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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2,506.002 | Structuring Radiology Reports: Challenging LLMs with Lightweight Models | ['Johannes Moll', 'Louisa Fay', 'Asfandyar Azhar', 'Sophie Ostmeier', 'Tim Lueth', 'Sergios Gatidis', 'Curtis Langlotz', 'Jean-Benoit Delbrouck'] | ['cs.CL', 'cs.LG'] | Radiology reports are critical for clinical decision-making but often lack a
standardized format, limiting both human interpretability and machine learning
(ML) applications. While large language models (LLMs) have shown strong
capabilities in reformatting clinical text, their high computational
requirements, lack of t... | 2025-05-30T20:12:51Z | null | null | null | null | null | null | null | null | null | null |
2,506.00227 | Ctrl-Crash: Controllable Diffusion for Realistic Car Crashes | ['Anthony Gosselin', 'Ge Ya Luo', 'Luis Lara', 'Florian Golemo', 'Derek Nowrouzezahrai', 'Liam Paull', 'Alexia Jolicoeur-Martineau', 'Christopher Pal'] | ['cs.CV', 'cs.AI', 'cs.RO'] | Video diffusion techniques have advanced significantly in recent years;
however, they struggle to generate realistic imagery of car crashes due to the
scarcity of accident events in most driving datasets. Improving traffic safety
requires realistic and controllable accident simulations. To tackle the
problem, we propos... | 2025-05-30T21:04:38Z | Under review | null | null | null | null | null | null | null | null | null |
2,506.00288 | Emergent Abilities of Large Language Models under Continued Pretraining
for Language Adaptation | ['Ahmed Elhady', 'Eneko Agirre', 'Mikel Artetxe'] | ['cs.CL', 'cs.AI'] | Continued pretraining (CPT) is a popular approach to adapt existing large
language models (LLMs) to new languages. When doing so, it is common practice
to include a portion of English data in the mixture, but its role has not been
carefully studied to date. In this work, we show that including English does
not impact v... | 2025-05-30T22:31:59Z | To appear in ACL 2025 Main | null | null | Emergent Abilities of Large Language Models under Continued Pretraining for Language Adaptation | ['Ahmed Elhady', 'Eneko Agirre', 'Mikel Artetxe'] | 2,025 | arXiv.org | 0 | 39 | ['Computer Science'] |
2,506.00338 | OWSM v4: Improving Open Whisper-Style Speech Models via Data Scaling and
Cleaning | ['Yifan Peng', 'Shakeel Muhammad', 'Yui Sudo', 'William Chen', 'Jinchuan Tian', 'Chyi-Jiunn Lin', 'Shinji Watanabe'] | ['cs.CL', 'cs.SD', 'eess.AS'] | The Open Whisper-style Speech Models (OWSM) project has developed a series of
fully open speech foundation models using academic-scale resources, but their
training data remains insufficient. This work enhances OWSM by integrating
YODAS, a large-scale web-crawled dataset with a Creative Commons license.
However, incorp... | 2025-05-31T01:44:44Z | Accepted at INTERSPEECH 2025 | null | null | null | null | null | null | null | null | null |
2,506.00385 | MagiCodec: Simple Masked Gaussian-Injected Codec for High-Fidelity
Reconstruction and Generation | ['Yakun Song', 'Jiawei Chen', 'Xiaobin Zhuang', 'Chenpeng Du', 'Ziyang Ma', 'Jian Wu', 'Jian Cong', 'Dongya Jia', 'Zhuo Chen', 'Yuping Wang', 'Yuxuan Wang', 'Xie Chen'] | ['cs.SD', 'cs.AI', 'cs.LG', 'eess.AS'] | Neural audio codecs have made significant strides in efficiently mapping raw
audio waveforms into discrete token representations, which are foundational for
contemporary audio generative models. However, most existing codecs are
optimized primarily for reconstruction quality, often at the expense of the
downstream mode... | 2025-05-31T04:31:02Z | 18 pages, 3 figures. The code and pre-trained models are available at
https://github.com/Ereboas/MagiCodec | null | null | null | null | null | null | null | null | null |
2,506.00391 | SHARE: An SLM-based Hierarchical Action CorREction Assistant for
Text-to-SQL | ['Ge Qu', 'Jinyang Li', 'Bowen Qin', 'Xiaolong Li', 'Nan Huo', 'Chenhao Ma', 'Reynold Cheng'] | ['cs.CL'] | Current self-correction approaches in text-to-SQL face two critical
limitations: 1) Conventional self-correction methods rely on recursive
self-calls of LLMs, resulting in multiplicative computational overhead, and 2)
LLMs struggle to implement effective error detection and correction for
declarative SQL queries, as th... | 2025-05-31T04:51:12Z | Accepted to ACL 2025 Main | null | null | SHARE: An SLM-based Hierarchical Action CorREction Assistant for Text-to-SQL | ['Ge Qu', 'Jinyang Li', 'Bowen Qin', 'Xiaolong Li', 'Nan Huo', 'Chenhao Ma', 'Reynold Cheng'] | 2,025 | arXiv.org | 0 | 49 | ['Computer Science'] |
2,506.00421 | Enabling Chatbots with Eyes and Ears: An Immersive Multimodal
Conversation System for Dynamic Interactions | ['Jihyoung Jang', 'Minwook Bae', 'Minji Kim', 'Dilek Hakkani-Tur', 'Hyounghun Kim'] | ['cs.CL', 'cs.AI', 'cs.CV'] | As chatbots continue to evolve toward human-like, real-world, interactions,
multimodality remains an active area of research and exploration. So far,
efforts to integrate multimodality into chatbots have primarily focused on
image-centric tasks, such as visual dialogue and image-based instructions,
placing emphasis on ... | 2025-05-31T06:50:51Z | ACL 2025 (32 pages); Project website: https://m3c-dataset.github.io/ | null | null | null | null | null | null | null | null | null |
2,506.00469 | Massively Multilingual Adaptation of Large Language Models Using
Bilingual Translation Data | ['Shaoxiong Ji', 'Zihao Li', 'Jaakko Paavola', 'Indraneil Paul', 'Hengyu Luo', 'Jörg Tiedemann'] | ['cs.CL'] | This paper investigates a critical design decision in the practice of
massively multilingual continual pre-training -- the inclusion of parallel
data. Specifically, we study the impact of bilingual translation data for
massively multilingual language adaptation of the Llama3 family of models to
500 languages. To this e... | 2025-05-31T08:37:17Z | EMMA-500 Gen 2; refer to Gen 1 in arXiv:2409.17892 | null | null | null | null | null | null | null | null | null |
2,506.00649 | GuideX: Guided Synthetic Data Generation for Zero-Shot Information
Extraction | ['Neil De La Fuente', 'Oscar Sainz', 'Iker García-Ferrero', 'Eneko Agirre'] | ['cs.CL'] | Information Extraction (IE) systems are traditionally domain-specific,
requiring costly adaptation that involves expert schema design, data
annotation, and model training. While Large Language Models have shown promise
in zero-shot IE, performance degrades significantly in unseen domains where
label definitions differ.... | 2025-05-31T17:36:18Z | ACL Findings 2025 | null | null | GuideX: Guided Synthetic Data Generation for Zero-Shot Information Extraction | ['Neil De La Fuente', 'Oscar Sainz', "Iker Garc'ia-Ferrero", 'Eneko Agirre'] | 2,025 | arXiv.org | 0 | 52 | ['Computer Science'] |
2,506.00679 | CineMA: A Foundation Model for Cine Cardiac MRI | ['Yunguan Fu', 'Weixi Yi', 'Charlotte Manisty', 'Anish N Bhuva', 'Thomas A Treibel', 'James C Moon', 'Matthew J Clarkson', 'Rhodri Huw Davies', 'Yipeng Hu'] | ['eess.IV', 'cs.AI', 'cs.CV'] | Cardiac magnetic resonance (CMR) is a key investigation in clinical
cardiovascular medicine and has been used extensively in population research.
However, extracting clinically important measurements such as ejection fraction
for diagnosing cardiovascular diseases remains time-consuming and subjective.
We developed Cin... | 2025-05-31T19:12:34Z | null | null | null | CineMA: A Foundation Model for Cine Cardiac MRI | ['Yunguan Fu', 'Weixi Yi', 'Charlotte Manisty', 'A. Bhuva', 'Thomas A. Treibel', 'James C. Moon', 'Matthew J. Clarkson', 'R. Davies', 'Yipeng Hu'] | 2,025 | arXiv.org | 0 | 29 | ['Computer Science'] |
2,506.00711 | QoQ-Med: Building Multimodal Clinical Foundation Models with
Domain-Aware GRPO Training | ['Wei Dai', 'Peilin Chen', 'Chanakya Ekbote', 'Paul Pu Liang'] | ['cs.LG', 'cs.AI', 'cs.CV'] | Clinical decision-making routinely demands reasoning over heterogeneous data,
yet existing multimodal language models (MLLMs) remain largely vision-centric
and fail to generalize across clinical specialties. To bridge this gap, we
introduce QoQ-Med-7B/32B, the first open generalist clinical foundation model
that jointl... | 2025-05-31T21:02:52Z | null | null | null | null | null | null | null | null | null | null |
2,506.00782 | Jailbreak-R1: Exploring the Jailbreak Capabilities of LLMs via
Reinforcement Learning | ['Weiyang Guo', 'Zesheng Shi', 'Zhuo Li', 'Yequan Wang', 'Xuebo Liu', 'Wenya Wang', 'Fangming Liu', 'Min Zhang', 'Jing Li'] | ['cs.AI'] | As large language models (LLMs) grow in power and influence, ensuring their
safety and preventing harmful output becomes critical. Automated red teaming
serves as a tool to detect security vulnerabilities in LLMs without manual
labor. However, most existing methods struggle to balance the effectiveness and
diversity of... | 2025-06-01T02:19:46Z | 21 pages, 8 figures | null | null | null | null | null | null | null | null | null |
2,506.00863 | L3Cube-MahaEmotions: A Marathi Emotion Recognition Dataset with
Synthetic Annotations using CoTR prompting and Large Language Models | ['Nidhi Kowtal', 'Raviraj Joshi'] | ['cs.CL', 'cs.LG'] | Emotion recognition in low-resource languages like Marathi remains
challenging due to limited annotated data. We present L3Cube-MahaEmotions, a
high-quality Marathi emotion recognition dataset with 11 fine-grained emotion
labels. The training data is synthetically annotated using large language
models (LLMs), while the... | 2025-06-01T07:01:34Z | null | null | null | L3Cube-MahaEmotions: A Marathi Emotion Recognition Dataset with Synthetic Annotations using CoTR prompting and Large Language Models | ['Nidhi Kowtal', 'Raviraj Joshi'] | 2,025 | arXiv.org | 0 | 25 | ['Computer Science'] |
2,506.00956 | Continual-MEGA: A Large-scale Benchmark for Generalizable Continual
Anomaly Detection | ['Geonu Lee', 'Yujeong Oh', 'Geonhui Jang', 'Soyoung Lee', 'Jeonghyo Song', 'Sungmin Cha', 'YoungJoon Yoo'] | ['cs.CV'] | In this paper, we introduce a new benchmark for continual learning in anomaly
detection, aimed at better reflecting real-world deployment scenarios. Our
benchmark, Continual-MEGA, includes a large and diverse dataset that
significantly expands existing evaluation settings by combining carefully
curated existing dataset... | 2025-06-01T11:00:24Z | null | null | null | null | null | null | null | null | null | null |
2,506.00975 | NTPP: Generative Speech Language Modeling for Dual-Channel Spoken
Dialogue via Next-Token-Pair Prediction | ['Qichao Wang', 'Ziqiao Meng', 'Wenqian Cui', 'Yifei Zhang', 'Pengcheng Wu', 'Bingzhe Wu', 'Irwin King', 'Liang Chen', 'Peilin Zhao'] | ['cs.CL', 'cs.AI', 'cs.SD', 'eess.AS'] | Inspired by the impressive capabilities of GPT-4o, there is growing interest
in enabling speech language models (SLMs) to engage in natural, fluid spoken
interactions with humans. Recent advancements have led to the development of
several SLMs that demonstrate promising results in this area. However, current
approaches... | 2025-06-01T12:01:40Z | Accepted by ICML 2025 | null | null | NTPP: Generative Speech Language Modeling for Dual-Channel Spoken Dialogue via Next-Token-Pair Prediction | ['Qichao Wang', 'Ziqiao Meng', 'Wenqian Cui', 'Yifei Zhang', 'Pengcheng Wu', 'Bingzhe Wu', 'Irwin King', 'Liang Chen', 'Peilin Zhao'] | 2,025 | arXiv.org | 0 | 0 | ['Computer Science', 'Engineering'] |
2,506.00981 | What do self-supervised speech models know about Dutch? Analyzing
advantages of language-specific pre-training | ['Marianne de Heer Kloots', 'Hosein Mohebbi', 'Charlotte Pouw', 'Gaofei Shen', 'Willem Zuidema', 'Martijn Bentum'] | ['cs.CL', 'cs.AI', 'cs.SD', 'eess.AS'] | How language-specific are speech representations learned by self-supervised
models? Existing work has shown that a range of linguistic features can be
successfully decoded from end-to-end models trained only on speech recordings.
