Liu', 'Leyan Fei', 'Yuming Cheng', 'Lilin Yi', 'Weisheng Hu', 'Qunbi Zhuge'] | ['cs.MA', 'physics.optics'] | We demonstrate the first cross-domain cross-layer level-4 autonomous optical
network via a multi-AI-agent system. Field trials show 98 percent task
completion rate across the distributed AI training lifecycle-3.2x higher than
single agents using state-of-the-art LLMs. | 2025-04-01T22:48:22Z | Submitted to the PDP session of the Optical Fiber Communications
Conference (OFC) 2025 | null | null | null | null | null | null | null | null | null |
2,504.01308 | Safeguarding Vision-Language Models: Mitigating Vulnerabilities to
Gaussian Noise in Perturbation-based Attacks | ['Jiawei Wang', 'Yushen Zuo', 'Yuanjun Chai', 'Zhendong Liu', 'Yicheng Fu', 'Yichun Feng', 'Kin-Man Lam'] | ['cs.CV'] | Vision-Language Models (VLMs) extend the capabilities of Large Language
Models (LLMs) by incorporating visual information, yet they remain vulnerable
to jailbreak attacks, especially when processing noisy or corrupted images.
Although existing VLMs adopt security measures during training to mitigate such
attacks, vulne... | 2025-04-02T02:35:19Z | null | null | null | null | null | null | null | null | null | null |
2,504.01328 | Slow-Fast Architecture for Video Multi-Modal Large Language Models | ['Min Shi', 'Shihao Wang', 'Chieh-Yun Chen', 'Jitesh Jain', 'Kai Wang', 'Junjun Xiong', 'Guilin Liu', 'Zhiding Yu', 'Humphrey Shi'] | ['cs.CV'] | Balancing temporal resolution and spatial detail under limited compute budget
remains a key challenge for video-based multi-modal large language models
(MLLMs). Existing methods typically compress video representations using
predefined rules before feeding them into the LLM, resulting in irreversible
information loss a... | 2025-04-02T03:24:58Z | Technical report | null | null | null | null | null | null | null | null | null |
2,504.01382 | An Illusion of Progress? Assessing the Current State of Web Agents | ['Tianci Xue', 'Weijian Qi', 'Tianneng Shi', 'Chan Hee Song', 'Boyu Gou', 'Dawn Song', 'Huan Sun', 'Yu Su'] | ['cs.AI', 'cs.CL'] | As digitalization and cloud technologies evolve, the web is becoming
increasingly important in the modern society. Autonomous web agents based on
large language models (LLMs) hold a great potential in work automation. It is
therefore important to accurately measure and monitor the progression of their
capabilities. In ... | 2025-04-02T05:51:29Z | 22 pages, 17 figures, 7 tables | null | null | null | null | null | null | null | null | null |
2,504.01383 | v-CLR: View-Consistent Learning for Open-World Instance Segmentation | ['Chang-Bin Zhang', 'Jinhong Ni', 'Yujie Zhong', 'Kai Han'] | ['cs.CV'] | In this paper, we address the challenging problem of open-world instance
segmentation. Existing works have shown that vanilla visual networks are biased
toward learning appearance information, \eg texture, to recognize objects. This
implicit bias causes the model to fail in detecting novel objects with unseen
textures ... | 2025-04-02T05:52:30Z | Accepted by CVPR 2025, Project page:
https://visual-ai.github.io/vclr, Code: https://github.com/Visual-AI/vCLR | null | null | null | null | null | null | null | null | null |
