arxiv_id float64 1.5k 2.51k | title stringlengths 9 178 ⌀ | authors stringlengths 2 22.8k | categories stringlengths 4 146 | summary stringlengths 103 1.92k ⌀ | published stringdate 2015-02-06 10:44:00 2025-07-10 17:59:58 ⌀ | comments stringlengths 2 417 ⌀ | journal_ref stringclasses 321
values | doi stringclasses 398
values | ss_title stringlengths 8 159 ⌀ | ss_authors stringlengths 11 8.38k ⌀ | ss_year float64 2.02k 2.03k ⌀ | ss_venue stringclasses 281
values | ss_citationCount float64 0 134k ⌀ | ss_referenceCount float64 0 429 ⌀ | ss_fieldsOfStudy stringclasses 47
values |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2,503.08307 | $^R$FLAV: Rolling Flow matching for infinite Audio Video generation | ['Alex Ergasti', 'Giuseppe Gabriele Tarollo', 'Filippo Botti', 'Tomaso Fontanini', 'Claudio Ferrari', 'Massimo Bertozzi', 'Andrea Prati'] | ['cs.CV'] | Joint audio-video (AV) generation is still a significant challenge in
generative AI, primarily due to three critical requirements: quality of the
generated samples, seamless multimodal synchronization and temporal coherence,
with audio tracks that match the visual data and vice versa, and limitless
video duration. In t... | 2025-03-11T11:18:47Z | null | null | null | null | null | null | null | null | null | null |
2,503.08363 | Parametric Point Cloud Completion for Polygonal Surface Reconstruction | ['Zhaiyu Chen', 'Yuqing Wang', 'Liangliang Nan', 'Xiao Xiang Zhu'] | ['cs.CV'] | Existing polygonal surface reconstruction methods heavily depend on input
completeness and struggle with incomplete point clouds. We argue that while
current point cloud completion techniques may recover missing points, they are
not optimized for polygonal surface reconstruction, where the parametric
representation of ... | 2025-03-11T12:20:24Z | CVPR 2025 | null | null | Parametric Point Cloud Completion for Polygonal Surface Reconstruction | ['Zhaiyu Chen', 'Yuqing Wang', 'Liangliang Nan', 'Xiao Xiang Zhu'] | 2,025 | arXiv.org | 0 | 50 | ['Computer Science'] |
2,503.08373 | nnInteractive: Redefining 3D Promptable Segmentation | ['Fabian Isensee', 'Maximilian Rokuss', 'Lars Krämer', 'Stefan Dinkelacker', 'Ashis Ravindran', 'Florian Stritzke', 'Benjamin Hamm', 'Tassilo Wald', 'Moritz Langenberg', 'Constantin Ulrich', 'Jonathan Deissler', 'Ralf Floca', 'Klaus Maier-Hein'] | ['cs.CV'] | Accurate and efficient 3D segmentation is essential for both clinical and
research applications. While foundation models like SAM have revolutionized
interactive segmentation, their 2D design and domain shift limitations make
them ill-suited for 3D medical images. Current adaptations address some of
these challenges bu... | 2025-03-11T12:30:34Z | Fabian Isensee, Maximilian Rokuss and Lars Kr\"amer contributed
equally. Each co-first author may list themselves as lead author on their CV | null | null | nnInteractive: Redefining 3D Promptable Segmentation | ['Fabian Isensee', 'Maximilian Rokuss', 'Lars Krämer', 'Stefan Dinkelacker', 'Ashis Ravindran', 'Florian Stritzke', 'Benjamin Hamm', 'Tassilo Wald', 'Moritz Langenberg', 'Constantin Ulrich', 'Jonathan Deissler', 'Ralf Floca', 'K. Maier-Hein'] | 2,025 | arXiv.org | 6 | 132 | ['Computer Science'] |
2,503.08505 | CFNet: Optimizing Remote Sensing Change Detection through Content-Aware
Enhancement | ['Fan Wu', 'Sijun Dong', 'Xiaoliang Meng'] | ['cs.CV'] | Change detection is a crucial and widely applied task in remote sensing,
aimed at identifying and analyzing changes occurring in the same geographical
area over time. Due to variability in acquisition conditions, bi-temporal
remote sensing images often exhibit significant differences in image style.
Even with the power... | 2025-03-11T14:56:11Z | 17 pages, 12 figures | null | null | null | null | null | null | null | null | null |
2,503.08507 | Referring to Any Person | ['Qing Jiang', 'Lin Wu', 'Zhaoyang Zeng', 'Tianhe Ren', 'Yuda Xiong', 'Yihao Chen', 'Qin Liu', 'Lei Zhang'] | ['cs.CV'] | Humans are undoubtedly the most important participants in computer vision,
and the ability to detect any individual given a natural language description,
a task we define as referring to any person, holds substantial practical value.
However, we find that existing models generally fail to achieve real-world
usability, ... | 2025-03-11T14:57:14Z | null | null | null | Referring to Any Person | ['Qing Jiang', 'Lin Wu', 'Zhaoyang Zeng', 'Tianhe Ren', 'Yuda Xiong', 'Yihao Chen', 'Qin Liu', 'Lei Zhang'] | 2,025 | arXiv.org | 2 | 86 | ['Computer Science'] |
2,503.0854 | Mellow: a small audio language model for reasoning | ['Soham Deshmukh', 'Satvik Dixit', 'Rita Singh', 'Bhiksha Raj'] | ['cs.SD', 'cs.AI', 'eess.AS'] | Multimodal Audio-Language Models (ALMs) can understand and reason over both
audio and text. Typically, reasoning performance correlates with model size,
with the best results achieved by models exceeding 8 billion parameters.
However, no prior work has explored enabling small audio-language models to
perform reasoning ... | 2025-03-11T15:29:00Z | Checkpoint and dataset available at:
https://github.com/soham97/mellow | null | null | Mellow: a small audio language model for reasoning | ['Soham Deshmukh', 'Satvik Dixit', 'Rita Singh', 'Bhiksha Raj'] | 2,025 | arXiv.org | 4 | 74 | ['Computer Science', 'Engineering'] |
2,503.08561 | ComicsPAP: understanding comic strips by picking the correct panel | ['Emanuele Vivoli', 'Artemis Llabrés', 'Mohamed Ali Souibgui', 'Marco Bertini', 'Ernest Valveny Llobet', 'Dimosthenis Karatzas'] | ['cs.CV'] | Large multimodal models (LMMs) have made impressive strides in image
captioning, VQA, and video comprehension, yet they still struggle with the
intricate temporal and spatial cues found in comics. To address this gap, we
introduce ComicsPAP, a large-scale benchmark designed for comic strip
understanding. Comprising ove... | 2025-03-11T15:50:20Z | null | null | null | null | null | null | null | null | null | null |
2,503.08569 | DeepReview: Improving LLM-based Paper Review with Human-like Deep
Thinking Process | ['Minjun Zhu', 'Yixuan Weng', 'Linyi Yang', 'Yue Zhang'] | ['cs.CL', 'cs.LG'] | Large Language Models (LLMs) are increasingly utilized in scientific research
assessment, particularly in automated paper review. However, existing LLM-based
review systems face significant challenges, including limited domain expertise,
hallucinated reasoning, and a lack of structured evaluation. To address these
limi... | 2025-03-11T15:59:43Z | null | null | null | null | null | null | null | null | null | null |
2,503.08619 | LightGen: Efficient Image Generation through Knowledge Distillation and
Direct Preference Optimization | ['Xianfeng Wu', 'Yajing Bai', 'Haoze Zheng', 'Harold Haodong Chen', 'Yexin Liu', 'Zihao Wang', 'Xuran Ma', 'Wen-Jie Shu', 'Xianzu Wu', 'Harry Yang', 'Ser-Nam Lim'] | ['cs.CV'] | Recent advances in text-to-image generation have primarily relied on
extensive datasets and parameter-heavy architectures. These requirements
severely limit accessibility for researchers and practitioners who lack
substantial computational resources. In this paper, we introduce \model, an
efficient training paradigm fo... | 2025-03-11T16:58:02Z | Code: https://github.com/XianfengWu01/LightGen | null | null | null | null | null | null | null | null | null |
2,503.08638 | YuE: Scaling Open Foundation Models for Long-Form Music Generation | ['Ruibin Yuan', 'Hanfeng Lin', 'Shuyue Guo', 'Ge Zhang', 'Jiahao Pan', 'Yongyi Zang', 'Haohe Liu', 'Yiming Liang', 'Wenye Ma', 'Xingjian Du', 'Xinrun Du', 'Zhen Ye', 'Tianyu Zheng', 'Yinghao Ma', 'Minghao Liu', 'Zeyue Tian', 'Ziya Zhou', 'Liumeng Xue', 'Xingwei Qu', 'Yizhi Li', 'Shangda Wu', 'Tianhao Shen', 'Ziyang Ma'... | ['eess.AS', 'cs.AI', 'cs.MM', 'cs.SD'] | We tackle the task of long-form music generation--particularly the
challenging \textbf{lyrics-to-song} problem--by introducing YuE, a family of
open foundation models based on the LLaMA2 architecture. Specifically, YuE
scales to trillions of tokens and generates up to five minutes of music while