However, it's less clear to what extent pre-training on specific languages
improves langua... | 2025-06-01T12:25:13Z | Accepted to Interspeech 2025. For model, code, and materials, see
https://github.com/mdhk/SSL-NL-eval | Proc. INTERSPEECH 2025 | 10.21437/Interspeech.2025-1526 | null | null | null | null | null | null | null |
2,506.00993 | FlexSelect: Flexible Token Selection for Efficient Long Video
Understanding | ['Yunzhu Zhang', 'Yu Lu', 'Tianyi Wang', 'Fengyun Rao', 'Yi Yang', 'Linchao Zhu'] | ['cs.CV'] | Long-form video understanding poses a significant challenge for video large
language models (VideoLLMs) due to prohibitively high computational and memory
demands. In this paper, we propose FlexSelect, a flexible and efficient token
selection strategy for processing long videos. FlexSelect identifies and
retains the mo... | 2025-06-01T12:49:39Z | null | null | null | FlexSelect: Flexible Token Selection for Efficient Long Video Understanding | ['Yunzhu Zhang', 'Yu Lu', 'Tianyi Wang', 'Fengyun Rao', 'Yi Yang', 'Linchao Zhu'] | 2,025 | arXiv.org | 0 | 38 | ['Computer Science'] |
2,506.01078 | GThinker: Towards General Multimodal Reasoning via Cue-Guided Rethinking | ['Yufei Zhan', 'Ziheng Wu', 'Yousong Zhu', 'Rongkun Xue', 'Ruipu Luo', 'Zhenghao Chen', 'Can Zhang', 'Yifan Li', 'Zhentao He', 'Zheming Yang', 'Ming Tang', 'Minghui Qiu', 'Jinqiao Wang'] | ['cs.CV', 'cs.AI'] | Despite notable advancements in multimodal reasoning, leading Multimodal
Large Language Models (MLLMs) still underperform on vision-centric multimodal
reasoning tasks in general scenarios. This shortfall stems from their
predominant reliance on logic- and knowledge-based slow thinking strategies,
while effective for do... | 2025-06-01T16:28:26Z | Tech report | null | null | GThinker: Towards General Multimodal Reasoning via Cue-Guided Rethinking | ['Yufei Zhan', 'Ziheng Wu', 'Yousong Zhu', 'Rongkun Xue', 'Ruipu Luo', 'Zhenghao Chen', 'Can Zhang', 'Yifan Li', 'Zhentao He', 'Zheming Yang', 'Ming Tang', 'Minghui Qiu', 'Jinqiao Wang'] | 2,025 | arXiv.org | 0 | 66 | ['Computer Science'] |
2,506.01084 | zip2zip: Inference-Time Adaptive Vocabularies for Language Models via
Token Compression | ['Saibo Geng', 'Nathan Ranchin', 'Yunzhen yao', 'Maxime Peyrard', 'Chris Wendler', 'Michael Gastpar', 'Robert West'] | ['cs.CL', 'cs.LG'] | Tokenization efficiency plays a critical role in the performance and cost of
large language models (LLMs), yet most models rely on static tokenizers
optimized for general-purpose corpora. These tokenizers' fixed vocabularies
often fail to adapt to domain- or language-specific inputs, leading to longer
token sequences a... | 2025-06-01T17:03:02Z | Code will be released at https://github.com/epfl-dlab/zip2zip | null | null | zip2zip: Inference-Time Adaptive Vocabularies for Language Models via Token Compression | ['Saibo Geng', 'Nathan Ranchin', 'Yunzhen Yao', 'Maxime Peyrard', 'Chris Wendler', 'Michael Gastpar', 'Robert West'] | 2,025 | arXiv.org | 0 | 49 | ['Computer Science'] |
2,506.01262 | Exploring the Potential of LLMs as Personalized Assistants: Dataset,
Evaluation, and Analysis | ['Jisoo Mok', 'Ik-hwan Kim', 'Sangkwon Park', 'Sungroh Yoon'] | ['cs.CL'] | Personalized AI assistants, a hallmark of the human-like capabilities of
Large Language Models (LLMs), are a challenging application that intertwines
multiple problems in LLM research. Despite the growing interest in the
development of personalized assistants, the lack of an open-source
conversational dataset tailored ... | 2025-06-02T02:25:46Z | ACL 2025 | null | null | Exploring the Potential of LLMs as Personalized Assistants: Dataset, Evaluation, and Analysis | ['J. Mok', 'Ik-hwan Kim', 'Sangkwon Park', 'Sungroh Yoon'] | 2,025 | arXiv.org | 0 | 49 | ['Computer Science'] |
2,506.01357 | KokoroChat: A Japanese Psychological Counseling Dialogue Dataset
Collected via Role-Playing by Trained Counselors | ['Zhiyang Qi', 'Takumasa Kaneko', 'Keiko Takamizo', 'Mariko Ukiyo', 'Michimasa Inaba'] | ['cs.CL', 'cs.AI'] | Generating psychological counseling responses with language models relies
heavily on high-quality datasets. Crowdsourced data collection methods require
strict worker training, and data from real-world counseling environments may
raise privacy and ethical concerns. While recent studies have explored using
large languag... | 2025-06-02T06:20:53Z | Accepted to ACL 2025 Main Conference | null | null | KokoroChat: A Japanese Psychological Counseling Dialogue Dataset Collected via Role-Playing by Trained Counselors | ['Zhiyang Qi', 'Takumasa Kaneko', 'Keiko Takamizo', 'Mariko Ukiyo', 'Michimasa Inaba'] | 2,025 | arXiv.org | 0 | 34 | ['Computer Science'] |
2,506.01391 | AgentCPM-GUI: Building Mobile-Use Agents with Reinforcement Fine-Tuning | ['Zhong Zhang', 'Yaxi Lu', 'Yikun Fu', 'Yupeng Huo', 'Shenzhi Yang', 'Yesai Wu', 'Han Si', 'Xin Cong', 'Haotian Chen', 'Yankai Lin', 'Jie Xie', 'Wei Zhou', 'Wang Xu', 'Yuanheng Zhang', 'Zhou Su', 'Zhongwu Zhai', 'Xiaoming Liu', 'Yudong Mei', 'Jianming Xu', 'Hongyan Tian', 'Chongyi Wang', 'Chi Chen', 'Yuan Yao', 'Zhiyua... | ['cs.AI', 'cs.CL', 'cs.CV', 'cs.HC', 'I.2.8; I.2.7; I.2.10; H.5.2'] | The recent progress of large language model agents has opened new
possibilities for automating tasks through graphical user interfaces (GUIs),
especially in mobile environments where intelligent interaction can greatly
enhance usability. However, practical deployment of such agents remains
constrained by several key ch... | 2025-06-02T07:30:29Z | Updated results in Table 2 and Table 3; The project is available at
https://github.com/OpenBMB/AgentCPM-GUI | null | null | AgentCPM-GUI: Building Mobile-Use Agents with Reinforcement Fine-Tuning | ['Zhong Zhang', 'Ya-Ting Lu', 'Yikun Fu', 'Yupeng Huo', 'Shenzhi Yang', 'Yesai Wu', 'Han Si', 'Xin Cong', 'Haotian Chen', 'Yankai Lin', 'Jie Xie', 'Wei Zhou', 'Wang Xu', 'Yuanheng Zhang', 'Zhou Su', 'Zhongwu Zhai', 'Xiao-Meng Liu', 'Yudong Mei', 'Jianming Xu', 'Hongyan Tian', 'Chongyi Wang', 'Chi Chen', 'Yuan Yao', 'Zh... | 2,025 | arXiv.org | 0 | 58 | ['Computer Science'] |
2,506.01413 | Incentivizing Reasoning for Advanced Instruction-Following of Large
Language Models | ['Yulei Qin', 'Gang Li', 'Zongyi Li', 'Zihan Xu', 'Yuchen Shi', 'Zhekai Lin', 'Xiao Cui', 'Ke Li', 'Xing Sun'] | ['cs.CV', 'cs.AI', 'cs.CL', 'cs.LG'] | Existing large language models (LLMs) face challenges of following complex
instructions, especially when multiple constraints are present and organized in
paralleling, chaining, and branching structures. One intuitive solution, namely
chain-of-thought (CoT), is expected to universally improve capabilities of
LLMs. Howe... | 2025-06-02T08:11:44Z | 13 pages of main body, 3 tables, 5 figures, 45 pages of appendix | null | null | null | null | null | null | null | null | null |
2,506.01666 | Synthesis of discrete-continuous quantum circuits with multimodal
diffusion models | ['Florian Fürrutter', 'Zohim Chandani', 'Ikko Hamamura', 'Hans J. Briegel', 'Gorka Muñoz-Gil'] | ['quant-ph', 'cs.AI', 'cs.LG'] | Efficiently compiling quantum operations remains a major bottleneck in
scaling quantum computing. Today's state-of-the-art methods achieve low
compilation error by combining search algorithms with gradient-based parameter
optimization, but they incur long runtimes and require multiple calls to
quantum hardware or expen... | 2025-06-02T13:35:33Z | Main Text: 10 pages and 5 figures; Appendix: 17 pages, 7 figures and
1 table. Code available at: https://github.com/FlorianFuerrutter/genQC | null | null | null | null | null | null | null | null | null |
2,506.01801 | OmniV2V: Versatile Video Generation and Editing via Dynamic Content
Manipulation | ['Sen Liang', 'Zhentao Yu', 'Zhengguang Zhou', 'Teng Hu', 'Hongmei Wang', 'Yi Chen', 'Qin Lin', 'Yuan Zhou', 'Xin Li', 'Qinglin Lu', 'Zhibo Chen'] | ['cs.CV'] | The emergence of Diffusion Transformers (DiT) has brought significant
advancements to video generation, especially in text-to-video and
image-to-video tasks. Although video generation is widely applied in various
fields, most existing models are limited to single scenarios and cannot perform
diverse video generation an... | 2025-06-02T15:42:06Z | null | null | null | OmniV2V: Versatile Video Generation and Editing via Dynamic Content Manipulation | ['Sen Liang', 'Zhentao Yu', 'Zhengguang Zhou', 'Teng Hu', 'Hongmei Wang', 'Yi Chen', 'Qin Lin', 'Yuan Zhou', 'Xin Li', 'Qinglin Lu', 'Zhibo Chen'] | 2,025 | arXiv.org | 0 | 61 | ['Computer Science'] |
2,506.01806 | Ridgeformer: Mutli-Stage Contrastive Training For Fine-grained
Cross-Domain Fingerprint Recognition | ['Shubham Pandey', 'Bhavin Jawade', 'Srirangaraj Setlur'] | ['cs.CV', 'cs.AI'] | The increasing demand for hygienic and portable biometric systems has
underscored the critical need for advancements in contactless fingerprint
recognition. Despite its potential, this technology faces notable challenges,
including out-of-focus image acquisition, reduced contrast between fingerprint