2,504.0155 | Representation Bending for Large Language Model Safety | ['Ashkan Yousefpour', 'Taeheon Kim', 'Ryan S. Kwon', 'Seungbeen Lee', 'Wonje Jeung', 'Seungju Han', 'Alvin Wan', 'Harrison Ngan', 'Youngjae Yu', 'Jonghyun Choi'] | ['cs.LG', 'cs.CL', 'cs.CR'] | Large Language Models (LLMs) have emerged as powerful tools, but their
inherent safety risks - ranging from harmful content generation to broader
societal harms - pose significant challenges. These risks can be amplified by
the recent adversarial attacks, fine-tuning vulnerabilities, and the increasing
deployment of LL... | 2025-04-02T09:47:01Z | Accepted to ACL 2025 (main) | null | null | null | null | null | null | null | null | null |
2,504.01789 | OpenThaiGPT 1.6 and R1: Thai-Centric Open Source and Reasoning Large
Language Models | ['Sumeth Yuenyong', 'Thodsaporn Chay-intr', 'Kobkrit Viriyayudhakorn'] | ['cs.CL'] | We present OpenThaiGPT 1.6 and R1 (OTG-1.6 and OTG-R1), Thai-centric Large
Language Models (LLMs) developed through distinct methodologies to enhance
generalization and reasoning capabilities. OTG-1.6 employs Task Arithmetic
model merging for broad generalization, while OTG-R1 integrates multi-stage
training with the L... | 2025-04-02T14:55:52Z | null | null | null | OpenThaiGPT 1.6 and R1: Thai-Centric Open Source and Reasoning Large Language Models | ['Sumeth Yuenyong', 'T. Chay-intr', 'K. Viriyayudhakorn'] | 2,025 | arXiv.org | 0 | 8 | ['Computer Science'] |
2,504.01792 | UniViTAR: Unified Vision Transformer with Native Resolution | ['Limeng Qiao', 'Yiyang Gan', 'Bairui Wang', 'Jie Qin', 'Shuang Xu', 'Siqi Yang', 'Lin Ma'] | ['cs.CV'] | Conventional Vision Transformer simplifies visual modeling by standardizing
input resolutions, often disregarding the variability of natural visual data
and compromising spatial-contextual fidelity. While preliminary explorations
have superficially investigated native resolution modeling, existing approaches
still lack... | 2025-04-02T14:59:39Z | null | null | null | UniViTAR: Unified Vision Transformer with Native Resolution | ['Limeng Qiao', 'Yiyang Gan', 'Bairui Wang', 'Jie Qin', 'Shuang Xu', 'Siqi Yang', 'Lin Ma'] | 2,025 | arXiv.org | 0 | 95 | ['Computer Science'] |
2,504.01805 | SpaceR: Reinforcing MLLMs in Video Spatial Reasoning | ['Kun Ouyang', 'Yuanxin Liu', 'Haoning Wu', 'Yi Liu', 'Hao Zhou', 'Jie Zhou', 'Fandong Meng', 'Xu Sun'] | ['cs.CV'] | Video spatial reasoning, which involves inferring the underlying spatial
structure from observed video frames, poses a significant challenge for
existing Multimodal Large Language Models (MLLMs). This limitation stems
primarily from 1) the absence of high-quality datasets for this task, and 2)
the lack of effective tra... | 2025-04-02T15:12:17Z | null | null | null | null | null | null | null | null | null | null |
2,504.01903 | STAR-1: Safer Alignment of Reasoning LLMs with 1K Data | ['Zijun Wang', 'Haoqin Tu', 'Yuhan Wang', 'Juncheng Wu', 'Jieru Mei', 'Brian R. Bartoldson', 'Bhavya Kailkhura', 'Cihang Xie'] | ['cs.CL', 'cs.AI'] | This paper introduces STAR-1, a high-quality, just-1k-scale safety dataset
specifically designed for large reasoning models (LRMs) like DeepSeek-R1. Built
on three core principles -- diversity, deliberative reasoning, and rigorous
filtering -- STAR-1 aims to address the critical needs for safety alignment in