maintaining lyrical ali... | 2025-03-11T17:26:50Z | https://github.com/multimodal-art-projection/YuE | null | null | null | null | null | null | null | null | null |
2,503.08639 | GBlobs: Explicit Local Structure via Gaussian Blobs for Improved
Cross-Domain LiDAR-based 3D Object Detection | ['Dušan Malić', 'Christian Fruhwirth-Reisinger', 'Samuel Schulter', 'Horst Possegger'] | ['cs.CV'] | LiDAR-based 3D detectors need large datasets for training, yet they struggle
to generalize to novel domains. Domain Generalization (DG) aims to mitigate
this by training detectors that are invariant to such domain shifts. Current DG
approaches exclusively rely on global geometric features (point cloud Cartesian
coordin... | 2025-03-11T17:29:56Z | Accepted at CVPR 2025 | null | null | GBlobs: Explicit Local Structure via Gaussian Blobs for Improved Cross-Domain LiDAR-based 3D Object Detection | ["Duvsan Mali'c", 'Christian Fruhwirth-Reisinger', 'Samuel Schulter', 'Horst Possegger'] | 2,025 | arXiv.org | 0 | 68 | ['Computer Science'] |
2,503.08662 | Exploring the Word Sense Disambiguation Capabilities of Large Language
Models | ['Pierpaolo Basile', 'Lucia Siciliani', 'Elio Musacchio', 'Giovanni Semeraro'] | ['cs.CL', 'cs.AI'] | Word Sense Disambiguation (WSD) is a historical task in computational
linguistics that has received much attention over the years. However, with the
advent of Large Language Models (LLMs), interest in this task (in its classical
definition) has decreased. In this study, we evaluate the performance of
various LLMs on th... | 2025-03-11T17:50:44Z | null | null | null | null | null | null | null | null | null | null |
2,503.08686 | OmniMamba: Efficient and Unified Multimodal Understanding and Generation
via State Space Models | ['Jialv Zou', 'Bencheng Liao', 'Qian Zhang', 'Wenyu Liu', 'Xinggang Wang'] | ['cs.CV'] | Recent advancements in unified multimodal understanding and visual generation
(or multimodal generation) models have been hindered by their quadratic
computational complexity and dependence on large-scale training data. We
present OmniMamba, the first linear-architecture-based multimodal generation
model that generates... | 2025-03-11T17:59:46Z | null | null | null | null | null | null | null | null | null | null |
2,503.08805 | Filter Like You Test: Data-Driven Data Filtering for CLIP Pretraining | ['Mikey Shechter', 'Yair Carmon'] | ['cs.CV', 'cs.LG'] | We introduce Filter Like You Test (FLYT), an algorithm for curating
large-scale vision-language datasets that learns the usefulness of each data
point as a pretraining example. FLYT trains a scoring model that learns to
weigh each example's features using gradient signals from downstream tasks
training sets. Based on F... | 2025-03-11T18:34:12Z | null | null | null | Filter Like You Test: Data-Driven Data Filtering for CLIP Pretraining | ['Mikey Shechter', 'Y. Carmon'] | 2,025 | arXiv.org | 0 | 48 | ['Computer Science'] |
2,503.0889 | PlainQAFact: Automatic Factuality Evaluation Metric for Biomedical Plain
Language Summaries Generation | ['Zhiwen You', 'Yue Guo'] | ['cs.CL'] | Hallucinated outputs from language models pose risks in the medical domain,
especially for lay audiences making health-related decisions. Existing
factuality evaluation methods, such as entailment- and question-answering-based
(QA), struggle with plain language summary (PLS) generation due to elaborative
explanation ph... | 2025-03-11T20:59:53Z | null | null | null | PlainQAFact: Automatic Factuality Evaluation Metric for Biomedical Plain Language Summaries Generation | ['Zhiwen You', 'Yue Guo'] | 2,025 | arXiv.org | 0 | 49 | ['Computer Science'] |
2,503.08942 | Extragradient Preference Optimization (EGPO): Beyond Last-Iterate
Convergence for Nash Learning from Human Feedback | ['Runlong Zhou', 'Maryam Fazel', 'Simon S. Du'] | ['cs.LG'] | Reinforcement learning from human feedback (RLHF) has become essential for
improving language model capabilities, but traditional approaches rely on the
assumption that human preferences follow a transitive Bradley-Terry model. This
assumption fails to capture the non-transitive nature of populational human
preferences... | 2025-03-11T22:44:54Z | COLM 2025 | null | null | null | null | null | null | null | null | null |
2,503.08965 | LLM-Driven Usefulness Labeling for IR Evaluation | ['Mouly Dewan', 'Jiqun Liu', 'Chirag Shah'] | ['cs.IR'] | In the information retrieval (IR) domain, evaluation plays a crucial role in
optimizing search experiences and supporting diverse user intents. In the
recent LLM era, research has been conducted to automate document relevance
labels, as these labels have traditionally been assigned by crowd-sourced
workers - a process ... | 2025-03-12T00:07:39Z | null | null | null | LLM-Driven Usefulness Labeling for IR Evaluation | ['Mouly Dewan', 'Jiqun Liu', 'Chirag Shah'] | 2,025 | arXiv.org | 0 | 30 | ['Computer Science'] |
2,503.09089 | LocAgent: Graph-Guided LLM Agents for Code Localization | ['Zhaoling Chen', 'Xiangru Tang', 'Gangda Deng', 'Fang Wu', 'Jialong Wu', 'Zhiwei Jiang', 'Viktor Prasanna', 'Arman Cohan', 'Xingyao Wang'] | ['cs.SE', 'cs.AI', 'cs.CL'] | Code localization--identifying precisely where in a codebase changes need to
be made--is a fundamental yet challenging task in software maintenance.
Existing approaches struggle to efficiently navigate complex codebases when
identifying relevant code sections. The challenge lies in bridging natural
language problem des... | 2025-03-12T05:55:01Z | null | null | null | null | null | null | null | null | null | null |
2,503.09146 | Generative Frame Sampler for Long Video Understanding | ['Linli Yao', 'Haoning Wu', 'Kun Ouyang', 'Yuanxing Zhang', 'Caiming Xiong', 'Bei Chen', 'Xu Sun', 'Junnan Li'] | ['cs.CV', 'cs.MM'] | Despite recent advances in Video Large Language Models (VideoLLMs),
effectively understanding long-form videos remains a significant challenge.
Perceiving lengthy videos containing thousands of frames poses substantial
computational burden. To mitigate this issue, this paper introduces Generative
Frame Sampler (GenS), ... | 2025-03-12T08:16:39Z | null | null | null | null | null | null | null | null | null | null |
2,503.09197 | Teaching LMMs for Image Quality Scoring and Interpreting | ['Zicheng Zhang', 'Haoning Wu', 'Ziheng Jia', 'Weisi Lin', 'Guangtao Zhai'] | ['cs.CV'] | Image quality scoring and interpreting are two fundamental components of
Image Quality Assessment (IQA). The former quantifies image quality, while the
latter enables descriptive question answering about image quality.
Traditionally, these two tasks have been addressed independently. However, from
the perspective of th... | 2025-03-12T09:39:33Z | null | null | null | Teaching LMMs for Image Quality Scoring and Interpreting | ['Zicheng Zhang', 'Haoning Wu', 'Ziheng Jia', 'Weisi Lin', 'Guangtao Zhai'] | 2,025 | arXiv.org | 2 | 69 | ['Computer Science'] |
2,503.09279 | Cockatiel: Ensembling Synthetic and Human Preferenced Training for
Detailed Video Caption | ['Luozheng Qin', 'Zhiyu Tan', 'Mengping Yang', 'Xiaomeng Yang', 'Hao Li'] | ['cs.CV'] | Video Detailed Captioning (VDC) is a crucial task for vision-language
bridging, enabling fine-grained descriptions of complex video content. In this
paper, we first comprehensively benchmark current state-of-the-art approaches
and systematically identified two critical limitations: biased capability
towards specific ca... | 2025-03-12T11:25:04Z | For more details, please refer to our project page:
https://sais-fuxi.github.io/projects/cockatiel/ | null | null | null | null | null | null | null | null | null |
2,503.09313 | xVLM2Vec: Adapting LVLM-based embedding models to multilinguality using
Self-Knowledge Distillation | ['Elio Musacchio', 'Lucia Siciliani', 'Pierpaolo Basile', 'Giovanni Semeraro'] | ['cs.CL', 'cs.IR'] | In the current literature, most embedding models are based on the
encoder-only transformer architecture to extract a dense and meaningful
representation of the given input, which can be a text, an image, and more.