ridges and valleys,... | 2025-06-02T15:51:45Z | Accepted to IEEE International Conference on Image Processing 2025 | null | null | Ridgeformer: Mutli-Stage Contrastive Training For Fine-grained Cross-Domain Fingerprint Recognition | ['Shubham Pandey', 'Bhavin Jawade', 'Srirangaraj Setlur'] | 2,025 | arXiv.org | 0 | 22 | ['Computer Science'] |
2,506.01833 | SPACE: Your Genomic Profile Predictor is a Powerful DNA Foundation Model | ['Zhao Yang', 'Jiwei Zhu', 'Bing Su'] | ['cs.LG', 'q-bio.GN'] | Inspired by the success of unsupervised pre-training paradigms, researchers
have applied these approaches to DNA pre-training. However, we argue that these
approaches alone yield suboptimal results because pure DNA sequences lack
sufficient information, since their functions are regulated by genomic profiles
like chrom... | 2025-06-02T16:23:05Z | Accepted to ICML 2025 | null | null | null | null | null | null | null | null | null |
2,506.01844 | SmolVLA: A Vision-Language-Action Model for Affordable and Efficient
Robotics | ['Mustafa Shukor', 'Dana Aubakirova', 'Francesco Capuano', 'Pepijn Kooijmans', 'Steven Palma', 'Adil Zouitine', 'Michel Aractingi', 'Caroline Pascal', 'Martino Russi', 'Andres Marafioti', 'Simon Alibert', 'Matthieu Cord', 'Thomas Wolf', 'Remi Cadene'] | ['cs.LG', 'cs.RO'] | Vision-language models (VLMs) pretrained on large-scale multimodal datasets
encode rich visual and linguistic knowledge, making them a strong foundation
for robotics. Rather than training robotic policies from scratch, recent
approaches adapt VLMs into vision-language-action (VLA) models that enable
natural language-dr... | 2025-06-02T16:30:19Z | 24 pages. Code and assets: https://github.com/huggingface/lerobot | null | null | SmolVLA: A Vision-Language-Action Model for Affordable and Efficient Robotics | ['Mustafa Shukor', 'Dana Aubakirova', 'Francesco Capuano', 'Pepijn Kooijmans', 'Steven Palma', 'Adil Zouitine', 'Michel Aractingi', 'Caroline Pascal', 'Martino Russi', 'Andrés Marafioti', 'Simon Alibert', 'Matthieu Cord', 'Thomas Wolf', 'Rémi Cadène'] | 2,025 | arXiv.org | 0 | 85 | ['Computer Science'] |
2,506.01853 | ShapeLLM-Omni: A Native Multimodal LLM for 3D Generation and
Understanding | ['Junliang Ye', 'Zhengyi Wang', 'Ruowen Zhao', 'Shenghao Xie', 'Jun Zhu'] | ['cs.CV'] | Recently, the powerful text-to-image capabilities of ChatGPT-4o have led to
growing appreciation for native multimodal large language models. However, its
multimodal capabilities remain confined to images and text. Yet beyond images,
the ability to understand and generate 3D content is equally crucial. To
address this ... | 2025-06-02T16:40:50Z | Project page: https://github.com/JAMESYJL/ShapeLLM-Omni | null | null | null | null | null | null | null | null | null |
2,506.01937 | RewardBench 2: Advancing Reward Model Evaluation | ['Saumya Malik', 'Valentina Pyatkin', 'Sander Land', 'Jacob Morrison', 'Noah A. Smith', 'Hannaneh Hajishirzi', 'Nathan Lambert'] | ['cs.CL'] | Reward models are used throughout the post-training of language models to
capture nuanced signals from preference data and provide a training target for
optimization across instruction following, reasoning, safety, and more domains.
The community has begun establishing best practices for evaluating reward
models, from ... | 2025-06-02T17:54:04Z | Data, models, and leaderboard available at
https://huggingface.co/collections/allenai/reward-bench-2-683d2612a4b3e38a3e53bb51 | null | null | null | null | null | null | null | null | null |
2,506.01949 | IMAGHarmony: Controllable Image Editing with Consistent Object Quantity
and Layout | ['Fei Shen', 'Xiaoyu Du', 'Yutong Gao', 'Jian Yu', 'Yushe Cao', 'Xing Lei', 'Jinhui Tang'] | ['cs.CV'] | Recent diffusion models have advanced image editing by enhancing visual
quality and control, supporting broad applications across creative and
personalized domains. However, current image editing largely overlooks
multi-object scenarios, where precise control over object categories, counts,
and spatial layouts remains ... | 2025-06-02T17:59:09Z | null | null | null | IMAGHarmony: Controllable Image Editing with Consistent Object Quantity and Layout | ['Fei Shen', 'Xiaoyu Du', 'Yutong Gao', 'Jian Yu', 'Yushe Cao', 'Xing Lei', 'Jinhui Tang'] | 2,025 | arXiv.org | 0 | 69 | ['Computer Science'] |
2,506.02018 | Enhancing Paraphrase Type Generation: The Impact of DPO and RLHF
Evaluated with Human-Ranked Data | ['Christopher Lee Lübbers'] | ['cs.CL', 'I.2.7'] | Paraphrasing re-expresses meaning to enhance applications like text
simplification, machine translation, and question-answering. Specific
paraphrase types facilitate accurate semantic analysis and robust language
models. However, existing paraphrase-type generation methods often misalign
with human preferences due to r... | 2025-05-28T07:52:18Z | 21 pages, 11 figures. Master's thesis, University of Goettingen,
December 2025. Code: https://github.com/cluebbers/dpo-rlhf-paraphrase-types.
Models:
https://huggingface.co/collections/cluebbers/enhancing-paraphrase-type-generation-673ca8d75dfe2ce962a48ac0 | null | null | null | null | null | null | null | null | null |
2,506.02095 | Cycle Consistency as Reward: Learning Image-Text Alignment without Human
Preferences | ['Hyojin Bahng', 'Caroline Chan', 'Fredo Durand', 'Phillip Isola'] | ['cs.CV', 'cs.LG'] | Learning alignment between language and vision is a fundamental challenge,
especially as multimodal data becomes increasingly detailed and complex.
Existing methods often rely on collecting human or AI preferences, which can be
costly and time-intensive. We propose an alternative approach that leverages
cycle consisten... | 2025-06-02T17:42:58Z | null | null | null | null | null | null | null | null | null | null |
2,506.02096 | SynthRL: Scaling Visual Reasoning with Verifiable Data Synthesis | ['Zijian Wu', 'Jinjie Ni', 'Xiangyan Liu', 'Zichen Liu', 'Hang Yan', 'Michael Qizhe Shieh'] | ['cs.LG', 'cs.CL', 'cs.CV'] | Vision-language models (VLMs) trained via reinforcement learning with
verifiable reward (RLVR) have shown notable progress in scaling test-time
compute effectively. In this work, we investigate how synthesized RL data can
further improve RLVR. To this end, we propose \textbf{SynthRL}-a scalable and
guaranteed pipeline ... | 2025-06-02T17:45:16Z | null | null | null | null | null | null | null | null | null | null |
2,506.02178 | Cocktail-Party Audio-Visual Speech Recognition | ['Thai-Binh Nguyen', 'Ngoc-Quan Pham', 'Alexander Waibel'] | ['cs.SD', 'cs.CL'] | Audio-Visual Speech Recognition (AVSR) offers a robust solution for speech
recognition in challenging environments, such as cocktail-party scenarios,
where relying solely on audio proves insufficient. However, current AVSR models
are often optimized for idealized scenarios with consistently active speakers,
overlooking... | 2025-06-02T19:07:51Z | Accepted at Interspeech 2025 | null | null | null | null | null | null | null | null | null |
2,506.02295 | QARI-OCR: High-Fidelity Arabic Text Recognition through Multimodal Large
Language Model Adaptation | ['Ahmed Wasfy', 'Omer Nacar', 'Abdelakreem Elkhateb', 'Mahmoud Reda', 'Omar Elshehy', 'Adel Ammar', 'Wadii Boulila'] | ['cs.CV', 'cs.AI'] | The inherent complexities of Arabic script; its cursive nature, diacritical
marks (tashkeel), and varied typography, pose persistent challenges for Optical
Character Recognition (OCR). We present Qari-OCR, a series of vision-language
models derived from Qwen2-VL-2B-Instruct, progressively optimized for Arabic
through i... | 2025-06-02T22:21:06Z | null | null | null | null | null | null | null | null | null | null |
2,506.02459 | ReSpace: Text-Driven 3D Scene Synthesis and Editing with Preference
Alignment | ['Martin JJ. Bucher', 'Iro Armeni'] | ['cs.CV', 'I.2.10; I.2.7'] | Scene synthesis and editing has emerged as a promising direction in computer
graphics. Current trained approaches for 3D indoor scenes either oversimplify
object semantics through one-hot class encodings (e.g., 'chair' or 'table'),
require masked diffusion for editing, ignore room boundaries, or rely on floor
plan rend... | 2025-06-03T05:22:04Z | 20 pages, 17 figures (incl. appendix) | null | null | null | null | null | null | null | null | null |
2,506.02587 | BEVCALIB: LiDAR-Camera Calibration via Geometry-Guided Bird's-Eye View
Representations | ['Weiduo Yuan', 'Jerry Li', 'Justin Yue', 'Divyank Shah', 'Konstantinos Karydis', 'Hang Qiu'] | ['cs.CV', 'cs.RO'] | Accurate LiDAR-camera calibration is fundamental to fusing multi-modal
perception in autonomous driving and robotic systems. Traditional calibration
methods require extensive data collection in controlled environments and cannot
compensate for the transformation changes during the vehicle/robot movement. In
this paper,... | 2025-06-03T08:07:18Z | null | null | null | null | null | null | null | null | null | null |
2,506.02751 | RobustSplat: Decoupling Densification and Dynamics for Transient-Free
3DGS | ['Chuanyu Fu', 'Yuqi Zhang', 'Kunbin Yao', 'Guanying Chen', 'Yuan Xiong', 'Chuan Huang', 'Shuguang Cui', 'Xiaochun Cao'] | ['cs.CV'] | 3D Gaussian Splatting (3DGS) has gained significant attention for its
real-time, photo-realistic rendering in novel-view synthesis and 3D modeling.