LRMs. Spec... | 2025-04-02T17:04:04Z | null | null | null | null | null | null | null | null | null | null |
2,504.01934 | ILLUME+: Illuminating Unified MLLM with Dual Visual Tokenization and
Diffusion Refinement | ['Runhui Huang', 'Chunwei Wang', 'Junwei Yang', 'Guansong Lu', 'Yunlong Yuan', 'Jianhua Han', 'Lu Hou', 'Wei Zhang', 'Lanqing Hong', 'Hengshuang Zhao', 'Hang Xu'] | ['cs.CV'] | We present ILLUME+ that leverages dual visual tokenization and a diffusion
decoder to improve both deep semantic understanding and high-fidelity image
generation. Existing unified models have struggled to simultaneously handle the
three fundamental capabilities in a unified model: understanding, generation,
and editing... | 2025-04-02T17:45:00Z | null | null | null | ILLUME+: Illuminating Unified MLLM with Dual Visual Tokenization and Diffusion Refinement | ['Runhu Huang', 'Chunwei Wang', 'Junwei Yang', 'Guansong Lu', 'Yunlong Yuan', 'Jianhua Han', 'Lu Hou', 'Wei Zhang', 'Lanqing Hong', 'Hengshuang Zhao', 'Hang Xu'] | 2,025 | arXiv.org | 7 | 80 | ['Computer Science'] |
2,504.01943 | OpenCodeReasoning: Advancing Data Distillation for Competitive Coding | ['Wasi Uddin Ahmad', 'Sean Narenthiran', 'Somshubra Majumdar', 'Aleksander Ficek', 'Siddhartha Jain', 'Jocelyn Huang', 'Vahid Noroozi', 'Boris Ginsburg'] | ['cs.CL'] | Since the advent of reasoning-based large language models, many have found
great success from distilling reasoning capabilities into student models. Such
techniques have significantly bridged the gap between reasoning and standard
LLMs on coding tasks. Despite this, much of the progress on distilling
reasoning models r... | 2025-04-02T17:50:31Z | Work in progress | null | null | OpenCodeReasoning: Advancing Data Distillation for Competitive Coding | ['Wasi Uddin Ahmad', 'Sean Narenthiran', 'Somshubra Majumdar', 'Aleksander Ficek', 'Siddhartha Jain', 'Jocelyn Huang', 'V. Noroozi', 'Boris Ginsburg'] | 2,025 | arXiv.org | 13 | 53 | ['Computer Science'] |
2,504.0216 | Less-to-More Generalization: Unlocking More Controllability by
In-Context Generation | ['Shaojin Wu', 'Mengqi Huang', 'Wenxu Wu', 'Yufeng Cheng', 'Fei Ding', 'Qian He'] | ['cs.CV', 'cs.LG'] | Although subject-driven generation has been extensively explored in image
generation due to its wide applications, it still has challenges in data
scalability and subject expansibility. For the first challenge, moving from
curating single-subject datasets to multiple-subject ones and scaling them is
particularly diffic... | 2025-04-02T22:20:21Z | Project page: https://bytedance.github.io/UNO Code and model:
https://github.com/bytedance/UNO | null | null | null | null | null | null | null | null | null |
2,504.02268 | Advancing Semantic Caching for LLMs with Domain-Specific Embeddings and
Synthetic Data | ['Waris Gill', 'Justin Cechmanek', 'Tyler Hutcherson', 'Srijith Rajamohan', 'Jen Agarwal', 'Muhammad Ali Gulzar', 'Manvinder Singh', 'Benoit Dion'] | ['cs.LG', 'cs.CL'] | This report investigates enhancing semantic caching effectiveness by
employing specialized, fine-tuned embedding models. Semantic caching relies on
embedding similarity rather than exact key matching, presenting unique
challenges in balancing precision, query latency, and computational efficiency.