With the recent advances in language modeling thanks to the introduction of
Large Language Models, the pos... | 2025-03-12T12:04:05Z | fix typo in number of tasks in MMEB; fix url for source code; added
missing reference to XTD10 | null | null | xVLM2Vec: Adapting LVLM-based embedding models to multilinguality using Self-Knowledge Distillation | ['Elio Musacchio', 'Lucia Siciliani', 'Pierpaolo Basile', 'Giovanni Semeraro'] | 2,025 | arXiv.org | 0 | 32 | ['Computer Science'] |
2,503.09532 | SAEBench: A Comprehensive Benchmark for Sparse Autoencoders in Language
Model Interpretability | ['Adam Karvonen', 'Can Rager', 'Johnny Lin', 'Curt Tigges', 'Joseph Bloom', 'David Chanin', 'Yeu-Tong Lau', 'Eoin Farrell', 'Callum McDougall', 'Kola Ayonrinde', 'Demian Till', 'Matthew Wearden', 'Arthur Conmy', 'Samuel Marks', 'Neel Nanda'] | ['cs.LG', 'cs.CL'] | Sparse autoencoders (SAEs) are a popular technique for interpreting language
model activations, and there is extensive recent work on improving SAE
effectiveness. However, most prior work evaluates progress using unsupervised
proxy metrics with unclear practical relevance. We introduce SAEBench, a
comprehensive evaluat... | 2025-03-12T16:49:02Z | Accepted to ICML 2025 main conference | null | null | SAEBench: A Comprehensive Benchmark for Sparse Autoencoders in Language Model Interpretability | ['Adam Karvonen', 'Can Rager', 'Johnny Lin', 'Curt Tigges', 'Joseph Bloom', 'David Chanin', 'Yeu-Tong Lau', 'Eoin Farrell', 'Callum McDougall', 'Kola Ayonrinde', 'Matthew Wearden', 'Arthur Conmy', 'Samuel Marks', 'Neel Nanda'] | 2,025 | arXiv.org | 23 | 29 | ['Computer Science'] |
2,503.09573 | Block Diffusion: Interpolating Between Autoregressive and Diffusion
Language Models | ['Marianne Arriola', 'Aaron Gokaslan', 'Justin T. Chiu', 'Zhihan Yang', 'Zhixuan Qi', 'Jiaqi Han', 'Subham Sekhar Sahoo', 'Volodymyr Kuleshov'] | ['cs.LG', 'cs.AI'] | Diffusion language models offer unique benefits over autoregressive models
due to their potential for parallelized generation and controllability, yet
they lag in likelihood modeling and are limited to fixed-length generation. In
this work, we introduce a class of block diffusion language models that
interpolate betwee... | 2025-03-12T17:43:40Z | ICLR 2025 Oral. We provide the code at
https://github.com/kuleshov-group/bd3lms | null | null | null | null | null | null | null | null | null |
2,503.0959 | BIMBA: Selective-Scan Compression for Long-Range Video Question
Answering | ['Md Mohaiminul Islam', 'Tushar Nagarajan', 'Huiyu Wang', 'Gedas Bertasius', 'Lorenzo Torresani'] | ['cs.CV'] | Video Question Answering (VQA) in long videos poses the key challenge of
extracting relevant information and modeling long-range dependencies from many
redundant frames. The self-attention mechanism provides a general solution for
sequence modeling, but it has a prohibitive cost when applied to a massive
number of spat... | 2025-03-12T17:57:32Z | Accepted by CVPR 2025 | null | null | null | null | null | null | null | null | null |
2,503.096 | MoC: Mixtures of Text Chunking Learners for Retrieval-Augmented
Generation System | ['Jihao Zhao', 'Zhiyuan Ji', 'Zhaoxin Fan', 'Hanyu Wang', 'Simin Niu', 'Bo Tang', 'Feiyu Xiong', 'Zhiyu Li'] | ['cs.CL'] | Retrieval-Augmented Generation (RAG), while serving as a viable complement to
large language models (LLMs), often overlooks the crucial aspect of text
chunking within its pipeline. This paper initially introduces a dual-metric
evaluation method, comprising Boundary Clarity and Chunk Stickiness, to enable
the direct qua... | 2025-03-12T17:59:42Z | null | null | null | null | null | null | null | null | null | null |
2,503.09641 | SANA-Sprint: One-Step Diffusion with Continuous-Time Consistency
Distillation | ['Junsong Chen', 'Shuchen Xue', 'Yuyang Zhao', 'Jincheng Yu', 'Sayak Paul', 'Junyu Chen', 'Han Cai', 'Song Han', 'Enze Xie'] | ['cs.GR'] | This paper presents SANA-Sprint, an efficient diffusion model for ultra-fast
text-to-image (T2I) generation. SANA-Sprint is built on a pre-trained
foundation model and augmented with hybrid distillation, dramatically reducing
inference steps from 20 to 1-4. We introduce three key innovations: (1) We
propose a training-... | 2025-03-12T04:53:07Z | 22 pages, 11 figures, 8 tables, In submission | null | null | null | null | null | null | null | null | null |
2,503.09642 | Open-Sora 2.0: Training a Commercial-Level Video Generation Model in
$200k | ['Xiangyu Peng', 'Zangwei Zheng', 'Chenhui Shen', 'Tom Young', 'Xinying Guo', 'Binluo Wang', 'Hang Xu', 'Hongxin Liu', 'Mingyan Jiang', 'Wenjun Li', 'Yuhui Wang', 'Anbang Ye', 'Gang Ren', 'Qianran Ma', 'Wanying Liang', 'Xiang Lian', 'Xiwen Wu', 'Yuting Zhong', 'Zhuangyan Li', 'Chaoyu Gong', 'Guojun Lei', 'Leijun Cheng'... | ['cs.GR', 'cs.AI'] | Video generation models have achieved remarkable progress in the past year.
The quality of AI video continues to improve, but at the cost of larger model
size, increased data quantity, and greater demand for training compute. In this
report, we present Open-Sora 2.0, a commercial-level video generation model
trained fo... | 2025-03-12T05:00:07Z | null | null | null | Open-Sora 2.0: Training a Commercial-Level Video Generation Model in $200k | ['Xiangyu Peng', 'Zangwei Zheng', 'Chenhui Shen', 'Tom Young', 'Xinying Guo', 'Binluo Wang', 'Hang Xu', 'Hongxin Liu', 'Mingyan Jiang', 'Wenjun Li', 'Yuhui Wang', 'Anbang Ye', 'Gang Ren', 'Qianran Ma', 'Wanying Liang', 'Xiang Lian', 'Xiwen Wu', 'Yu Zhong', 'Zhuangyan Li', 'Chaoyu Gong', 'Guojun Lei', 'Leijun Cheng', 'L... | 2,025 | arXiv.org | 13 | 44 | ['Computer Science'] |
2,503.09662 | CoRe^2: Collect, Reflect and Refine to Generate Better and Faster | ['Shitong Shao', 'Zikai Zhou', 'Dian Xie', 'Yuetong Fang', 'Tian Ye', 'Lichen Bai', 'Zeke Xie'] | ['cs.CV'] | Making text-to-image (T2I) generative model sample both fast and well
represents a promising research direction. Previous studies have typically
focused on either enhancing the visual quality of synthesized images at the
expense of sampling efficiency or dramatically accelerating sampling without
improving the base mod... | 2025-03-12T15:15:25Z | null | null | null | CoRe2: Collect, Reflect and Refine to Generate Better and Faster | ['Shitong Shao', 'Zikai Zhou', 'Dian Xie', 'Yuetong Fang', 'Tian Ye', 'Lichen Bai', 'Zeke Xie'] | 2,025 | arXiv.org | 0 | 43 | ['Computer Science'] |
2,503.10076 | VMBench: A Benchmark for Perception-Aligned Video Motion Generation | ['Xinran Ling', 'Chen Zhu', 'Meiqi Wu', 'Hangyu Li', 'Xiaokun Feng', 'Cundian Yang', 'Aiming Hao', 'Jiashu Zhu', 'Jiahong Wu', 'Xiangxiang Chu'] | ['cs.CV'] | Video generation has advanced rapidly, improving evaluation methods, yet
assessing video's motion remains a major challenge. Specifically, there are two
key issues: 1) current motion metrics do not fully align with human
perceptions; 2) the existing motion prompts are limited. Based on these
findings, we introduce VMBe... | 2025-03-13T05:54:42Z | null | null | null | null | null | null | null | null | null | null |
2,503.10267 | An Expanded Massive Multilingual Dataset for High-Performance Language
Technologies (HPLT) | ['Laurie Burchell', 'Ona de Gibert', 'Nikolay Arefyev', 'Mikko Aulamo', 'Marta Bañón', 'Pinzhen Chen', 'Mariia Fedorova', 'Liane Guillou', 'Barry Haddow', 'Jan Hajič', 'Jindřich Helcl', 'Erik Henriksson', 'Mateusz Klimaszewski', 'Ville Komulainen', 'Andrey Kutuzov', 'Joona Kytöniemi', 'Veronika Laippala', 'Petter Mæhlu... | ['cs.CL'] | Training state-of-the-art large language models requires vast amounts of
clean and diverse textual data. However, building suitable multilingual
datasets remains a challenge. In this work, we present HPLT v2, a collection of
high-quality multilingual monolingual and parallel corpora, extending prior
work of the HPLT pr... | 2025-03-13T11:24:09Z | ACL'2025 Main Proceedings | null | null | An Expanded Massive Multilingual Dataset for High-Performance Language Technologies | ['Laurie Burchell', 'Ona de Gibert', 'Nikolay Arefyev', 'Mikko Aulamo', 'Marta Bañón', 'Pinzhen Chen', 'Mariia Fedorova', 'Liane Guillou', 'Barry Haddow', 'Jan Hajivc', 'and Jindvrich Helcl', 'Erik Henriksson', 'Mateusz Klimaszewski', 'Ville Komulainen', 'Andrey Kutuzov', 'Joona Kytoniemi', 'Veronika Laippala', 'Petter... | 2,025 | arXiv.org | 4 | 64 | ['Computer Science'] |
2,503.10286 | VicaSplat: A Single Run is All You Need for 3D Gaussian Splatting and
Camera Estimation from Unposed Video Frames | ['Zhiqi Li', 'Chengrui Dong', 'Yiming Chen', 'Zhangchi Huang', 'Peidong Liu'] | ['cs.CV'] | We present VicaSplat, a novel framework for joint 3D Gaussians reconstruction
and camera pose estimation from a sequence of unposed video frames, which is a
critical yet underexplored task in real-world 3D applications. The core of our
method lies in a novel transformer-based network architecture. In particular,
our mo... | 2025-03-13T11:56:05Z | null | null | null | VicaSplat: A Single Run is All You Need for 3D Gaussian Splatting and Camera Estimation from Unposed Video Frames | ['Zhiqi Li', 'Chengrui Dong', 'Yiming Chen', 'Zhangchi Huang', 'Peidong Liu'] | 2,025 | arXiv.org | 2 | 49 | ['Computer Science'] |
2,503.10291 | VisualPRM: An Effective Process Reward Model for Multimodal Reasoning | ['Weiyun Wang', 'Zhangwei Gao', 'Lianjie Chen', 'Zhe Chen', 'Jinguo Zhu', 'Xiangyu Zhao', 'Yangzhou Liu', 'Yue Cao', 'Shenglong Ye', 'Xizhou Zhu', 'Lewei Lu', 'Haodong Duan', 'Yu Qiao', 'Jifeng Dai', 'Wenhai Wang'] | ['cs.CV', 'cs.CL'] | We introduce VisualPRM, an advanced multimodal Process Reward Model (PRM)