However, existing methods struggle with accurately modeling scenes affected by
transient objects, leading to artifacts in the rendered images. We identify
that the Gaussian... | 2025-06-03T11:13:48Z | ICCV 2025. Project page: https://fcyycf.github.io/RobustSplat/ | null | null | RobustSplat: Decoupling Densification and Dynamics for Transient-Free 3DGS | ['Chuanyu Fu', 'Yuqi Zhang', 'Kunbin Yao', 'Guanying Chen', 'Yuan Xiong', 'Chuan Huang', 'Shuguang Cui', 'Xiaochun Cao'] | 2,025 | arXiv.org | 0 | 63 | ['Computer Science'] |
2,506.02845 | Go Beyond Earth: Understanding Human Actions and Scenes in Microgravity
Environments | ['Di Wen', 'Lei Qi', 'Kunyu Peng', 'Kailun Yang', 'Fei Teng', 'Ao Luo', 'Jia Fu', 'Yufan Chen', 'Ruiping Liu', 'Yitian Shi', 'M. Saquib Sarfraz', 'Rainer Stiefelhagen'] | ['cs.CV'] | Despite substantial progress in video understanding, most existing datasets
are limited to Earth's gravitational conditions. However, microgravity alters
human motion, interactions, and visual semantics, revealing a critical gap for
real-world vision systems. This presents a challenge for domain-robust video
understand... | 2025-06-03T13:15:19Z | 15 pages, 3 figures, code are available at
https://github.com/LEI-QI-233/HAR-in-Space | null | null | null | null | null | null | null | null | null |
2,506.02863 | CapSpeech: Enabling Downstream Applications in Style-Captioned
Text-to-Speech | ['Helin Wang', 'Jiarui Hai', 'Dading Chong', 'Karan Thakkar', 'Tiantian Feng', 'Dongchao Yang', 'Junhyeok Lee', 'Laureano Moro Velazquez', 'Jesus Villalba', 'Zengyi Qin', 'Shrikanth Narayanan', 'Mounya Elhiali', 'Najim Dehak'] | ['eess.AS', 'cs.AI', 'cs.SD'] | Recent advancements in generative artificial intelligence have significantly
transformed the field of style-captioned text-to-speech synthesis (CapTTS).
However, adapting CapTTS to real-world applications remains challenging due to
the lack of standardized, comprehensive datasets and limited research on
downstream task... | 2025-06-03T13:28:55Z | null | null | null | null | null | null | null | null | null | null |
2,506.02865 | Surfer-H Meets Holo1: Cost-Efficient Web Agent Powered by Open Weights | ['Mathieu Andreux', 'Breno Baldas Skuk', 'Hamza Benchekroun', 'Emilien Biré', 'Antoine Bonnet', 'Riaz Bordie', 'Nathan Bout', 'Matthias Brunel', 'Pierre-Louis Cedoz', 'Antoine Chassang', 'Mickaël Chen', 'Alexandra D. Constantinou', "Antoine d'Andigné", 'Hubert de La Jonquière', 'Aurélien Delfosse', 'Ludovic Denoyer', '... | ['cs.AI'] | We present Surfer-H, a cost-efficient web agent that integrates
Vision-Language Models (VLM) to perform user-defined tasks on the web. We pair
it with Holo1, a new open-weight collection of VLMs specialized in web
navigation and information extraction. Holo1 was trained on carefully curated
data sources, including open... | 2025-06-03T13:29:03Z | Alphabetical order | null | null | null | null | null | null | null | null | null |
2,506.02911 | Cell-o1: Training LLMs to Solve Single-Cell Reasoning Puzzles with
Reinforcement Learning | ['Yin Fang', 'Qiao Jin', 'Guangzhi Xiong', 'Bowen Jin', 'Xianrui Zhong', 'Siru Ouyang', 'Aidong Zhang', 'Jiawei Han', 'Zhiyong Lu'] | ['cs.CL', 'cs.AI', 'cs.CE', 'cs.HC', 'cs.LG'] | Cell type annotation is a key task in analyzing the heterogeneity of
single-cell RNA sequencing data. Although recent foundation models automate
this process, they typically annotate cells independently, without considering
batch-level cellular context or providing explanatory reasoning. In contrast,
human experts ofte... | 2025-06-03T14:16:53Z | 28 pages; 16 tables; 7 figures; Code:
https://github.com/ncbi-nlp/cell-o1 | null | null | null | null | null | null | null | null | null |
2,506.02979 | Towards a Japanese Full-duplex Spoken Dialogue System | ['Atsumoto Ohashi', 'Shinya Iizuka', 'Jingjing Jiang', 'Ryuichiro Higashinaka'] | ['cs.CL', 'eess.AS'] | Full-duplex spoken dialogue systems, which can model simultaneous
bidirectional features of human conversations such as speech overlaps and
backchannels, have attracted significant attention recently. However, the study
of full-duplex spoken dialogue systems for the Japanese language has been
limited, and the research ... | 2025-06-03T15:16:50Z | Accepted to Interspeech 2025 | null | null | null | null | null | null | null | null | null |
2,506.03096 | FuseLIP: Multimodal Embeddings via Early Fusion of Discrete Tokens | ['Christian Schlarmann', 'Francesco Croce', 'Nicolas Flammarion', 'Matthias Hein'] | ['cs.CV', 'cs.LG'] | Contrastive language-image pre-training aligns the features of text-image
pairs in a common latent space via distinct encoders for each modality. While
this approach achieves impressive performance in several zero-shot tasks, it
cannot natively handle multimodal inputs, i.e., encoding image and text into a
single featu... | 2025-06-03T17:27:12Z | Code and models available at https://github.com/chs20/fuselip | null | null | null | null | null | null | null | null | null |
2,506.03107 | ByteMorph: Benchmarking Instruction-Guided Image Editing with Non-Rigid
Motions | ['Di Chang', 'Mingdeng Cao', 'Yichun Shi', 'Bo Liu', 'Shengqu Cai', 'Shijie Zhou', 'Weilin Huang', 'Gordon Wetzstein', 'Mohammad Soleymani', 'Peng Wang'] | ['cs.CV'] | Editing images with instructions to reflect non-rigid motions, camera
viewpoint shifts, object deformations, human articulations, and complex
interactions, poses a challenging yet underexplored problem in computer vision.
Existing approaches and datasets predominantly focus on static scenes or rigid
transformations, li... | 2025-06-03T17:39:47Z | Website: https://boese0601.github.io/bytemorph Dataset:
https://huggingface.co/datasets/ByteDance-Seed/BM-6M Benchmark:
https://huggingface.co/datasets/ByteDance-Seed/BM-Bench Code:
https://github.com/ByteDance-Seed/BM-code Demo:
https://huggingface.co/spaces/Boese0601/ByteMorph-Demo | null | null | ByteMorph: Benchmarking Instruction-Guided Image Editing with Non-Rigid Motions | ['Di Chang', 'Mingdeng Cao', 'Yichun Shi', 'Bo Liu', 'Shengqu Cai', 'Shijie Zhou', 'Weilin Huang', 'Gordon Wetzstein', 'Mohammad Soleymani', 'Peng Wang'] | 2,025 | arXiv.org | 0 | 65 | ['Computer Science'] |
2,506.03123 | DCM: Dual-Expert Consistency Model for Efficient and High-Quality Video
Generation | ['Zhengyao Lv', 'Chenyang Si', 'Tianlin Pan', 'Zhaoxi Chen', 'Kwan-Yee K. Wong', 'Yu Qiao', 'Ziwei Liu'] | ['cs.CV'] | Diffusion Models have achieved remarkable results in video synthesis but
require iterative denoising steps, leading to substantial computational
overhead. Consistency Models have made significant progress in accelerating
diffusion models. However, directly applying them to video diffusion models
often results in severe... | 2025-06-03T17:55:04Z | null | null | null | null | null | null | null | null | null | null |
2,506.03126 | AnimeShooter: A Multi-Shot Animation Dataset for Reference-Guided Video
Generation | ['Lu Qiu', 'Yizhuo Li', 'Yuying Ge', 'Yixiao Ge', 'Ying Shan', 'Xihui Liu'] | ['cs.CV'] | Recent advances in AI-generated content (AIGC) have significantly accelerated
animation production. To produce engaging animations, it is essential to
generate coherent multi-shot video clips with narrative scripts and character
references. However, existing public datasets primarily focus on real-world
scenarios with ... | 2025-06-03T17:55:18Z | Project released at: https://qiulu66.github.io/animeshooter/ | null | null | null | null | null | null | null | null | null |
2,506.03131 | Native-Resolution Image Synthesis | ['Zidong Wang', 'Lei Bai', 'Xiangyu Yue', 'Wanli Ouyang', 'Yiyuan Zhang'] | ['cs.CV', 'cs.LG'] | We introduce native-resolution image synthesis, a novel generative modeling
paradigm that enables the synthesis of images at arbitrary resolutions and
aspect ratios. This approach overcomes the limitations of conventional
fixed-resolution, square-image methods by natively handling variable-length
visual tokens, a core ... | 2025-06-03T17:57:33Z | Project Page: https://wzdthu.github.io/NiT/ | null | null | Native-Resolution Image Synthesis | ['Zidong Wang', 'Lei Bai', 'Xiangyu Yue', 'Wanli Ouyang', 'Yiyuan Zhang'] | 2,025 | arXiv.org | 0 | 84 | ['Computer Science'] |
2,506.03135 | OmniSpatial: Towards Comprehensive Spatial Reasoning Benchmark for
Vision Language Models | ['Mengdi Jia', 'Zekun Qi', 'Shaochen Zhang', 'Wenyao Zhang', 'Xinqiang Yu', 'Jiawei He', 'He Wang', 'Li Yi'] | ['cs.CV', 'cs.AI', 'cs.CL'] | Spatial reasoning is a key aspect of cognitive psychology and remains a major
bottleneck for current vision-language models (VLMs). While extensive research
has aimed to evaluate or improve VLMs' understanding of basic spatial
relations, such as distinguishing left from right, near from far, and object
counting, these ... | 2025-06-03T17:58:29Z | Project Page: https://qizekun.github.io/omnispatial/ | null | null | OmniSpatial: Towards Comprehensive Spatial Reasoning Benchmark for Vision Language Models | ['Mengdi Jia', 'Zekun Qi', 'Shaochen Zhang', 'Wenyao Zhang', 'Xinqiang Yu', 'Jiawei He', 'He Wang', 'Li Yi'] | 2,025 | arXiv.org | 0 | 122 | ['Computer Science'] |