We propose leveraging... | 2025-04-03T04:27:02Z | Initial study on embedding fine tuning for semantic cache. It also
explores synthetic data. Total pages are 12, including refrences | null | null | Advancing Semantic Caching for LLMs with Domain-Specific Embeddings and Synthetic Data | ['Waris Gill', 'Justin Cechmanek', 'Tyler Hutcherson', 'Srijith Rajamohan', 'Jen Agarwal', 'Muhammad Ali Gulzar', 'Manvinder Singh', 'Benoit Dion'] | 2,025 | arXiv.org | 1 | 38 | ['Computer Science'] |
2,504.02273 | Reasoning Under 1 Billion: Memory-Augmented Reinforcement Learning for
Large Language Models | ['Hung Le', 'Dai Do', 'Dung Nguyen', 'Svetha Venkatesh'] | ['cs.LG'] | Recent advances in fine-tuning large language models (LLMs) with
reinforcement learning (RL) have shown promising improvements in complex
reasoning tasks, particularly when paired with chain-of-thought (CoT)
prompting. However, these successes have been largely demonstrated on
large-scale models with billions of parame... | 2025-04-03T04:46:17Z | preprint,20 pages | null | null | Reasoning Under 1 Billion: Memory-Augmented Reinforcement Learning for Large Language Models | ['Hung Le', 'Dai Do', 'D. Nguyen', 'S. Venkatesh'] | 2,025 | arXiv.org | 1 | 32 | ['Computer Science'] |
2,504.02398 | Scaling Analysis of Interleaved Speech-Text Language Models | ['Gallil Maimon', 'Michael Hassid', 'Amit Roth', 'Yossi Adi'] | ['cs.CL', 'cs.SD', 'eess.AS'] | Existing Speech Language Model (SLM) scaling analysis paints a bleak picture.
They predict that SLMs require much more compute and data compared to text,
leading some to question the feasibility of training high-quality SLMs.
However, modern SLMs are often initialised from pre-trained TextLMs using
speech-text interlea... | 2025-04-03T08:46:56Z | null | null | null | null | null | null | null | null | null | null |
2,504.02436 | SkyReels-A2: Compose Anything in Video Diffusion Transformers | ['Zhengcong Fei', 'Debang Li', 'Di Qiu', 'Jiahua Wang', 'Yikun Dou', 'Rui Wang', 'Jingtao Xu', 'Mingyuan Fan', 'Guibin Chen', 'Yang Li', 'Yahui Zhou'] | ['cs.CV'] | This paper presents SkyReels-A2, a controllable video generation framework
capable of assembling arbitrary visual elements (e.g., characters, objects,
backgrounds) into synthesized videos based on textual prompts while maintaining
strict consistency with reference images for each element. We term this task
elements-to-... | 2025-04-03T09:50:50Z | null | null | null | null | null | null | null | null | null | null |
2,504.02438 | Scaling Video-Language Models to 10K Frames via Hierarchical
Differential Distillation | ['Chuanqi Cheng', 'Jian Guan', 'Wei Wu', 'Rui Yan'] | ['cs.CL', 'cs.AI'] | Long-form video processing fundamentally challenges vision-language models
(VLMs) due to the high computational costs of handling extended temporal
sequences. Existing token pruning and feature merging methods often sacrifice
critical temporal dependencies or dilute semantic information. We introduce
differential disti... | 2025-04-03T09:55:09Z | Accepted by ICML 2025 | null | null | Scaling Video-Language Models to 10K Frames via Hierarchical Differential Distillation | ['Chuanqi Cheng', 'Jian Guan', 'Wei Wu', 'Rui Yan'] | 2,025 | arXiv.org | 3 | 71 | ['Computer Science'] |
2,504.02495 | Inference-Time Scaling for Generalist Reward Modeling | ['Zijun Liu', 'Peiyi Wang', 'Runxin Xu', 'Shirong Ma', 'Chong Ruan', 'Peng Li', 'Yang Liu', 'Yu Wu'] | ['cs.CL', 'cs.AI', 'cs.LG'] | Reinforcement learning (RL) has been widely adopted in post-training for
large language models (LLMs) at scale. Recently, the incentivization of
reasoning capabilities in LLMs from RL indicates that $\textit{proper learning
methods could enable effective inference-time scalability}$. A key challenge of
RL is to obtain ... | 2025-04-03T11:19:49Z | Preprint, under review. 42 pages | null | null | null | null | null | null | null | null | null |
2,504.02508 | APHQ-ViT: Post-Training Quantization with Average Perturbation Hessian
Based Reconstruction for Vision Transformers | ['Zhuguanyu Wu', 'Jiayi Zhang', 'Jiaxin Chen', 'Jinyang Guo', 'Di Huang', 'Yunhong Wang'] | ['cs.CV'] | Vision Transformers (ViTs) have become one of the most commonly used
backbones for vision tasks. Despite their remarkable performance, they often
suffer significant accuracy drops when quantized for practical deployment,
particularly by post-training quantization (PTQ) under ultra-low bits.