with 8B parameters, which improves the reasoning abilities of existing
Multimodal Large Language Models (MLLMs) across different model scales and
families with Best-of-N (BoN) evaluation strategies. Specifically, our model
improves the reasoning ... | 2025-03-13T12:03:37Z | null | null | null | VisualPRM: An Effective Process Reward Model for Multimodal Reasoning | ['Weiyun Wang', 'Zhangwei Gao', 'Lianjie Chen', 'Zhe Chen', 'Jinguo Zhu', 'Xiangyu Zhao', 'Yangzhou Liu', 'Yue Cao', 'Shenglong Ye', 'Xizhou Zhu', 'Lewei Lu', 'Haodong Duan', 'Yu Qiao', 'Jifeng Dai', 'Wenhai Wang'] | 2,025 | arXiv.org | 39 | 98 | ['Computer Science'] |
2,503.10354 | A Hybrid Architecture with Efficient Fine Tuning for Abstractive Patent
Document Summarization | ['Nevidu Jayatilleke', 'Ruvan Weerasinghe'] | ['cs.CL'] | Automatic patent summarization approaches that help in the patent analysis
and comprehension procedure are in high demand due to the colossal growth of
innovations. The development of natural language processing (NLP), text mining,
and deep learning has notably amplified the efficacy of text summarization
models for ab... | 2025-03-13T13:30:54Z | 8th International Research Conference on Smart Computing and Systems
Engineering, University of Kelaniya, Sri Lanka | null | 10.1109/SCSE65633.2025.11030964 | null | null | null | null | null | null | null |
2,503.10365 | Piece it Together: Part-Based Concepting with IP-Priors | ['Elad Richardson', 'Kfir Goldberg', 'Yuval Alaluf', 'Daniel Cohen-Or'] | ['cs.CV'] | Advanced generative models excel at synthesizing images but often rely on
text-based conditioning. Visual designers, however, often work beyond language,
directly drawing inspiration from existing visual elements. In many cases,
these elements represent only fragments of a potential concept-such as an
uniquely structur... | 2025-03-13T13:46:10Z | Project page available at https://eladrich.github.io/PiT/ | null | null | null | null | null | null | null | null | null |
2,503.10392 | RoMA: Scaling up Mamba-based Foundation Models for Remote Sensing | ['Fengxiang Wang', 'Hongzhen Wang', 'Yulin Wang', 'Di Wang', 'Mingshuo Chen', 'Haiyan Zhao', 'Yangang Sun', 'Shuo Wang', 'Long Lan', 'Wenjing Yang', 'Jing Zhang'] | ['cs.CV', 'cs.AI'] | Recent advances in self-supervised learning for Vision Transformers (ViTs)
have fueled breakthroughs in remote sensing (RS) foundation models. However,
the quadratic complexity of self-attention poses a significant barrier to
scalability, particularly for large models and high-resolution images. While
the linear-comple... | 2025-03-13T14:09:18Z | null | null | null | RoMA: Scaling up Mamba-based Foundation Models for Remote Sensing | ['Fengxiang Wang', 'Hongzhen Wang', 'Yulin Wang', 'Di Wang', 'Mingshuo Chen', 'Haiyan Zhao', 'Yangang Sun', 'Shuo Wang', 'Long Lan', 'Wenjing Yang', 'Jing Zhang'] | 2,025 | arXiv.org | 3 | 70 | ['Computer Science'] |
2,503.10437 | 4D LangSplat: 4D Language Gaussian Splatting via Multimodal Large
Language Models | ['Wanhua Li', 'Renping Zhou', 'Jiawei Zhou', 'Yingwei Song', 'Johannes Herter', 'Minghan Qin', 'Gao Huang', 'Hanspeter Pfister'] | ['cs.CV'] | Learning 4D language fields to enable time-sensitive, open-ended language
queries in dynamic scenes is essential for many real-world applications. While
LangSplat successfully grounds CLIP features into 3D Gaussian representations,
achieving precision and efficiency in 3D static scenes, it lacks the ability to
handle d... | 2025-03-13T14:58:22Z | CVPR 2025. Project Page: https://4d-langsplat.github.io | null | null | 4D LangSplat: 4D Language Gaussian Splatting via Multimodal Large Language Models | ['Wanhua Li', 'Renping Zhou', 'Jiawei Zhou', 'Yingwei Song', 'Johannes Herter', 'Minghan Qin', 'Gao Huang', 'Hanspeter Pfister'] | 2,025 | arXiv.org | 3 | 69 | ['Computer Science'] |
2,503.1046 | Light-R1: Curriculum SFT, DPO and RL for Long COT from Scratch and
Beyond | ['Liang Wen', 'Yunke Cai', 'Fenrui Xiao', 'Xin He', 'Qi An', 'Zhenyu Duan', 'Yimin Du', 'Junchen Liu', 'Lifu Tang', 'Xiaowei Lv', 'Haosheng Zou', 'Yongchao Deng', 'Shousheng Jia', 'Xiangzheng Zhang'] | ['cs.CL', 'cs.LG'] | This paper introduces Light-R1, an open-source suite for training long
reasoning models using reproducible and cost-effective methodology. Given the
proprietary nature of data used in the DeepSeek-R1 series, we develop an
alternative approach leveraging exclusively public data and models. Our
curriculum training progre... | 2025-03-13T15:29:22Z | v4: ACL'25 industry track camera ready; v3: minor modifications; v2:
better writing & format for later submission; all release at
https://github.com/Qihoo360/Light-R1 | null | null | null | null | null | null | null | null | null |
2,503.10522 | AudioX: Diffusion Transformer for Anything-to-Audio Generation | ['Zeyue Tian', 'Yizhu Jin', 'Zhaoyang Liu', 'Ruibin Yuan', 'Xu Tan', 'Qifeng Chen', 'Wei Xue', 'Yike Guo'] | ['cs.MM', 'cs.CV', 'cs.LG', 'cs.SD', 'eess.AS'] | Audio and music generation have emerged as crucial tasks in many
applications, yet existing approaches face significant limitations: they
operate in isolation without unified capabilities across modalities, suffer
from scarce high-quality, multi-modal training data, and struggle to
effectively integrate diverse inputs.... | 2025-03-13T16:30:59Z | The code and datasets will be available at
https://zeyuet.github.io/AudioX/ | null | null | AudioX: Diffusion Transformer for Anything-to-Audio Generation | ['Zeyue Tian', 'Yizhu Jin', 'Zhaoyang Liu', 'Ruibin Yuan', 'Xu Tan', 'Qifeng Chen', 'Wei Xue', 'Yi-Ting Guo'] | 2,025 | arXiv.org | 6 | 72 | ['Computer Science', 'Engineering'] |
2,503.10568 | Autoregressive Image Generation with Randomized Parallel Decoding | ['Haopeng Li', 'Jinyue Yang', 'Guoqi Li', 'Huan Wang'] | ['cs.CV'] | We introduce ARPG, a novel visual autoregressive model that enables
randomized parallel generation, addressing the inherent limitations of
conventional raster-order approaches, which hinder inference efficiency and
zero-shot generalization due to their sequential, predefined token generation
order. Our key insight is t... | 2025-03-13T17:19:51Z | null | null | null | null | null | null | null | null | null | null |
2,503.10582 | VisualWebInstruct: Scaling up Multimodal Instruction Data through Web
Search | ['Yiming Jia', 'Jiachen Li', 'Xiang Yue', 'Bo Li', 'Ping Nie', 'Kai Zou', 'Wenhu Chen'] | ['cs.CV', 'cs.AI', 'cs.CL'] | Vision-Language Models have made significant progress on many
perception-focused tasks. However, their progress on reasoning-focused tasks
remains limited due to the lack of high-quality and diverse training data. In
this work, we aim to address the scarcity of reasoning-focused multimodal
datasets. We propose VisualWe... | 2025-03-13T17:32:48Z | Technical Report | null | null | VisualWebInstruct: Scaling up Multimodal Instruction Data through Web Search | ['Yiming Jia', 'Jiachen Li', 'Xiang Yue', 'Bo Li', 'Ping Nie', 'Kai Zou', 'Wenhu Chen'] | 2,025 | arXiv.org | 4 | 65 | ['Computer Science'] |
2,503.1062 | From TOWER to SPIRE: Adding the Speech Modality to a Text-Only LLM | ['Kshitij Ambilduke', 'Ben Peters', 'Sonal Sannigrahi', 'Anil Keshwani', 'Tsz Kin Lam', 'Bruno Martins', 'Marcely Zanon Boito', 'André F. T. Martins'] | ['cs.CL'] | Large language models (LLMs) have shown remarkable performance and
generalization capabilities across multiple languages and tasks, making them
very attractive targets for multi-modality integration (e.g., images or
speech). In this work, we extend an existing LLM to the speech modality via
speech discretization and co... | 2025-03-13T17:57:32Z | null | null | null | null | null | null | null | null | null | null |
2,503.10621 | DriveLMM-o1: A Step-by-Step Reasoning Dataset and Large Multimodal Model
for Driving Scenario Understanding | ['Ayesha Ishaq', 'Jean Lahoud', 'Ketan More', 'Omkar Thawakar', 'Ritesh Thawkar', 'Dinura Dissanayake', 'Noor Ahsan', 'Yuhao Li', 'Fahad Shahbaz Khan', 'Hisham Cholakkal', 'Ivan Laptev', 'Rao Muhammad Anwer', 'Salman Khan'] | ['cs.CV', 'cs.RO'] | While large multimodal models (LMMs) have demonstrated strong performance
across various Visual Question Answering (VQA) tasks, certain challenges
require complex multi-step reasoning to reach accurate answers. One
particularly challenging task is autonomous driving, which demands thorough
cognitive processing before d... | 2025-03-13T17:59:01Z | 8 pages, 4 figures, 3 tables, github:
https://github.com/ayesha-ishaq/DriveLMM-o1 | null | null | DriveLMM-o1: A Step-by-Step Reasoning Dataset and Large Multimodal Model for Driving Scenario Understanding | ['Ayesha Ishaq', 'Jean Lahoud', 'Ketan More', 'Omkar Thawakar', 'Ritesh Thawkar', 'Dinura Dissanayake', 'Noor Ahsan', 'Yuhao Li', 'F. Khan', 'Hisham Cholakkal', 'Ivan Laptev', 'R. Anwer', 'Salman Khan'] | 2,025 | arXiv.org | 4 | 32 | ['Computer Science'] |
2,503.10625 | LHM: Large Animatable Human Reconstruction Model from a Single Image in
Seconds | ['Lingteng Qiu', 'Xiaodong Gu', 'Peihao Li', 'Qi Zuo', 'Weichao Shen', 'Junfei Zhang', 'Kejie Qiu', 'Weihao Yuan', 'Guanying Chen', 'Zilong Dong', 'Liefeng Bo'] | ['cs.CV', 'cs.AI'] | Animatable 3D human reconstruction from a single image is a challenging
problem due to the ambiguity in decoupling geometry, appearance, and
deformation. Recent advances in 3D human reconstruction mainly focus on static