2,506.03136 | Co-Evolving LLM Coder and Unit Tester via Reinforcement Learning | ['Yinjie Wang', 'Ling Yang', 'Ye Tian', 'Ke Shen', 'Mengdi Wang'] | ['cs.CL'] | We propose CURE, a novel reinforcement learning framework with a dedicated
reward design that co-evolves coding and unit test generation capabilities
based on their interaction outcomes, without any ground-truth code as
supervision. This approach enables flexible and scalable training and allows
the unit tester to lear... | 2025-06-03T17:58:42Z | Project: https://github.com/Gen-Verse/CURE | null | null | null | null | null | null | null | null | null |
2,506.03143 | GUI-Actor: Coordinate-Free Visual Grounding for GUI Agents | ['Qianhui Wu', 'Kanzhi Cheng', 'Rui Yang', 'Chaoyun Zhang', 'Jianwei Yang', 'Huiqiang Jiang', 'Jian Mu', 'Baolin Peng', 'Bo Qiao', 'Reuben Tan', 'Si Qin', 'Lars Liden', 'Qingwei Lin', 'Huan Zhang', 'Tong Zhang', 'Jianbing Zhang', 'Dongmei Zhang', 'Jianfeng Gao'] | ['cs.CL', 'cs.AI', 'cs.CV'] | One of the principal challenges in building VLM-powered GUI agents is visual
grounding, i.e., localizing the appropriate screen region for action execution
based on both the visual content and the textual plans. Most existing work
formulates this as a text-based coordinate generation task. However, these
approaches suf... | 2025-06-03T17:59:08Z | null | null | null | null | null | null | null | null | null | null |
2,506.03147 | UniWorld-V1: High-Resolution Semantic Encoders for Unified Visual
Understanding and Generation | ['Bin Lin', 'Zongjian Li', 'Xinhua Cheng', 'Yuwei Niu', 'Yang Ye', 'Xianyi He', 'Shenghai Yuan', 'Wangbo Yu', 'Shaodong Wang', 'Yunyang Ge', 'Yatian Pang', 'Li Yuan'] | ['cs.CV', 'cs.AI', 'cs.CL'] | Although existing unified models achieve strong performance in
vision-language understanding and text-to-image generation, they remain limited
in addressing image perception and manipulation -- capabilities increasingly
demanded in practical applications. Recently, OpenAI introduced the powerful
GPT-4o-Image model, whi... | 2025-06-03T17:59:33Z | null | null | null | null | null | null | null | null | null | null |
2,506.03238 | Rethinking Whole-Body CT Image Interpretation: An Abnormality-Centric
Approach | ['Ziheng Zhao', 'Lisong Dai', 'Ya Zhang', 'Yanfeng Wang', 'Weidi Xie'] | ['eess.IV', 'cs.AI', 'cs.CV'] | Automated interpretation of CT images-particularly localizing and describing
abnormal findings across multi-plane and whole-body scans-remains a significant
challenge in clinical radiology. This work aims to address this challenge
through four key contributions: (i) On taxonomy, we collaborate with senior
radiologists ... | 2025-06-03T17:57:34Z | null | null | null | null | null | null | null | null | null | null |
2,506.03295 | Unleashing the Reasoning Potential of Pre-trained LLMs by Critique
Fine-Tuning on One Problem | ['Yubo Wang', 'Ping Nie', 'Kai Zou', 'Lijun Wu', 'Wenhu Chen'] | ['cs.CL', 'cs.LG'] | We have witnessed that strong LLMs like Qwen-Math, MiMo, and Phi-4 possess
immense reasoning potential inherited from the pre-training stage. With
reinforcement learning (RL), these models can improve dramatically on reasoning
tasks. Recent studies have shown that even RL on a single problem can unleash
these models' r... | 2025-06-03T18:35:52Z | null | null | null | Unleashing the Reasoning Potential of Pre-trained LLMs by Critique Fine-Tuning on One Problem | ['Yubo Wang', 'Ping Nie', 'Kai Zou', 'Lijun Wu', 'Wenhu Chen'] | 2,025 | arXiv.org | 0 | 21 | ['Computer Science'] |
2,506.03355 | Robustness in Both Domains: CLIP Needs a Robust Text Encoder | ['Elias Abad Rocamora', 'Christian Schlarmann', 'Naman Deep Singh', 'Yongtao Wu', 'Matthias Hein', 'Volkan Cevher'] | ['cs.LG', 'cs.AI', 'cs.CV'] | Adversarial input attacks can cause a significant shift of CLIP embeddings.
This can affect the downstream robustness of models incorporating CLIP in the
pipeline, such as text-to-image generative models or large vision language
models. While some efforts have been done towards making the CLIP image
encoders robust, th... | 2025-06-03T19:57:09Z | null | null | null | null | null | null | null | null | null | null |
2,506.03487 | ProRank: Prompt Warmup via Reinforcement Learning for Small Language
Models Reranking | ['Xianming Li', 'Aamir Shakir', 'Rui Huang', 'Julius Lipp', 'Jing Li'] | ['cs.IR', 'cs.CL'] | Reranking is fundamental to information retrieval and retrieval-augmented
generation, with recent Large Language Models (LLMs) significantly advancing
reranking quality. While recent advances with LLMs have significantly improved
document reranking quality, current approaches primarily rely on large-scale
LLMs (>7B par... | 2025-06-04T02:00:44Z | null | null | null | null | null | null | null | null | null | null |
2,506.03524 | Seed-Coder: Let the Code Model Curate Data for Itself | ['ByteDance Seed', 'Yuyu Zhang', 'Jing Su', 'Yifan Sun', 'Chenguang Xi', 'Xia Xiao', 'Shen Zheng', 'Anxiang Zhang', 'Kaibo Liu', 'Daoguang Zan', 'Tao Sun', 'Jinhua Zhu', 'Shulin Xin', 'Dong Huang', 'Yetao Bai', 'Lixin Dong', 'Chao Li', 'Jianchong Chen', 'Hanzhi Zhou', 'Yifan Huang', 'Guanghan Ning', 'Xierui Song', 'Jia... | ['cs.CL', 'cs.SE'] | Code data in large language model (LLM) pretraining is recognized crucial not
only for code-related tasks but also for enhancing general intelligence of
LLMs. Current open-source LLMs often heavily rely on human effort to produce
their code pretraining data, such as employing hand-crafted filtering rules
tailored to in... | 2025-06-04T03:17:19Z | null | null | null | Seed-Coder: Let the Code Model Curate Data for Itself | ['ByteDance Seed', 'Yuyu Zhang', 'Jing Su', 'Yifan Sun', 'Chenguang Xi', 'Xia Xiao', 'Shen Zheng', 'Anxiang Zhang', 'Kaibo Liu', 'Daoguang Zan', 'Tao Sun', 'Jinhua Zhu', 'Shulin Xin', 'Dong Huang', 'Yetao Bai', 'Lixin Dong', 'Chao Li', 'Jianchong Chen', 'Hanzhi Zhou', 'Yifan Huang', 'Guanghan Ning', 'Xierui Song', 'Jia... | 2,025 | arXiv.org | 2 | 57 | ['Computer Science'] |
2,506.03533 | Go-Browse: Training Web Agents with Structured Exploration | ['Apurva Gandhi', 'Graham Neubig'] | ['cs.CL'] | One of the fundamental problems in digital agents is their lack of
understanding of their environment. For instance, a web browsing agent may get
lost in unfamiliar websites, uncertain what pages must be visited to achieve
its goals. To address this, we propose Go-Browse, a method for automatically
collecting diverse a... | 2025-06-04T03:27:56Z | null | null | null | null | null | null | null | null | null | null |
2,506.03569 | MiMo-VL Technical Report | ['Xiaomi LLM-Core Team', ':', 'Zihao Yue', 'Zhenru Lin', 'Yifan Song', 'Weikun Wang', 'Shuhuai Ren', 'Shuhao Gu', 'Shicheng Li', 'Peidian Li', 'Liang Zhao', 'Lei Li', 'Kainan Bao', 'Hao Tian', 'Hailin Zhang', 'Gang Wang', 'Dawei Zhu', 'Cici', 'Chenhong He', 'Bowen Ye', 'Bowen Shen', 'Zihan Zhang', 'Zihan Jiang', 'Zhixi... | ['cs.CL'] | We open-source MiMo-VL-7B-SFT and MiMo-VL-7B-RL, two powerful vision-language
models delivering state-of-the-art performance in both general visual
understanding and multimodal reasoning. MiMo-VL-7B-RL outperforms Qwen2.5-VL-7B
on 35 out of 40 evaluated tasks, and scores 59.4 on OlympiadBench, surpassing
models with up... | 2025-06-04T04:32:54Z | 32 pages | null | null | MiMo-VL Technical Report | ['Xiaomi LLM-Core Team Zihao Yue', 'Zhenrui Lin', 'Yi-Hao Song', 'Weikun Wang', 'Shu-Qin Ren', 'Shuhao Gu', 'Shi-Guang Li', 'Peidian Li', 'Liang Zhao', 'Lei Li', 'Kainan Bao', 'Hao Tian', 'Hailin Zhang', 'Gang Wang', 'Dawei Zhu', 'Cici', 'Chenhong He', 'Bowen Ye', 'Bowen Shen', 'Zihan Zhang', 'Zi-Ang Jiang', 'Zhixian Z... | 2,025 | arXiv.org | 0 | 74 | ['Computer Science'] |
2,506.03637 | RewardAnything: Generalizable Principle-Following Reward Models | ['Zhuohao Yu', 'Jiali Zeng', 'Weizheng Gu', 'Yidong Wang', 'Jindong Wang', 'Fandong Meng', 'Jie Zhou', 'Yue Zhang', 'Shikun Zhang', 'Wei Ye'] | ['cs.CL', 'cs.AI', 'cs.LG'] | Reward Models, essential for guiding Large Language Model optimization, are
typically trained on fixed preference datasets, resulting in rigid alignment to
single, implicit preference distributions. This prevents adaptation to diverse
real-world needs-from conciseness in one task to detailed explanations in
another. Th... | 2025-06-04T07:30:16Z | 25 pages, 9 figures, Code & model weights available at:
https://zhuohaoyu.github.io/RewardAnything | null | null | RewardAnything: Generalizable Principle-Following Reward Models | ['Zhuohao Yu', 'Jiali Zeng', 'Weizheng Gu', 'Yidong Wang', 'Jindong Wang', 'Fandong Meng', 'Jie Zhou', 'Yue Zhang', 'Shikun Zhang', 'Wei Ye'] | 2,025 | arXiv.org | 1 | 97 | ['Computer Science'] |
2,506.0369 | Robust Preference Optimization via Dynamic Target Margins | ['Jie Sun', 'Junkang Wu', 'Jiancan Wu', 'Zhibo Zhu', 'Xingyu Lu', 'Jun Zhou', 'Lintao Ma', 'Xiang Wang'] | ['cs.CL'] | The alignment of Large Language Models (LLMs) is crucial for ensuring their
safety and reliability in practical applications. Direct Preference
Optimization (DPO) has emerged as an efficient method that directly optimizes
models using preference pairs, significantly reducing resource demands.