Recently, reconstruction-bas... | 2025-04-03T11:48:56Z | Accepted to CVPR 2025 | null | null | null | null | null | null | null | null | null |
2,504.02522 | Charm: The Missing Piece in ViT fine-tuning for Image Aesthetic
Assessment | ['Fatemeh Behrad', 'Tinne Tuytelaars', 'Johan Wagemans'] | ['cs.CV'] | The capacity of Vision transformers (ViTs) to handle variable-sized inputs is
often constrained by computational complexity and batch processing limitations.
Consequently, ViTs are typically trained on small, fixed-size images obtained
through downscaling or cropping. While reducing computational burden, these
methods ... | 2025-04-03T12:19:04Z | CVPR 2025 | null | null | null | null | null | null | null | null | null |
2,504.02534 | Delineate Anything: Resolution-Agnostic Field Boundary Delineation on
Satellite Imagery | ['Mykola Lavreniuk', 'Nataliia Kussul', 'Andrii Shelestov', 'Bohdan Yailymov', 'Yevhenii Salii', 'Volodymyr Kuzin', 'Zoltan Szantoi'] | ['cs.CV'] | The accurate delineation of agricultural field boundaries from satellite
imagery is vital for land management and crop monitoring. However, current
methods face challenges due to limited dataset sizes, resolution discrepancies,
and diverse environmental conditions. We address this by reformulating the task
as instance ... | 2025-04-03T12:37:04Z | null | null | null | null | null | null | null | null | null | null |
2,504.02546 | GPG: A Simple and Strong Reinforcement Learning Baseline for Model
Reasoning | ['Xiangxiang Chu', 'Hailang Huang', 'Xiao Zhang', 'Fei Wei', 'Yong Wang'] | ['cs.LG', 'cs.AI'] | Reinforcement Learning (RL) can directly enhance the reasoning capabilities
of large language models without extensive reliance on Supervised Fine-Tuning
(SFT). In this work, we revisit the traditional Policy Gradient (PG) mechanism
and propose a minimalist RL approach termed Group Policy Gradient (GPG). Unlike
convent... | 2025-04-03T12:53:41Z | null | null | null | null | null | null | null | null | null | null |
2,504.02604 | LinTO Audio and Textual Datasets to Train and Evaluate Automatic Speech
Recognition in Tunisian Arabic Dialect | ['Hedi Naouara', 'Jean-Pierre Lorré', 'Jérôme Louradour'] | ['cs.CL', 'cs.SD', 'eess.AS'] | Developing Automatic Speech Recognition (ASR) systems for Tunisian Arabic
Dialect is challenging due to the dialect's linguistic complexity and the
scarcity of annotated speech datasets. To address these challenges, we propose
the LinTO audio and textual datasets -- comprehensive resources that capture
phonological and... | 2025-04-03T14:05:56Z | null | null | null | LinTO Audio and Textual Datasets to Train and Evaluate Automatic Speech Recognition in Tunisian Arabic Dialect | ['Hedi Naouara', "Jean-Pierre Lorr'e", 'Jérôme Louradour'] | 2,025 | arXiv.org | 0 | 22 | ['Computer Science', 'Engineering'] |
2,504.02801 | F-ViTA: Foundation Model Guided Visible to Thermal Translation | ['Jay N. Paranjape', 'Celso de Melo', 'Vishal M. Patel'] | ['cs.CV'] | Thermal imaging is crucial for scene understanding, particularly in low-light