human modeling, and the reliance of using synthetic 3D scans for training
limits their generalizatio... | 2025-03-13T17:59:21Z | Project Page: https://lingtengqiu.github.io/LHM/ | null | null | null | null | null | null | null | null | null |
2,503.10636 | The Curse of Conditions: Analyzing and Improving Optimal Transport for
Conditional Flow-Based Generation | ['Ho Kei Cheng', 'Alexander Schwing'] | ['cs.LG', 'cs.CV'] | Minibatch optimal transport coupling straightens paths in unconditional flow
matching. This leads to computationally less demanding inference as fewer
integration steps and less complex numerical solvers can be employed when
numerically solving an ordinary differential equation at test time. However, in
the conditional... | 2025-03-13T17:59:56Z | Project page: https://hkchengrex.github.io/C2OT | null | null | null | null | null | null | null | null | null |
2,503.10684 | Open-World Skill Discovery from Unsegmented Demonstrations | ['Jingwen Deng', 'Zihao Wang', 'Shaofei Cai', 'Anji Liu', 'Yitao Liang'] | ['cs.CV', 'cs.AI'] | Learning skills in open-world environments is essential for developing agents
capable of handling a variety of tasks by combining basic skills. Online
demonstration videos are typically long but unsegmented, making them difficult
to segment and label with skill identifiers. Unlike existing methods that rely
on sequence... | 2025-03-11T18:51:40Z | null | null | null | Open-World Skill Discovery from Unsegmented Demonstrations | ['Jingwen Deng', 'Zihao Wang', 'Shaofei Cai', 'Anji Liu', 'Yitao Liang'] | 2,025 | arXiv.org | 1 | 52 | ['Computer Science'] |
2,503.10745 | Unifying 2D and 3D Vision-Language Understanding | ['Ayush Jain', 'Alexander Swerdlow', 'Yuzhou Wang', 'Sergio Arnaud', 'Ada Martin', 'Alexander Sax', 'Franziska Meier', 'Katerina Fragkiadaki'] | ['cs.CV', 'cs.AI', 'cs.RO'] | Progress in 3D vision-language learning has been hindered by the scarcity of
large-scale 3D datasets. We introduce UniVLG, a unified architecture for 2D and
3D vision-language understanding that bridges the gap between existing
2D-centric models and the rich 3D sensory data available in embodied systems.
Our approach i... | 2025-03-13T17:56:22Z | The first two authors contributed equally | null | null | null | null | null | null | null | null | null |
2,503.10905 | Learning to Inference Adaptively for Multimodal Large Language Models | ['Zhuoyan Xu', 'Khoi Duc Nguyen', 'Preeti Mukherjee', 'Saurabh Bagchi', 'Somali Chaterji', 'Yingyu Liang', 'Yin Li'] | ['cs.AI', 'cs.CV', 'cs.LG'] | Multimodal Large Language Models (MLLMs) have shown impressive capabilities
in reasoning, yet come with substantial computational cost, limiting their
deployment in resource-constrained settings. Despite recent efforts on
improving the efficiency of MLLMs, prior solutions fall short in responding to
varying runtime con... | 2025-03-13T21:39:38Z | null | null | null | null | null | null | null | null | null | null |
2,503.10944 | Phishsense-1B: A Technical Perspective on an AI-Powered Phishing
Detection Model | ['SE Blake'] | ['cs.CR', 'cs.LG'] | Phishing is a persistent cybersecurity threat in today's digital landscape.
This paper introduces Phishsense-1B, a refined version of the Llama-Guard-3-1B
model, specifically tailored for phishing detection and reasoning. This
adaptation utilizes Low-Rank Adaptation (LoRA) and the GuardReasoner finetuning
methodology. ... | 2025-03-13T23:03:09Z | Phishing Detection Model
https://huggingface.co/AcuteShrewdSecurity/Llama-Phishsense-1B | null | null | null | null | null | null | null | null | null |
2,503.1097 | TxAgent: An AI Agent for Therapeutic Reasoning Across a Universe of
Tools | ['Shanghua Gao', 'Richard Zhu', 'Zhenglun Kong', 'Ayush Noori', 'Xiaorui Su', 'Curtis Ginder', 'Theodoros Tsiligkaridis', 'Marinka Zitnik'] | ['cs.AI', 'cs.LG'] | Precision therapeutics require multimodal adaptive models that generate
personalized treatment recommendations. We introduce TxAgent, an AI agent that
leverages multi-step reasoning and real-time biomedical knowledge retrieval
across a toolbox of 211 tools to analyze drug interactions, contraindications,
and patient-sp... | 2025-03-14T00:28:15Z | Project page: https://zitniklab.hms.harvard.edu/TxAgent TxAgent code:
https://github.com/mims-harvard/TxAgent ToolUniverse code:
https://github.com/mims-harvard/ToolUniverse | null | null | TxAgent: An AI Agent for Therapeutic Reasoning Across a Universe of Tools | ['Shanghua Gao', 'Richard Zhu', 'Zhenglun Kong', 'Ayush Noori', 'Xiaorui Su', 'Curtis R Ginder', 'Theodoros Tsiligkaridis', 'Marinka Zitnik'] | 2,025 | arXiv.org | 8 | 0 | ['Computer Science'] |
2,503.10995 | TigerLLM - A Family of Bangla Large Language Models | ['Nishat Raihan', 'Marcos Zampieri'] | ['cs.CL'] | The development of Large Language Models (LLMs) remains heavily skewed
towards English and a few other high-resource languages. This linguistic
disparity is particularly evident for Bangla - the 5th most spoken language. A
few initiatives attempted to create open-source Bangla LLMs with performance
still behind high-re... | 2025-03-14T01:41:16Z | null | null | null | TigerLLM - A Family of Bangla Large Language Models | ['Nishat Raihan', 'Marcos Zampieri'] | 2,025 | arXiv.org | 0 | 25 | ['Computer Science'] |
2,503.11073 | Perceive, Understand and Restore: Real-World Image Super-Resolution with
Autoregressive Multimodal Generative Models | ['Hongyang Wei', 'Shuaizheng Liu', 'Chun Yuan', 'Lei Zhang'] | ['cs.CV'] | By leveraging the generative priors from pre-trained text-to-image diffusion
models, significant progress has been made in real-world image super-resolution
(Real-ISR). However, these methods tend to generate inaccurate and unnatural
reconstructions in complex and/or heavily degraded scenes, primarily due to
their limi... | 2025-03-14T04:33:59Z | null | null | null | null | null | null | null | null | null | null |
2,503.11129 | Direction-Aware Diagonal Autoregressive Image Generation | ['Yijia Xu', 'Jianzhong Ju', 'Jian Luan', 'Jinshi Cui'] | ['cs.CV', 'cs.AI'] | The raster-ordered image token sequence exhibits a significant Euclidean
distance between index-adjacent tokens at line breaks, making it unsuitable for
autoregressive generation. To address this issue, this paper proposes
Direction-Aware Diagonal Autoregressive Image Generation (DAR) method, which
generates image toke... | 2025-03-14T06:44:01Z | null | null | null | null | null | null | null | null | null | null |
2,503.1117 | DeskVision: Large Scale Desktop Region Captioning for Advanced GUI
Agents | ['Yibin Xu', 'Liang Yang', 'Hao Chen', 'Hua Wang', 'Zhi Chen', 'Yaohua Tang'] | ['cs.CL'] | The limitation of graphical user interface (GUI) data has been a significant
barrier to the development of GUI agents today, especially for the desktop /
computer use scenarios. To address this, we propose an automated GUI data
generation pipeline, AutoCaptioner, which generates data with rich descriptions
while minimi... | 2025-03-14T08:16:02Z | null | null | null | null | null | null | null | null | null | null |
2,503.11197 | Reinforcement Learning Outperforms Supervised Fine-Tuning: A Case Study
on Audio Question Answering | ['Gang Li', 'Jizhong Liu', 'Heinrich Dinkel', 'Yadong Niu', 'Junbo Zhang', 'Jian Luan'] | ['cs.SD', 'cs.AI', 'cs.CL', 'eess.AS'] | Recently, reinforcement learning (RL) has been shown to greatly enhance the
reasoning capabilities of large language models (LLMs), and RL-based approaches
have been progressively applied to visual multimodal tasks. However, the audio
modality has largely been overlooked in these developments. Thus, we conduct a
series... | 2025-03-14T08:43:53Z | null | null | null | null | null | null | null | null | null | null |
2,503.11221 | Toward Generalized Image Quality Assessment: Relaxing the Perfect
Reference Quality Assumption | ['Du Chen', 'Tianhe Wu', 'Kede Ma', 'Lei Zhang'] | ['cs.CV'] | Full-reference image quality assessment (FR-IQA) generally assumes that
reference images are of perfect quality. However, this assumption is flawed due
to the sensor and optical limitations of modern imaging systems. Moreover,
recent generative enhancement methods are capable of producing images of higher
quality than ... | 2025-03-14T09:12:03Z | Accepted by CVPR 2025 | null | null | null | null | null | null | null | null | null |
2,503.11251 | Step-Video-TI2V Technical Report: A State-of-the-Art Text-Driven
Image-to-Video Generation Model | ['Haoyang Huang', 'Guoqing Ma', 'Nan Duan', 'Xing Chen', 'Changyi Wan', 'Ranchen Ming', 'Tianyu Wang', 'Bo Wang', 'Zhiying Lu', 'Aojie Li', 'Xianfang Zeng', 'Xinhao Zhang', 'Gang Yu', 'Yuhe Yin', 'Qiling Wu', 'Wen Sun', 'Kang An', 'Xin Han', 'Deshan Sun', 'Wei Ji', 'Bizhu Huang', 'Brian Li', 'Chenfei Wu', 'Guanzhe Huan... | ['cs.CV', 'cs.CL'] | We present Step-Video-TI2V, a state-of-the-art text-driven image-to-video
generation model with 30B parameters, capable of generating videos up to 102
frames based on both text and image inputs. We build Step-Video-TI2V-Eval as a
new benchmark for the text-driven image-to-video task and compare
Step-Video-TI2V with ope... | 2025-03-14T10:01:55Z | 7 pages | null | null | null | null | null | null | null | null | null |
2,503.11299 | BriLLM: Brain-inspired Large Language Model | ['Hai Zhao', 'Hongqiu Wu', 'Dongjie Yang', 'Anni Zou', 'Jiale Hong'] | ['cs.CL', 'cs.AI'] | This paper reports the first brain-inspired large language model (BriLLM).