However, the effectiveness... | 2025-06-04T08:19:37Z | 18 pages, 6 figures, accepted to The 63rd Annual Meeting of the
Association for Computational Linguistics (ACL2025) | null | null | Robust Preference Optimization via Dynamic Target Margins | ['Jie Sun', 'Junkang Wu', 'Jiancan Wu', 'Zhibo Zhu', 'Xingyu Lu', 'Jun Zhou', 'Lintao Ma', 'Xiang Wang'] | 2,025 | arXiv.org | 0 | 51 | ['Computer Science'] |
2,506.03793 | Mark My Words: A Robust Multilingual Model for Punctuation in Text and
Speech Transcripts | ['Sidharth Pulipaka', 'Sparsh Jain', 'Ashwin Sankar', 'Raj Dabre'] | ['cs.CL'] | Punctuation plays a vital role in structuring meaning, yet current models
often struggle to restore it accurately in transcripts of spontaneous speech,
especially in the presence of disfluencies such as false starts and
backtracking. These limitations hinder the performance of downstream tasks like
translation, text to... | 2025-06-04T09:54:38Z | Work in Progress | null | null | null | null | null | null | null | null | null |
2,506.0393 | VisCoder: Fine-Tuning LLMs for Executable Python Visualization Code
Generation | ['Yuansheng Ni', 'Ping Nie', 'Kai Zou', 'Xiang Yue', 'Wenhu Chen'] | ['cs.SE', 'cs.AI', 'cs.CL'] | Large language models (LLMs) often struggle with visualization tasks like
plotting diagrams, charts, where success depends on both code correctness and
visual semantics. Existing instruction-tuning datasets lack execution-grounded
supervision and offer limited support for iterative code correction, resulting
in fragile... | 2025-06-04T13:24:44Z | null | null | null | null | null | null | null | null | null | null |
2,506.03968 | From Real to Synthetic: Synthesizing Millions of Diversified and
Complicated User Instructions with Attributed Grounding | ['Chiwei Zhu', 'Benfeng Xu', 'Xiaorui Wang', 'Zhendong Mao'] | ['cs.CL'] | The pursuit of diverse, complex, and large-scale instruction data is crucial
for automatically aligning large language models (LLMs). While there are
methods capable of generating synthetic instructions at scale, they either
suffer from limited grounding sources, leading to a narrow distribution, or
rely on trivial ext... | 2025-06-04T14:00:47Z | To be published at ACL 2025 | null | null | From Real to Synthetic: Synthesizing Millions of Diversified and Complicated User Instructions with Attributed Grounding | ['Chiwei Zhu', 'Benfeng Xu', 'Xiaorui Wang', 'Zhendong Mao'] | 2,025 | arXiv.org | 0 | 30 | ['Computer Science'] |
2,506.04034 | Rex-Thinker: Grounded Object Referring via Chain-of-Thought Reasoning | ['Qing Jiang', 'Xingyu Chen', 'Zhaoyang Zeng', 'Junzhi Yu', 'Lei Zhang'] | ['cs.CV'] | Object referring aims to detect all objects in an image that match a given
natural language description. We argue that a robust object referring model
should be grounded, meaning its predictions should be both explainable and
faithful to the visual content. Specifically, it should satisfy two key
properties: 1) Verifia... | 2025-06-04T14:56:57Z | homepage: https://rexthinker.github.io/ | null | null | null | null | null | null | null | null | null |
2,506.04158 | Image Editing As Programs with Diffusion Models | ['Yujia Hu', 'Songhua Liu', 'Zhenxiong Tan', 'Xingyi Yang', 'Xinchao Wang'] | ['cs.CV'] | While diffusion models have achieved remarkable success in text-to-image
generation, they encounter significant challenges with instruction-driven image
editing. Our research highlights a key challenge: these models particularly
struggle with structurally inconsistent edits that involve substantial layout
changes. To m... | 2025-06-04T16:57:24Z | null | null | null | Image Editing As Programs with Diffusion Models | ['Yujia Hu', 'Songhua Liu', 'Zhenxiong Tan', 'Xingyi Yang', 'Xinchao Wang'] | 2,025 | arXiv.org | 0 | 75 | ['Computer Science'] |
2,506.04178 | OpenThoughts: Data Recipes for Reasoning Models | ['Etash Guha', 'Ryan Marten', 'Sedrick Keh', 'Negin Raoof', 'Georgios Smyrnis', 'Hritik Bansal', 'Marianna Nezhurina', 'Jean Mercat', 'Trung Vu', 'Zayne Sprague', 'Ashima Suvarna', 'Benjamin Feuer', 'Liangyu Chen', 'Zaid Khan', 'Eric Frankel', 'Sachin Grover', 'Caroline Choi', 'Niklas Muennighoff', 'Shiye Su', 'Wanjia ... | ['cs.LG'] | Reasoning models have made rapid progress on many benchmarks involving math,
code, and science. Yet, there are still many open questions about the best
training recipes for reasoning since state-of-the-art models often rely on
proprietary datasets with little to no public information available. To address
this, the goa... | 2025-06-04T17:25:39Z | https://www.openthoughts.ai/blog/ot3. arXiv admin note: text overlap
with arXiv:2505.23754 by other authors | null | null | null | null | null | null | null | null | null |
2,506.04207 | Advancing Multimodal Reasoning: From Optimized Cold Start to Staged
Reinforcement Learning | ['Shuang Chen', 'Yue Guo', 'Zhaochen Su', 'Yafu Li', 'Yulun Wu', 'Jiacheng Chen', 'Jiayu Chen', 'Weijie Wang', 'Xiaoye Qu', 'Yu Cheng'] | ['cs.LG', 'cs.AI', 'cs.CL', 'cs.CV'] | Inspired by the remarkable reasoning capabilities of Deepseek-R1 in complex
textual tasks, many works attempt to incentivize similar capabilities in
Multimodal Large Language Models (MLLMs) by directly applying reinforcement
learning (RL). However, they still struggle to activate complex reasoning. In
this paper, rathe... | 2025-06-04T17:51:08Z | 19 pages, 6 figures | null | null | Advancing Multimodal Reasoning: From Optimized Cold Start to Staged Reinforcement Learning | ['Shuang Chen', 'Yue Guo', 'Zhao-yu Su', 'Yafu Li', 'Yulun Wu', 'Jiacheng Chen', 'Jiayu Chen', 'Weijie Wang', 'Xiaoye Qu', 'Yu Cheng'] | 2,025 | arXiv.org | 0 | 78 | ['Computer Science'] |
2,506.04217 | OWMM-Agent: Open World Mobile Manipulation With Multi-modal Agentic Data
Synthesis | ['Junting Chen', 'Haotian Liang', 'Lingxiao Du', 'Weiyun Wang', 'Mengkang Hu', 'Yao Mu', 'Wenhai Wang', 'Jifeng Dai', 'Ping Luo', 'Wenqi Shao', 'Lin Shao'] | ['cs.RO', 'cs.AI', 'I.2.4; I.2.9; I.2.10'] | The rapid progress of navigation, manipulation, and vision models has made
mobile manipulators capable in many specialized tasks. However, the open-world
mobile manipulation (OWMM) task remains a challenge due to the need for
generalization to open-ended instructions and environments, as well as the
systematic complexi... | 2025-06-04T17:57:44Z | 9 pages of main content, 19 pages in total | null | null | null | null | null | null | null | null | null |
2,506.04308 | RoboRefer: Towards Spatial Referring with Reasoning in Vision-Language
Models for Robotics | ['Enshen Zhou', 'Jingkun An', 'Cheng Chi', 'Yi Han', 'Shanyu Rong', 'Chi Zhang', 'Pengwei Wang', 'Zhongyuan Wang', 'Tiejun Huang', 'Lu Sheng', 'Shanghang Zhang'] | ['cs.RO', 'cs.AI', 'cs.CV'] | Spatial referring is a fundamental capability of embodied robots to interact
with the 3D physical world. However, even with the powerful pretrained vision
language models (VLMs), recent approaches are still not qualified to accurately
understand the complex 3D scenes and dynamically reason about the
instruction-indicat... | 2025-06-04T17:59:27Z | Project page: https://zhoues.github.io/RoboRefer/ | null | null | null | null | null | null | null | null | null |
2,506.04421 | HMAR: Efficient Hierarchical Masked Auto-Regressive Image Generation | ['Hermann Kumbong', 'Xian Liu', 'Tsung-Yi Lin', 'Ming-Yu Liu', 'Xihui Liu', 'Ziwei Liu', 'Daniel Y. Fu', 'Christopher Ré', 'David W. Romero'] | ['cs.CV', 'cs.AI', 'cs.LG'] | Visual Auto-Regressive modeling (VAR) has shown promise in bridging the speed
and quality gap between autoregressive image models and diffusion models. VAR
reformulates autoregressive modeling by decomposing an image into successive
resolution scales. During inference, an image is generated by predicting all
the tokens... | 2025-06-04T20:08:07Z | Accepted to CVPR 2025. Project Page:
https://research.nvidia.com/labs/dir/hmar/ | null | null | null | null | null | null | null | null | null |
2,506.04559 | Perceptual Decoupling for Scalable Multi-modal Reasoning via
Reward-Optimized Captioning | ['Yunhao Gou', 'Kai Chen', 'Zhili Liu', 'Lanqing Hong', 'Xin Jin', 'Zhenguo Li', 'James T. Kwok', 'Yu Zhang'] | ['cs.CV'] | Recent advances in slow-thinking language models (e.g., OpenAI-o1 and
DeepSeek-R1) have demonstrated remarkable abilities in complex reasoning tasks
by emulating human-like reflective cognition. However, extending such
capabilities to multi-modal large language models (MLLMs) remains challenging
due to the high cost of... | 2025-06-05T02:28:07Z | null | null | null | Perceptual Decoupling for Scalable Multi-modal Reasoning via Reward-Optimized Captioning | ['Yunhao Gou', 'Kai Chen', 'Zhili Liu', 'Lanqing Hong', 'Xin Jin', 'Zhenguo Li', 'James T. Kwok', 'Yu Zhang'] | 2,025 | arXiv.org | 0 | 57 | ['Computer Science'] |
2,506.04598 | Scaling Laws for Robust Comparison of Open Foundation Language-Vision
Models and Datasets | ['Marianna Nezhurina', 'Tomer Porian', 'Giovanni Pucceti', 'Tommie Kerssies', 'Romain Beaumont', 'Mehdi Cherti', 'Jenia Jitsev'] | ['cs.LG', 'cs.AI', 'cs.CV'] | In studies of transferable learning, scaling laws are obtained for various
important foundation models to predict their properties and performance at
larger scales. We show here how scaling law derivation can also be used for
model and dataset comparison, allowing to decide which procedure is to be
preferred for pre-tr... | 2025-06-05T03:35:59Z | Preprint. In Review | null | null | null | null | null | null | null | null | null |
2,506.04879 | Invisible Backdoor Triggers in Image Editing Model via Deep Watermarking | ['Yu-Feng Chen', 'Tzuhsuan Huang', 'Pin-Yen Chiu', 'Jun-Cheng Chen'] | ['cs.CV'] | Diffusion models have achieved remarkable progress in both image generation
and editing. However, recent studies have revealed their vulnerability to
backdoor attacks, in which specific patterns embedded in the input can
manipulate the model's behavior. Most existing research in this area has
proposed attack frameworks... | 2025-06-05T10:51:58Z | null | null | null | null | null | null | null | null | null | null |