and nighttime conditions. However, collecting large thermal datasets is costly
and labor-intensive due to the specialized equipment required for infrared
image capture. To address this challenge, researchers have explored
visible-to-thermal i... | 2025-04-03T17:47:06Z | null | null | null | F-ViTA: Foundation Model Guided Visible to Thermal Translation | ['Jay N. Paranjape', 'C. D. Melo', 'Vishal M. Patel'] | 2,025 | arXiv.org | 0 | 31 | ['Computer Science'] |
2,504.02807 | MegaMath: Pushing the Limits of Open Math Corpora | ['Fan Zhou', 'Zengzhi Wang', 'Nikhil Ranjan', 'Zhoujun Cheng', 'Liping Tang', 'Guowei He', 'Zhengzhong Liu', 'Eric P. Xing'] | ['cs.CL', 'cs.AI', 'cs.LG'] | Mathematical reasoning is a cornerstone of human intelligence and a key
benchmark for advanced capabilities in large language models (LLMs). However,
the research community still lacks an open, large-scale, high-quality corpus
tailored to the demands of math-centric LLM pre-training. We present MegaMath,
an open datase... | 2025-04-03T17:52:07Z | 26 pages, 15 figures, 22 tables | null | null | null | null | null | null | null | null | null |
2,504.02949 | VARGPT-v1.1: Improve Visual Autoregressive Large Unified Model via
Iterative Instruction Tuning and Reinforcement Learning | ['Xianwei Zhuang', 'Yuxin Xie', 'Yufan Deng', 'Dongchao Yang', 'Liming Liang', 'Jinghan Ru', 'Yuguo Yin', 'Yuexian Zou'] | ['cs.CV', 'cs.AI'] | In this work, we present VARGPT-v1.1, an advanced unified visual
autoregressive model that builds upon our previous framework VARGPT. The model
preserves the dual paradigm of next-token prediction for visual understanding
and next-scale generation for image synthesis. Specifically, VARGPT-v1.1
integrates: (1) a novel t... | 2025-04-03T18:06:28Z | Code is available at: https://github.com/VARGPT-family/VARGPT-v1.1.
arXiv admin note: text overlap with arXiv:2501.12327 | null | null | VARGPT-v1.1: Improve Visual Autoregressive Large Unified Model via Iterative Instruction Tuning and Reinforcement Learning | ['Xianwei Zhuang', 'Yuxin Xie', 'Yufan Deng', 'Dongchao Yang', 'Liming Liang', 'Jinghan Ru', 'Yuguo Yin', 'Yuexian Zou'] | 2,025 | arXiv.org | 5 | 86 | ['Computer Science'] |
2,504.03036 | IPA-CHILDES & G2P+: Feature-Rich Resources for Cross-Lingual Phonology
and Phonemic Language Modeling | ['Zébulon Goriely', 'Paula Buttery'] | ['cs.CL'] | In this paper, we introduce two resources: (i) G2P+, a tool for converting
orthographic datasets to a consistent phonemic representation; and (ii) IPA
CHILDES, a phonemic dataset of child-centered speech across 31 languages. Prior
tools for grapheme-to-phoneme conversion result in phonemic vocabularies that
are inconsi... | 2025-04-03T21:22:19Z | Accepted to CoNLL 2025 | null | null | IPA-CHILDES & G2P+: Feature-Rich Resources for Cross-Lingual Phonology and Phonemic Language Modeling | ['Zébulon Goriely', 'Paula Buttery'] | 2,025 | arXiv.org | 1 | 92 | ['Computer Science'] |
2,504.0316 | DeepResearcher: Scaling Deep Research via Reinforcement Learning in