This is a non-Transformer, non-GPT, non-traditional machine learning
input-output controlled generative language model. The model is based on the
Signal Fully-connected flowing (SiFu) definition on the directed graph in terms
of the neural netwo... | 2025-03-14T11:08:30Z | null | null | null | null | null | null | null | null | null | null |
2,503.11341 | Self-Supervised Pretraining for Fine-Grained Plankton Recognition | ['Joona Kareinen', 'Tuomas Eerola', 'Kaisa Kraft', 'Lasse Lensu', 'Sanna Suikkanen', 'Heikki Kälviäinen'] | ['cs.CV'] | Plankton recognition is an important computer vision problem due to
plankton's essential role in ocean food webs and carbon capture, highlighting
the need for species-level monitoring. However, this task is challenging due to
its fine-grained nature and dataset shifts caused by different imaging
instruments and varying... | 2025-03-14T12:15:20Z | CVPR 2025, FGVC12 workshop paper | null | null | null | null | null | null | null | null | null |
2,503.11509 | TikZero: Zero-Shot Text-Guided Graphics Program Synthesis | ['Jonas Belouadi', 'Eddy Ilg', 'Margret Keuper', 'Hideki Tanaka', 'Masao Utiyama', 'Raj Dabre', 'Steffen Eger', 'Simone Paolo Ponzetto'] | ['cs.CL', 'cs.CV'] | With the rise of generative AI, synthesizing figures from text captions
becomes a compelling application. However, achieving high geometric precision
and editability requires representing figures as graphics programs in languages
like TikZ, and aligned training data (i.e., graphics programs with captions)
remains scarc... | 2025-03-14T15:29:58Z | Project page: https://github.com/potamides/DeTikZify | null | null | TikZero: Zero-Shot Text-Guided Graphics Program Synthesis | ['Jonas Belouadi', 'Eddy Ilg', 'Margret Keuper', 'Hideki Tanaka', 'Masao Utiyama', 'Raj Dabre', 'Steffen Eger', 'Simone Paolo Ponzetto'] | 2,025 | arXiv.org | 0 | 85 | ['Computer Science'] |
2,503.11576 | SmolDocling: An ultra-compact vision-language model for end-to-end
multi-modal document conversion | ['Ahmed Nassar', 'Andres Marafioti', 'Matteo Omenetti', 'Maksym Lysak', 'Nikolaos Livathinos', 'Christoph Auer', 'Lucas Morin', 'Rafael Teixeira de Lima', 'Yusik Kim', 'A. Said Gurbuz', 'Michele Dolfi', 'Miquel Farré', 'Peter W. J. Staar'] | ['cs.CV'] | We introduce SmolDocling, an ultra-compact vision-language model targeting
end-to-end document conversion. Our model comprehensively processes entire
pages by generating DocTags, a new universal markup format that captures all
page elements in their full context with location. Unlike existing approaches
that rely on la... | 2025-03-14T16:44:14Z | 24 pages, 10 figures | null | null | null | null | null | null | null | null | null |
2,503.11579 | Vamba: Understanding Hour-Long Videos with Hybrid Mamba-Transformers | ['Weiming Ren', 'Wentao Ma', 'Huan Yang', 'Cong Wei', 'Ge Zhang', 'Wenhu Chen'] | ['cs.CV'] | State-of-the-art transformer-based large multimodal models (LMMs) struggle to
handle hour-long video inputs due to the quadratic complexity of the causal
self-attention operations, leading to high computational costs during training
and inference. Existing token compression-based methods reduce the number of
video toke... | 2025-03-14T16:45:23Z | ICCV 2025 Camera Ready Version. Project Page:
https://tiger-ai-lab.github.io/Vamba/ | null | null | Vamba: Understanding Hour-Long Videos with Hybrid Mamba-Transformers | ['Weiming Ren', 'Wentao Ma', 'Huan Yang', 'Cong Wei', 'Ge Zhang', 'Wenhu Chen'] | 2,025 | arXiv.org | 5 | 75 | ['Computer Science'] |
2,503.11591 | Pathology Image Compression with Pre-trained Autoencoders | ['Srikar Yellapragada', 'Alexandros Graikos', 'Kostas Triaridis', 'Zilinghan Li', 'Tarak Nath Nandi', 'Ravi K Madduri', 'Prateek Prasanna', 'Joel Saltz', 'Dimitris Samaras'] | ['eess.IV', 'cs.CV'] | The growing volume of high-resolution Whole Slide Images in digital
histopathology poses significant storage, transmission, and computational
efficiency challenges. Standard compression methods, such as JPEG, reduce file
sizes but often fail to preserve fine-grained phenotypic details critical for
downstream tasks. In ... | 2025-03-14T17:01:17Z | null | null | null | Pathology Image Compression with Pre-trained Autoencoders | ['Srikar Yellapragada', 'Alexandros Graikos', 'Kostas Triaridis', 'Zilinghan Li', 'T. Nandi', 'Ravi K. Madduri', 'Prateek Prasanna', 'J. Saltz', 'Dimitris Samaras'] | 2,025 | arXiv.org | 0 | 28 | ['Computer Science', 'Engineering'] |
2,503.11651 | VGGT: Visual Geometry Grounded Transformer | ['Jianyuan Wang', 'Minghao Chen', 'Nikita Karaev', 'Andrea Vedaldi', 'Christian Rupprecht', 'David Novotny'] | ['cs.CV'] | We present VGGT, a feed-forward neural network that directly infers all key
3D attributes of a scene, including camera parameters, point maps, depth maps,
and 3D point tracks, from one, a few, or hundreds of its views. This approach
is a step forward in 3D computer vision, where models have typically been
constrained t... | 2025-03-14T17:59:47Z | CVPR 2025, Project Page: https://vgg-t.github.io/ | null | null | VGGT: Visual Geometry Grounded Transformer | ['Jianyuan Wang', 'Minghao Chen', 'Nikita Karaev', 'Andrea Vedaldi', 'Christian Rupprecht', 'David Novotný'] | 2,025 | Computer Vision and Pattern Recognition | 38 | 151 | ['Computer Science'] |
2,503.11849 | Towards a Unified Copernicus Foundation Model for Earth Vision | ['Yi Wang', 'Zhitong Xiong', 'Chenying Liu', 'Adam J. Stewart', 'Thomas Dujardin', 'Nikolaos Ioannis Bountos', 'Angelos Zavras', 'Franziska Gerken', 'Ioannis Papoutsis', 'Laura Leal-Taixé', 'Xiao Xiang Zhu'] | ['cs.CV'] | Advances in Earth observation (EO) foundation models have unlocked the
potential of big satellite data to learn generic representations from space,
benefiting a wide range of downstream applications crucial to our planet.
However, most existing efforts remain limited to fixed spectral sensors, focus
solely on the Earth... | 2025-03-14T20:16:48Z | 31 pages, 32 figures | null | null | null | null | null | null | null | null | null |
2,503.12127 | Hyperbolic Safety-Aware Vision-Language Models | ['Tobia Poppi', 'Tejaswi Kasarla', 'Pascal Mettes', 'Lorenzo Baraldi', 'Rita Cucchiara'] | ['cs.CV', 'cs.AI', 'cs.CL', 'cs.MM'] | Addressing the retrieval of unsafe content from vision-language models such
as CLIP is an important step towards real-world integration. Current efforts
have relied on unlearning techniques that try to erase the model's knowledge of
unsafe concepts. While effective in reducing unwanted outputs, unlearning
limits the mo... | 2025-03-15T13:18:04Z | CVPR 2025 | null | null | null | null | null | null | null | null | null |
2,503.12167 | PLM: Efficient Peripheral Language Models Hardware-Co-Designed for
Ubiquitous Computing | ['Cheng Deng', 'Luoyang Sun', 'Jiwen Jiang', 'Yongcheng Zeng', 'Xinjian Wu', 'Wenxin Zhao', 'Qingfa Xiao', 'Jiachuan Wang', 'Haoyang Li', 'Lei Chen', 'Lionel M. Ni', 'Haifeng Zhang', 'Jun Wang'] | ['cs.CL', 'I.2.7'] | While scaling laws have been continuously validated in large language models
(LLMs) with increasing model parameters, the inherent tension between the
inference demands of LLMs and the limited resources of edge devices poses a
critical challenge to the development of edge intelligence. Recently, numerous
small language... | 2025-03-15T15:11:17Z | null | null | null | null | null | null | null | null | null | null |
2,503.12294 | The Lucie-7B LLM and the Lucie Training Dataset: Open resources for
multilingual language generation | ['Olivier Gouvert', 'Julie Hunter', 'Jérôme Louradour', 'Christophe Cerisara', 'Evan Dufraisse', 'Yaya Sy', 'Laura Rivière', 'Jean-Pierre Lorré', 'OpenLLM-France community'] | ['cs.CL', 'cs.AI'] | We present both the Lucie Training Dataset and the Lucie-7B foundation model.