2,506.04956 | FEAT: Full-Dimensional Efficient Attention Transformer for Medical Video
Generation | ['Huihan Wang', 'Zhiwen Yang', 'Hui Zhang', 'Dan Zhao', 'Bingzheng Wei', 'Yan Xu'] | ['cs.CV'] | Synthesizing high-quality dynamic medical videos remains a significant
challenge due to the need for modeling both spatial consistency and temporal
dynamics. Existing Transformer-based approaches face critical limitations,
including insufficient channel interactions, high computational complexity from
self-attention, a... | 2025-06-05T12:31:02Z | This paper has been early accepted by MICCAI 2025 | null | null | null | null | null | null | null | null | null |
2,506.05074 | EMBER2024 -- A Benchmark Dataset for Holistic Evaluation of Malware
Classifiers | ['Robert J. Joyce', 'Gideon Miller', 'Phil Roth', 'Richard Zak', 'Elliott Zaresky-Williams', 'Hyrum Anderson', 'Edward Raff', 'James Holt'] | ['cs.CR', 'cs.LG'] | A lack of accessible data has historically restricted malware analysis
research, and practitioners have relied heavily on datasets provided by
industry sources to advance. Existing public datasets are limited by narrow
scope - most include files targeting a single platform, have labels supporting
just one type of malwa... | 2025-06-05T14:20:36Z | null | null | 10.1145/3711896.3737431 | null | null | null | null | null | null | null |
2,506.05127 | PixCell: A generative foundation model for digital histopathology images | ['Srikar Yellapragada', 'Alexandros Graikos', 'Zilinghan Li', 'Kostas Triaridis', 'Varun Belagali', 'Saarthak Kapse', 'Tarak Nath Nandi', 'Ravi K Madduri', 'Prateek Prasanna', 'Tahsin Kurc', 'Rajarsi R. Gupta', 'Joel Saltz', 'Dimitris Samaras'] | ['eess.IV', 'cs.CV', 'q-bio.QM'] | The digitization of histology slides has revolutionized pathology, providing
massive datasets for cancer diagnosis and research. Contrastive self-supervised
and vision-language models have been shown to effectively mine large pathology
datasets to learn discriminative representations. On the other hand, generative
mode... | 2025-06-05T15:14:32Z | null | null | null | null | null | null | null | null | null | null |
2,506.05176 | Qwen3 Embedding: Advancing Text Embedding and Reranking Through
Foundation Models | ['Yanzhao Zhang', 'Mingxin Li', 'Dingkun Long', 'Xin Zhang', 'Huan Lin', 'Baosong Yang', 'Pengjun Xie', 'An Yang', 'Dayiheng Liu', 'Junyang Lin', 'Fei Huang', 'Jingren Zhou'] | ['cs.CL'] | In this work, we introduce the Qwen3 Embedding series, a significant
advancement over its predecessor, the GTE-Qwen series, in text embedding and
reranking capabilities, built upon the Qwen3 foundation models. Leveraging the
Qwen3 LLMs' robust capabilities in multilingual text understanding and
generation, our innovati... | 2025-06-05T15:49:48Z | null | null | null | null | null | null | null | null | null | null |
2,506.05209 | The Common Pile v0.1: An 8TB Dataset of Public Domain and Openly
Licensed Text | ['Nikhil Kandpal', 'Brian Lester', 'Colin Raffel', 'Sebastian Majstorovic', 'Stella Biderman', 'Baber Abbasi', 'Luca Soldaini', 'Enrico Shippole', 'A. Feder Cooper', 'Aviya Skowron', 'John Kirchenbauer', 'Shayne Longpre', 'Lintang Sutawika', 'Alon Albalak', 'Zhenlin Xu', 'Guilherme Penedo', 'Loubna Ben Allal', 'Elie Ba... | ['cs.CL', 'cs.LG'] | Large language models (LLMs) are typically trained on enormous quantities of
unlicensed text, a practice that has led to scrutiny due to possible
intellectual property infringement and ethical concerns. Training LLMs on
openly licensed text presents a first step towards addressing these issues, but
prior data collectio... | 2025-06-05T16:21:30Z | null | null | null | null | null | null | null | null | null | null |
2,506.05218 | MonkeyOCR: Document Parsing with a Structure-Recognition-Relation
Triplet Paradigm | ['Zhang Li', 'Yuliang Liu', 'Qiang Liu', 'Zhiyin Ma', 'Ziyang Zhang', 'Shuo Zhang', 'Zidun Guo', 'Jiarui Zhang', 'Xinyu Wang', 'Xiang Bai'] | ['cs.CV'] | We introduce MonkeyOCR, a vision-language model for document parsing that
advances the state of the art by leveraging a Structure-Recognition-Relation
(SRR) triplet paradigm. This design simplifies what would otherwise be a
complex multi-tool pipeline (as in MinerU's modular approach) and avoids the
inefficiencies of p... | 2025-06-05T16:34:57Z | null | null | null | MonkeyOCR: Document Parsing with a Structure-Recognition-Relation Triplet Paradigm | ['Zhang Li', 'Yuliang Liu', 'Qiang Liu', 'Zhiyin Ma', 'Ziyang Zhang', 'Shuo Zhang', 'Zidun Guo', 'Jiarui Zhang', 'Xinyu Wang', 'Xiang Bai'] | 2,025 | arXiv.org | 0 | 50 | ['Computer Science'] |
2,506.05282 | Rectified Point Flow: Generic Point Cloud Pose Estimation | ['Tao Sun', 'Liyuan Zhu', 'Shengyu Huang', 'Shuran Song', 'Iro Armeni'] | ['cs.CV', 'cs.AI', 'cs.RO'] | We introduce Rectified Point Flow, a unified parameterization that formulates
pairwise point cloud registration and multi-part shape assembly as a single
conditional generative problem. Given unposed point clouds, our method learns a
continuous point-wise velocity field that transports noisy points toward their
target ... | 2025-06-05T17:36:03Z | Project page: https://rectified-pointflow.github.io/ | null | null | Rectified Point Flow: Generic Point Cloud Pose Estimation | ['Tao Sun', 'Liyuan Zhu', 'Shengyu Huang', 'Shuran Song', 'Iro Armeni'] | 2,025 | arXiv.org | 0 | 67 | ['Computer Science'] |
2,506.05301 | SeedVR2: One-Step Video Restoration via Diffusion Adversarial
Post-Training | ['Jianyi Wang', 'Shanchuan Lin', 'Zhijie Lin', 'Yuxi Ren', 'Meng Wei', 'Zongsheng Yue', 'Shangchen Zhou', 'Hao Chen', 'Yang Zhao', 'Ceyuan Yang', 'Xuefeng Xiao', 'Chen Change Loy', 'Lu Jiang'] | ['cs.CV'] | Recent advances in diffusion-based video restoration (VR) demonstrate
significant improvement in visual quality, yet yield a prohibitive
computational cost during inference. While several distillation-based
approaches have exhibited the potential of one-step image restoration,
extending existing approaches to VR remain... | 2025-06-05T17:51:05Z | Draft Ver. Project page: https://iceclear.github.io/projects/seedvr2/ | null | null | SeedVR2: One-Step Video Restoration via Diffusion Adversarial Post-Training | ['Jianyi Wang', 'Shanchuan Lin', 'Zhijie Lin', 'Yuxi Ren', 'Meng Wei', 'Zongsheng Yue', 'Shangchen Zhou', 'Hao Chen', 'Yang Zhao', 'Ceyuan Yang', 'Xuefeng Xiao', 'Chen Change Loy', 'Lu Jiang'] | 2,025 | arXiv.org | 1 | 94 | ['Computer Science'] |
2,506.05302 | Perceive Anything: Recognize, Explain, Caption, and Segment Anything in
Images and Videos | ['Weifeng Lin', 'Xinyu Wei', 'Ruichuan An', 'Tianhe Ren', 'Tingwei Chen', 'Renrui Zhang', 'Ziyu Guo', 'Wentao Zhang', 'Lei Zhang', 'Hongsheng Li'] | ['cs.CV'] | We present Perceive Anything Model (PAM), a conceptually straightforward and
efficient framework for comprehensive region-level visual understanding in
images and videos. Our approach extends the powerful segmentation model SAM 2
by integrating Large Language Models (LLMs), enabling simultaneous object
segmentation wit... | 2025-06-05T17:51:39Z | 19 pages, 13 figures, Website: https://Perceive-Anything.github.io | null | null | Perceive Anything: Recognize, Explain, Caption, and Segment Anything in Images and Videos | ['Weifeng Lin', 'Xinyu Wei', 'Ruichuan An', 'Tianhe Ren', 'Tingwei Chen', 'Renrui Zhang', 'Ziyu Guo', 'Wentao Zhang', 'Lei Zhang', 'Hongsheng Li'] | 2,025 | arXiv.org | 0 | 78 | ['Computer Science'] |
2,506.05328 | AV-Reasoner: Improving and Benchmarking Clue-Grounded Audio-Visual
Counting for MLLMs | ['Lidong Lu', 'Guo Chen', 'Zhiqi Li', 'Yicheng Liu', 'Tong Lu'] | ['cs.CV'] | Despite progress in video understanding, current MLLMs struggle with counting
tasks. Existing benchmarks are limited by short videos, close-set queries, lack
of clue annotations, and weak multimodal coverage. In this paper, we introduce
CG-AV-Counting, a manually-annotated clue-grounded counting benchmark with
1,027 mu... | 2025-06-05T17:58:33Z | 21 pages, 11 figures | null | null | null | null | null | null | null | null | null |
2,506.05336 | VideoMolmo: Spatio-Temporal Grounding Meets Pointing | ['Ghazi Shazan Ahmad', 'Ahmed Heakl', 'Hanan Gani', 'Abdelrahman Shaker', 'Zhiqiang Shen', 'Fahad Shahbaz Khan', 'Salman Khan'] | ['cs.CV'] | Spatio-temporal localization is vital for precise interactions across diverse
domains, from biological research to autonomous navigation and interactive
interfaces. Current video-based approaches, while proficient in tracking, lack
the sophisticated reasoning capabilities of large language models, limiting
their contex... | 2025-06-05T17:59:29Z | 20 pages, 13 figures | null | null | null | null | null | null | null | null | null |
2,506.05343 | ContentV: Efficient Training of Video Generation Models with Limited
Compute | ['Wenfeng Lin', 'Renjie Chen', 'Boyuan Liu', 'Shiyue Yan', 'Ruoyu Feng', 'Jiangchuan Wei', 'Yichen Zhang', 'Yimeng Zhou', 'Chao Feng', 'Jiao Ran', 'Qi Wu', 'Zuotao Liu', 'Mingyu Guo'] | ['cs.CV'] | Recent advances in video generation demand increasingly efficient training
recipes to mitigate escalating computational costs. In this report, we present
ContentV, an 8B-parameter text-to-video model that achieves state-of-the-art
performance (85.14 on VBench) after training on 256 x 64GB Neural Processing
Units (NPUs)... | 2025-06-05T17:59:54Z | Project Page: https://contentv.github.io | null | null | ContentV: Efficient Training of Video Generation Models with Limited Compute | ['Wenfeng Lin', 'Renjie Chen', 'Boyuan Liu', 'Shiyue Yan', 'Ruoyu Feng', 'Jiangchuan Wei', 'Yichen Zhang', 'Yimeng Zhou', 'Chao Feng', 'Jiao Ran', 'Qi Wu', 'Zuotao Liu', 'Mingyu Guo'] | 2,025 | arXiv.org | 0 | 51 | ['Computer Science'] |
2,506.05426 | Mixture-of-Experts Meets In-Context Reinforcement Learning | ['Wenhao Wu', 'Fuhong Liu', 'Haoru Li', 'Zican Hu', 'Daoyi Dong', 'Chunlin Chen', 'Zhi Wang'] | ['cs.LG', 'cs.AI'] | In-context reinforcement learning (ICRL) has emerged as a promising paradigm
for adapting RL agents to downstream tasks through prompt conditioning.