Real-world Environments | ['Yuxiang Zheng', 'Dayuan Fu', 'Xiangkun Hu', 'Xiaojie Cai', 'Lyumanshan Ye', 'Pengrui Lu', 'Pengfei Liu'] | ['cs.AI', 'cs.CL', 'cs.LG'] | Large Language Models (LLMs) equipped with web search capabilities have
demonstrated impressive potential for deep research tasks. However, current
approaches predominantly rely on either manually engineered prompts (prompt
engineering-based) with brittle performance or reinforcement learning within
controlled Retrieva... | 2025-04-04T04:41:28Z | null | null | null | null | null | null | null | null | null | null |
2,504.03302 | Noise Augmented Fine Tuning for Mitigating Hallucinations in Large
Language Models | ['Afshin Khadangi', 'Amir Sartipi', 'Igor Tchappi', 'Ramin Bahmani'] | ['cs.CL', 'cs.AI'] | Large language models (LLMs) often produce inaccurate or misleading
content-hallucinations. To address this challenge, we introduce Noise-Augmented
Fine-Tuning (NoiseFiT), a novel framework that leverages adaptive noise
injection based on the signal-to-noise ratio (SNR) to enhance model robustness.
In particular, Noise... | 2025-04-04T09:27:19Z | null | null | null | null | null | null | null | null | null | null |
2,504.03338 | BabyLM's First Words: Word Segmentation as a Phonological Probing Task | ['Zébulon Goriely', 'Paula Buttery'] | ['cs.CL'] | Language models provide a key framework for studying linguistic theories
based on prediction, but phonological analysis using large language models
(LLMs) is difficult; there are few phonological benchmarks beyond English and
the standard input representation used in LLMs (subwords of graphemes) is not
suitable for ana... | 2025-04-04T10:42:56Z | Accepted to CoNLL 2025 | null | null | BabyLM's First Words: Word Segmentation as a Phonological Probing Task | ['Zébulon Goriely', 'Paula Buttery'] | 2,025 | arXiv.org | 2 | 72 | ['Computer Science'] |
2,504.03546 | MultiMed-ST: Large-scale Many-to-many Multilingual Medical Speech
Translation | ['Khai Le-Duc', 'Tuyen Tran', 'Bach Phan Tat', 'Nguyen Kim Hai Bui', 'Quan Dang', 'Hung-Phong Tran', 'Thanh-Thuy Nguyen', 'Ly Nguyen', 'Tuan-Minh Phan', 'Thi Thu Phuong Tran', 'Chris Ngo', 'Nguyen X. Khanh', 'Thanh Nguyen-Tang'] | ['cs.CL', 'cs.AI', 'cs.LG', 'cs.SD', 'eess.AS'] | Multilingual speech translation (ST) in the medical domain enhances patient
care by enabling efficient communication across language barriers, alleviating
specialized workforce shortages, and facilitating improved diagnosis and
treatment, particularly during pandemics. In this work, we present the first
systematic stud... | 2025-04-04T15:49:17Z | Preprint, 122 pages | null | null | MultiMed-ST: Large-scale Many-to-many Multilingual Medical Speech Translation | ['Khai Le-Duc', 'Tuyen Tran', 'Bach Phan Tat', 'Nguyen Kim Hai Bui', 'Quan Dang', 'Hung-Phong Tran', 'Thanh-Thuy Nguyen', 'Ly Nguyen', 'Tuan-Minh Phan', 'Thi Thu Phuong Tran', 'Chris Ngo', 'Nguyen X. Khanh', 'Thanh Nguyen-Tang'] | 2,025 | arXiv.org | 0 | 0 | ['Computer Science', 'Engineering'] |
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