The Lucie Training Dataset is a multilingual collection of textual corpora
centered around French and designed to offset anglo-centric biases found in
many datasets for large language model pretraining. Its French data is pulled
not only from... | 2025-03-15T23:20:45Z | null | null | null | The Lucie-7B LLM and the Lucie Training Dataset: Open resources for multilingual language generation | ['Olivier Gouvert', 'Julie Hunter', 'Jérôme Louradour', 'Christophe Cerisara', 'Evan Dufraisse', 'Yaya Sy', 'Laura Riviere', "Jean-Pierre Lorr'e", 'OpenLLM-France community'] | 2,025 | arXiv.org | 0 | 50 | ['Computer Science'] |
2,503.1244 | HKCanto-Eval: A Benchmark for Evaluating Cantonese Language
Understanding and Cultural Comprehension in LLMs | ['Tsz Chung Cheng', 'Chung Shing Cheng', 'Chaak Ming Lau', 'Eugene Tin-Ho Lam', 'Chun Yat Wong', 'Hoi On Yu', 'Cheuk Hei Chong'] | ['cs.CL'] | The ability of language models to comprehend and interact in diverse
linguistic and cultural landscapes is crucial. The Cantonese language used in
Hong Kong presents unique challenges for natural language processing due to its
rich cultural nuances and lack of dedicated evaluation datasets. The
HKCanto-Eval benchmark a... | 2025-03-16T10:26:24Z | null | null | null | HKCanto-Eval: A Benchmark for Evaluating Cantonese Language Understanding and Cultural Comprehension in LLMs | ['Tsz Chung Cheng', 'Chung Shing Cheng', 'Chaak-ming Lau', 'Eugene Tin-Ho Lam', 'Chun Yat Wong', 'Hoi On Yu', 'Cheuk Hei Chong'] | 2,025 | arXiv.org | 2 | 58 | ['Computer Science'] |
2,503.12446 | BREEN: Bridge Data-Efficient Encoder-Free Multimodal Learning with
Learnable Queries | ['Tianle Li', 'Yongming Rao', 'Winston Hu', 'Yu Cheng'] | ['cs.CV', 'cs.AI'] | Encoder-free multimodal large language models(MLLMs) eliminate the need for a
well-trained vision encoder by directly processing image tokens before the
language model. While this approach reduces computational overhead and model
complexity, it often requires large amounts of training data to effectively
capture the vi... | 2025-03-16T10:43:14Z | null | null | null | BREEN: Bridge Data-Efficient Encoder-Free Multimodal Learning with Learnable Queries | ['Tianle Li', 'Yongming Rao', 'Winston Hu', 'Yu Cheng'] | 2,025 | arXiv.org | 0 | 41 | ['Computer Science'] |
2,503.12507 | Segment Any-Quality Images with Generative Latent Space Enhancement | ['Guangqian Guo', 'Yong Guo', 'Xuehui Yu', 'Wenbo Li', 'Yaoxing Wang', 'Shan Gao'] | ['cs.CV'] | Despite their success, Segment Anything Models (SAMs) experience significant
performance drops on severely degraded, low-quality images, limiting their
effectiveness in real-world scenarios. To address this, we propose GleSAM,
which utilizes Generative Latent space Enhancement to boost robustness on
low-quality images,... | 2025-03-16T13:58:13Z | Accepted by CVPR2025 | null | null | null | null | null | null | null | null | null |
2,503.12524 | EXAONE Deep: Reasoning Enhanced Language Models | ['LG AI Research', 'Kyunghoon Bae', 'Eunbi Choi', 'Kibong Choi', 'Stanley Jungkyu Choi', 'Yemuk Choi', 'Seokhee Hong', 'Junwon Hwang', 'Hyojin Jeon', 'Kijeong Jeon', 'Gerrard Jeongwon Jo', 'Hyunjik Jo', 'Jiyeon Jung', 'Hyosang Kim', 'Joonkee Kim', 'Seonghwan Kim', 'Soyeon Kim', 'Sunkyoung Kim', 'Yireun Kim', 'Yongil Ki... | ['cs.CL', 'cs.AI'] | We present EXAONE Deep series, which exhibits superior capabilities in
various reasoning tasks, including math and coding benchmarks. We train our
models mainly on the reasoning-specialized dataset that incorporates long
streams of thought processes. Evaluation results show that our smaller models,
EXAONE Deep 2.4B and... | 2025-03-16T14:39:33Z | arXiv admin note: substantial text overlap with arXiv:2412.04862,
arXiv:2408.03541 | null | null | null | null | null | null | null | null | null |
2,503.12532 | STEVE: A Step Verification Pipeline for Computer-use Agent Training | ['Fanbin Lu', 'Zhisheng Zhong', 'Ziqin Wei', 'Shu Liu', 'Chi-Wing Fu', 'Jiaya Jia'] | ['cs.CV', 'cs.AI'] | Developing AI agents to autonomously manipulate graphical user interfaces is
a long challenging task. Recent advances in data scaling law inspire us to
train computer-use agents with a scaled instruction set, yet using behavior
cloning to train agents still requires immense high-quality trajectories. To
meet the scalab... | 2025-03-16T14:53:43Z | null | null | null | STEVE: A Step Verification Pipeline for Computer-use Agent Training | ['Fanbin Lu', 'Zhisheng Zhong', 'Ziqin Wei', 'Shu Liu', 'Chi-Wing Fu', 'Jiaya Jia'] | 2,025 | arXiv.org | 0 | 36 | ['Computer Science'] |
2,503.12553 | Niagara: Normal-Integrated Geometric Affine Field for Scene
Reconstruction from a Single View | ['Xianzu Wu', 'Zhenxin Ai', 'Harry Yang', 'Ser-Nam Lim', 'Jun Liu', 'Huan Wang'] | ['cs.GR', 'cs.CV'] | Recent advances in single-view 3D scene reconstruction have highlighted the
challenges in capturing fine geometric details and ensuring structural
consistency, particularly in high-fidelity outdoor scene modeling. This paper
presents Niagara, a new single-view 3D scene reconstruction framework that can
faithfully recon... | 2025-03-16T15:50:18Z | null | null | null | null | null | null | null | null | null | null |
2,503.12649 | FW-Merging: Scaling Model Merging with Frank-Wolfe Optimization | ['Hao Mark Chen', 'Shell Xu Hu', 'Wayne Luk', 'Timothy Hospedales', 'Hongxiang Fan'] | ['cs.LG', 'cs.AI'] | Model merging has emerged as a promising approach for multi-task learning
(MTL), offering a data-efficient alternative to conventional fine-tuning.
However, with the rapid development of the open-source AI ecosystem and the
increasing availability of fine-tuned foundation models, existing model merging
methods face two... | 2025-03-16T21:07:05Z | null | null | null | FW-Merging: Scaling Model Merging with Frank-Wolfe Optimization | ['Hao Chen', 'S. Hu', 'Wayne Luk', 'Timothy M. Hospedales', 'Hongxiang Fan'] | 2,025 | arXiv.org | 1 | 67 | ['Computer Science'] |
2,503.1272 | Towards Open-World Generation of Stereo Images and Unsupervised Matching | ['Feng Qiao', 'Zhexiao Xiong', 'Eric Xing', 'Nathan Jacobs'] | ['cs.CV'] | Stereo images are fundamental to numerous applications, including extended
reality (XR) devices, autonomous driving, and robotics. Unfortunately,
acquiring high-quality stereo images remains challenging due to the precise
calibration requirements of dual-camera setups and the complexity of obtaining
accurate, dense dis... | 2025-03-17T01:19:28Z | Accepted by ICCV 2025 | null | null | GenStereo: Towards Open-World Generation of Stereo Images and Unsupervised Matching | ['Feng Qiao', 'Feng Qiao', 'Zhexiao Xiong', 'Eric Xing', 'Nathan Jacobs'] | 2,025 | arXiv.org | 1 | 65 | ['Computer Science'] |
2,503.12769 | ViSpeak: Visual Instruction Feedback in Streaming Videos | ['Shenghao Fu', 'Qize Yang', 'Yuan-Ming Li', 'Yi-Xing Peng', 'Kun-Yu Lin', 'Xihan Wei', 'Jian-Fang Hu', 'Xiaohua Xie', 'Wei-Shi Zheng'] | ['cs.CV'] | Recent advances in Large Multi-modal Models (LMMs) are primarily focused on
offline video understanding. Instead, streaming video understanding poses great
challenges to recent models due to its time-sensitive, omni-modal and
interactive characteristics. In this work, we aim to extend the streaming video
understanding ... | 2025-03-17T03:05:31Z | null | null | null | ViSpeak: Visual Instruction Feedback in Streaming Videos | ['Shenghao Fu', 'Qize Yang', 'Yuan-Ming Li', 'Yi-Xing Peng', 'Kun-Yu Lin', 'Xihan Wei', 'Jianfang Hu', 'Xiaohua Xie', 'Wei-Shi Zheng'] | 2,025 | arXiv.org | 1 | 69 | ['Computer Science'] |
2,503.12797 | DeepPerception: Advancing R1-like Cognitive Visual Perception in MLLMs
for Knowledge-Intensive Visual Grounding | ['Xinyu Ma', 'Ziyang Ding', 'Zhicong Luo', 'Chi Chen', 'Zonghao Guo', 'Derek F. Wong', 'Xiaoyi Feng', 'Maosong Sun'] | ['cs.CV', 'cs.AI', 'cs.CL'] | Human experts excel at fine-grained visual discrimination by leveraging
domain knowledge to refine perceptual features, a capability that remains
underdeveloped in current Multimodal Large Language Models (MLLMs). Despite
possessing vast expert-level knowledge, MLLMs struggle to integrate reasoning
into visual percepti... | 2025-03-17T04:06:34Z | null | null | null | null | null | null | null | null | null | null |
2,503.12937 | R1-VL: Learning to Reason with Multimodal Large Language Models via
Step-wise Group Relative Policy Optimization | ['Jingyi Zhang', 'Jiaxing Huang', 'Huanjin Yao', 'Shunyu Liu', 'Xikun Zhang', 'Shijian Lu', 'Dacheng Tao'] | ['cs.AI', 'cs.CL', 'cs.CV', 'cs.LG'] | Recent studies generally enhance MLLMs' reasoning capabilities via supervised
fine-tuning on high-quality chain-of-thought reasoning data, which often leads
models to merely imitate successful reasoning paths without understanding what
the wrong reasoning paths are. In this work, we aim to enhance the MLLMs'
reasoning ... | 2025-03-17T08:51:44Z | null | null | null | null | null | null | null | null | null | null |
2,503.12963 | Unlock Pose Diversity: Accurate and Efficient Implicit Keypoint-based
Spatiotemporal Diffusion for Audio-driven Talking Portrait | ['Chaolong Yang', 'Kai Yao', 'Yuyao Yan', 'Chenru Jiang', 'Weiguang Zhao', 'Jie Sun', 'Guangliang Cheng', 'Yifei Zhang', 'Bin Dong', 'Kaizhu Huang'] | ['cs.CV'] | Audio-driven single-image talking portrait generation plays a crucial role in
virtual reality, digital human creation, and filmmaking. Existing approaches
are generally categorized into keypoint-based and image-based methods.