However, two notable challenges remain in fully harnessing in-context learning
within RL domains: the intrinsic multi-modality of the state-action-reward data
and the dive... | 2025-06-05T06:29:14Z | 26 pages, 13 figures | null | null | Mixture-of-Experts Meets In-Context Reinforcement Learning | ['Wenhao Wu', 'Fuhong Liu', 'Haoru Li', 'Zican Hu', 'Daoyi Dong', 'Chunlin Chen', 'Zhi Wang'] | 2,025 | arXiv.org | 0 | 66 | ['Computer Science'] |
2,506.05446 | Sentinel: SOTA model to protect against prompt injections | ['Dror Ivry', 'Oran Nahum'] | ['cs.CR', 'cs.AI'] | Large Language Models (LLMs) are increasingly powerful but remain vulnerable
to prompt injection attacks, where malicious inputs cause the model to deviate
from its intended instructions. This paper introduces Sentinel, a novel
detection model, qualifire/prompt-injection-sentinel, based on the
\answerdotai/ModernBERT-l... | 2025-06-05T14:07:15Z | 6 pages, 2 tables | null | null | Sentinel: SOTA model to protect against prompt injections | ['Dror Ivry', 'Oran Nahum'] | 2,025 | arXiv.org | 0 | 22 | ['Computer Science'] |
2,506.05501 | FocusDiff: Advancing Fine-Grained Text-Image Alignment for
Autoregressive Visual Generation through RL | ['Kaihang Pan', 'Wendong Bu', 'Yuruo Wu', 'Yang Wu', 'Kai Shen', 'Yunfei Li', 'Hang Zhao', 'Juncheng Li', 'Siliang Tang', 'Yueting Zhuang'] | ['cs.CV'] | Recent studies extend the autoregression paradigm to text-to-image
generation, achieving performance comparable to diffusion models. However, our
new PairComp benchmark -- featuring test cases of paired prompts with similar
syntax but different fine-grained semantics -- reveals that existing models
struggle with fine-g... | 2025-06-05T18:36:33Z | 15 pages, 8 figures. Project Page: https://focusdiff.github.io/ | null | null | FocusDiff: Advancing Fine-Grained Text-Image Alignment for Autoregressive Visual Generation through RL | ['Kaihang Pan', 'Wendong Bu', 'Yuruo Wu', 'Yang Wu', 'Kai Shen', 'Yunfei Li', 'Hang Zhao', 'Juncheng Li', 'Siliang Tang', 'Yueting Zhuang'] | 2,025 | arXiv.org | 0 | 38 | ['Computer Science'] |
2,506.05573 | PartCrafter: Structured 3D Mesh Generation via Compositional Latent
Diffusion Transformers | ['Yuchen Lin', 'Chenguo Lin', 'Panwang Pan', 'Honglei Yan', 'Yiqiang Feng', 'Yadong Mu', 'Katerina Fragkiadaki'] | ['cs.CV'] | We introduce PartCrafter, the first structured 3D generative model that
jointly synthesizes multiple semantically meaningful and geometrically distinct
3D meshes from a single RGB image. Unlike existing methods that either produce
monolithic 3D shapes or follow two-stage pipelines, i.e., first segmenting an
image and t... | 2025-06-05T20:30:28Z | Project Page: https://wgsxm.github.io/projects/partcrafter/ | null | null | null | null | null | null | null | null | null |
2,506.05587 | MMTU: A Massive Multi-Task Table Understanding and Reasoning Benchmark | ['Junjie Xing', 'Yeye He', 'Mengyu Zhou', 'Haoyu Dong', 'Shi Han', 'Lingjiao Chen', 'Dongmei Zhang', 'Surajit Chaudhuri', 'H. V. Jagadish'] | ['cs.AI', 'cs.CL', 'cs.DB', 'cs.LG'] | Tables and table-based use cases play a crucial role in many important
real-world applications, such as spreadsheets, databases, and computational
notebooks, which traditionally require expert-level users like data engineers,
data analysts, and database administrators to operate. Although LLMs have shown
remarkable pro... | 2025-06-05T21:05:03Z | null | null | null | MMTU: A Massive Multi-Task Table Understanding and Reasoning Benchmark | ['Junjie Xing', 'Yeye He', 'Mengyu Zhou', 'Haoyu Dong', 'Shi Han', 'Lingjiao Chen', 'Dongmei Zhang', 'Surajit Chaudhuri', 'H. V. Jagadish'] | 2,025 | arXiv.org | 0 | 129 | ['Computer Science'] |
2,506.05673 | Peer-Ranked Precision: Creating a Foundational Dataset for Fine-Tuning
Vision Models from DataSeeds' Annotated Imagery | ['Sajjad Abdoli', 'Freeman Lewin', 'Gediminas Vasiliauskas', 'Fabian Schonholz'] | ['cs.LG', 'cs.AI', 'cs.CV'] | The development of modern Artificial Intelligence (AI) models, particularly
diffusion-based models employed in computer vision and image generation tasks,
is undergoing a paradigmatic shift in development methodologies. Traditionally
dominated by a "Model Centric" approach, in which performance gains were
primarily pur... | 2025-06-06T01:50:28Z | 28 pages, 12 figures | null | null | Peer-Ranked Precision: Creating a Foundational Dataset for Fine-Tuning Vision Models from DataSeeds' Annotated Imagery | ['Sajjad Abdoli', 'Freeman Lewin', 'Gediminas Vasiliauskas', 'Fabian Schonholz'] | 2,025 | arXiv.org | 0 | 14 | ['Computer Science'] |
2,506.057 | RKEFino1: A Regulation Knowledge-Enhanced Large Language Model | ['Yan Wang', 'Yueru He', 'Ruoyu Xiang', 'Jeff Zhao'] | ['cs.CL', 'cs.AI'] | Recent advances in large language models (LLMs) hold great promise for
financial applications but introduce critical accuracy and compliance
challenges in Digital Regulatory Reporting (DRR). To address these issues, we
propose RKEFino1, a regulation knowledge-enhanced financial reasoning model
built upon Fino1, fine-tu... | 2025-06-06T03:02:52Z | null | null | null | null | null | null | null | null | null | null |
2,506.05767 | dots.llm1 Technical Report | ['Bi Huo', 'Bin Tu', 'Cheng Qin', 'Da Zheng', 'Debing Zhang', 'Dongjie Zhang', 'En Li', 'Fu Guo', 'Jian Yao', 'Jie Lou', 'Junfeng Tian', 'Li Hu', 'Ran Zhu', 'Shengdong Chen', 'Shuo Liu', 'Su Guang', 'Te Wo', 'Weijun Zhang', 'Xiaoming Shi', 'Xinxin Peng', 'Xing Wu', 'Yawen Liu', 'Yuqiu Ji', 'Ze Wen', 'Zhenhai Liu', 'Zic... | ['cs.CL', 'cs.AI'] | Mixture of Experts (MoE) models have emerged as a promising paradigm for
scaling language models efficiently by activating only a subset of parameters
for each input token. In this report, we present dots.llm1, a large-scale MoE
model that activates 14B parameters out of a total of 142B parameters,
delivering performan... | 2025-06-06T05:51:29Z | null | null | null | dots.llm1 Technical Report | ['Bi Huo', 'Bin Tu', 'Cheng Qin', 'Da Zheng', 'Debing Zhang', 'Dongjie Zhang', 'En Li', 'Fu Guo', 'Jian Yao', 'Jie Lou', 'Junfeng Tian', 'Li Hu', 'Ran Zhu', 'Shengdong Chen', 'Shuo Liu', 'Su Guang', 'Te Wo', 'Weijun Zhang', 'Xiaoming Shi', 'Xinxin Peng', 'Xing Wu', 'Yawen Liu', 'Yuqiu Ji', 'Ze Wen', 'Zhenhai Liu', 'Zic... | 2,025 | arXiv.org | 0 | 78 | ['Computer Science'] |
2,506.05928 | MoA: Heterogeneous Mixture of Adapters for Parameter-Efficient
Fine-Tuning of Large Language Models | ['Jie Cao', 'Tianwei Lin', 'Hongyang He', 'Rolan Yan', 'Wenqiao Zhang', 'Juncheng Li', 'Dongping Zhang', 'Siliang Tang', 'Yueting Zhuang'] | ['cs.CL', 'cs.AI'] | Recent studies integrate Low-Rank Adaptation (LoRA) and Mixture-of-Experts
(MoE) to further enhance the performance of parameter-efficient fine-tuning
(PEFT) methods in Large Language Model (LLM) applications. Existing methods
employ \emph{homogeneous} MoE-LoRA architectures composed of LoRA experts with
either similar... | 2025-06-06T09:54:19Z | null | null | null | MoA: Heterogeneous Mixture of Adapters for Parameter-Efficient Fine-Tuning of Large Language Models | ['Jie Cao', 'Tianwei Lin', 'Hongyang He', 'Rolan Yan', 'Wenqiao Zhang', 'Juncheng Li', 'Dongping Zhang', 'Siliang Tang', 'Yueting Zhuang'] | 2,025 | arXiv.org | 0 | 39 | ['Computer Science'] |
2,506.06006 | Bootstrapping World Models from Dynamics Models in Multimodal Foundation
Models | ['Yifu Qiu', 'Yftah Ziser', 'Anna Korhonen', 'Shay B. Cohen', 'Edoardo M. Ponti'] | ['cs.CV', 'cs.AI', 'cs.CL'] | To what extent do vision-and-language foundation models possess a realistic
world model (observation $\times$ action $\rightarrow$ observation) and a
dynamics model (observation $\times$ observation $\rightarrow$ action), when
actions are expressed through language? While open-source foundation models
struggle with bot... | 2025-06-06T11:50:18Z | null | null | null | null | null | null | null | null | null | null |
2,506.06144 | CLaMR: Contextualized Late-Interaction for Multimodal Content Retrieval | ['David Wan', 'Han Wang', 'Elias Stengel-Eskin', 'Jaemin Cho', 'Mohit Bansal'] | ['cs.CV', 'cs.CL', 'cs.IR'] | Online video web content is richly multimodal: a single video blends vision,
speech, ambient audio, and on-screen text. Retrieval systems typically treat
these modalities as independent retrieval sources, which can lead to noisy and
subpar retrieval. We explore multimodal video content retrieval, where
relevance can be... | 2025-06-06T15:02:30Z | 18 pages. Code and data: https://github.com/meetdavidwan/clamr | null | null | null | null | null | null | null | null | null |
2,506.0627 | RecGPT: A Foundation Model for Sequential Recommendation | ['Yangqin Jiang', 'Xubin Ren', 'Lianghao Xia', 'Da Luo', 'Kangyi Lin', 'Chao Huang'] | ['cs.IR'] | This work addresses a fundamental barrier in recommender systems: the
inability to generalize across domains without extensive retraining.
Traditional ID-based approaches fail entirely in cold-start and cross-domain
scenarios where new users or items lack sufficient interaction history.
Inspired by foundation models' c... | 2025-06-06T17:53:02Z | null | null | null | null | null | null | null | null | null | null |
2,506.06279 | CoMemo: LVLMs Need Image Context with Image Memory | ['Shi Liu', 'Weijie Su', 'Xizhou Zhu', 'Wenhai Wang', 'Jifeng Dai'] | ['cs.CV'] | Recent advancements in Large Vision-Language Models built upon Large Language
Models have established aligning visual features with LLM representations as
the dominant paradigm. However, inherited LLM architectural designs introduce
suboptimal characteristics for multimodal processing. First, LVLMs exhibit a
bimodal di... | 2025-06-06T17:59:06Z | ICML 2025 | null | null | null | null | null | null | null | null | null |
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