Keypoint-based methods effectively preserve character identity but struggle to
capture fine fa... | 2025-03-17T09:18:31Z | null | null | null | Unlock Pose Diversity: Accurate and Efficient Implicit Keypoint-based Spatiotemporal Diffusion for Audio-driven Talking Portrait | ['Chaolong Yang', 'Kai Yao', 'Yuyao Yan', 'Chenru Jiang', 'Weiguang Zhao', 'Jie Sun', 'Guangliang Cheng', 'Yifei Zhang', 'Bin Dong', 'Kaizhu Huang'] | 2,025 | arXiv.org | 0 | 39 | ['Computer Science'] |
2,503.13026 | HiMTok: Learning Hierarchical Mask Tokens for Image Segmentation with
Large Multimodal Model | ['Tao Wang', 'Changxu Cheng', 'Lingfeng Wang', 'Senda Chen', 'Wuyue Zhao'] | ['cs.CV'] | The remarkable performance of large multimodal models (LMMs) has attracted
significant interest from the image segmentation community. To align with the
next-token-prediction paradigm, current LMM-driven segmentation methods either
use object boundary points to represent masks or introduce special segmentation
tokens, ... | 2025-03-17T10:29:08Z | Accepted by ICCV 2025; the code is at
https://github.com/yayafengzi/LMM-HiMTok | null | null | null | null | null | null | null | null | null |
2,503.1306 | Historic Scripts to Modern Vision: A Novel Dataset and A VLM Framework
for Transliteration of Modi Script to Devanagari | ['Harshal Kausadikar', 'Tanvi Kale', 'Onkar Susladkar', 'Sparsh Mittal'] | ['cs.CV'] | In medieval India, the Marathi language was written using the Modi script.
The texts written in Modi script include extensive knowledge about medieval
sciences, medicines, land records and authentic evidence about Indian history.
Around 40 million documents are in poor condition and have not yet been
transliterated. Fu... | 2025-03-17T11:07:29Z | Under submission at a conference | null | null | Historic Scripts to Modern Vision: A Novel Dataset and A VLM Framework for Transliteration of Modi Script to Devanagari | ['Harshal Kausadikar', 'Tanvi Kale', 'Onkar Susladkar', 'Sparsh Mittal'] | 2,025 | arXiv.org | 0 | 36 | ['Computer Science'] |
2,503.1326 | Don't Judge Before You CLIP: A Unified Approach for Perceptual Tasks | ['Amit Zalcher', 'Navve Wasserman', 'Roman Beliy', 'Oliver Heinimann', 'Michal Irani'] | ['cs.CV'] | Visual perceptual tasks aim to predict human judgment of images (e.g.,
emotions invoked by images, image quality assessment). Unlike objective tasks
such as object/scene recognition, perceptual tasks rely on subjective human
assessments, making its data-labeling difficult. The scarcity of such
human-annotated data resu... | 2025-03-17T15:15:31Z | null | null | null | Don't Judge Before You CLIP: A Unified Approach for Perceptual Tasks | ['Amit Zalcher', 'Navve Wasserman', 'Roman Beliy', 'Oliver Heinimann', 'Michal Irani'] | 2,025 | arXiv.org | 0 | 58 | ['Computer Science'] |
2,503.13265 | FlexWorld: Progressively Expanding 3D Scenes for Flexiable-View
Synthesis | ['Luxi Chen', 'Zihan Zhou', 'Min Zhao', 'Yikai Wang', 'Ge Zhang', 'Wenhao Huang', 'Hao Sun', 'Ji-Rong Wen', 'Chongxuan Li'] | ['cs.CV'] | Generating flexible-view 3D scenes, including 360{\deg} rotation and zooming,
from single images is challenging due to a lack of 3D data. To this end, we
introduce FlexWorld, a novel framework consisting of two key components: (1) a
strong video-to-video (V2V) diffusion model to generate high-quality novel view
images ... | 2025-03-17T15:18:38Z | null | null | null | FlexWorld: Progressively Expanding 3D Scenes for Flexiable-View Synthesis | ['Luxi Chen', 'Zihan Zhou', 'Min Zhao', 'Yikai Wang', 'Ge Zhang', 'Wenhao Huang', 'Hao Sun', 'Ji-Rong Wen', 'Chongxuan Li'] | 2,025 | arXiv.org | 4 | 72 | ['Computer Science'] |
2,503.13327 | Edit Transfer: Learning Image Editing via Vision In-Context Relations | ['Lan Chen', 'Qi Mao', 'Yuchao Gu', 'Mike Zheng Shou'] | ['cs.CV'] | We introduce a new setting, Edit Transfer, where a model learns a
transformation from just a single source-target example and applies it to a new
query image. While text-based methods excel at semantic manipulations through
textual prompts, they often struggle with precise geometric details (e.g.,
poses and viewpoint c... | 2025-03-17T16:04:44Z | null | null | null | null | null | null | null | null | null | null |
2,503.1336 | Mitigating Visual Forgetting via Take-along Visual Conditioning for
Multi-modal Long CoT Reasoning | ['Hai-Long Sun', 'Zhun Sun', 'Houwen Peng', 'Han-Jia Ye'] | ['cs.CV', 'cs.AI', 'cs.LG'] | Recent advancements in Large Language Models (LLMs) have demonstrated
enhanced reasoning capabilities, evolving from Chain-of-Thought (CoT) prompting
to advanced, product-oriented solutions like OpenAI o1. During our
re-implementation of this model, we noticed that in multimodal tasks requiring
visual input (e.g., geom... | 2025-03-17T16:45:12Z | Accepted to ACL 2025. The project page is available at
https://sun-hailong.github.io/projects/TVC | null | null | Mitigating Visual Forgetting via Take-along Visual Conditioning for Multi-modal Long CoT Reasoning | ['Hai-Long Sun', 'Zhun Sun', 'Houwen Peng', 'Han-Jia Ye'] | 2,025 | arXiv.org | 6 | 49 | ['Computer Science'] |
2,503.13383 | Cream of the Crop: Harvesting Rich, Scalable and Transferable
Multi-Modal Data for Instruction Fine-Tuning | ['Mengyao Lyu', 'Yan Li', 'Huasong Zhong', 'Wenhao Yang', 'Hui Chen', 'Jungong Han', 'Guiguang Ding', 'Zhenheng Yang'] | ['cs.CV', 'cs.AI', 'cs.CL', 'cs.LG'] | The hypothesis that pretrained large language models (LLMs) necessitate only
minimal supervision during the fine-tuning (SFT) stage (Zhou et al., 2024) has
been substantiated by recent advancements in data curation and selection
research. However, their stability and generalizability are compromised due to
the vulnerab... | 2025-03-17T17:11:22Z | update comparison with sota and analysis | null | null | null | null | null | null | null | null | null |
2,503.13423 | SuperBPE: Space Travel for Language Models | ['Alisa Liu', 'Jonathan Hayase', 'Valentin Hofmann', 'Sewoong Oh', 'Noah A. Smith', 'Yejin Choi'] | ['cs.CL', 'cs.LG'] | The assumption across nearly all language model (LM) tokenization schemes is
that tokens should be subwords, i.e., contained within word boundaries. While
providing a seemingly reasonable inductive bias, is this common practice
limiting the potential of modern LMs? Whitespace is not a reliable delimiter of
meaning, as ... | 2025-03-17T17:53:23Z | updated related work | null | null | null | null | null | null | null | null | null |
2,503.13434 | BlobCtrl: A Unified and Flexible Framework for Element-level Image
Generation and Editing | ['Yaowei Li', 'Lingen Li', 'Zhaoyang Zhang', 'Xiaoyu Li', 'Guangzhi Wang', 'Hongxiang Li', 'Xiaodong Cun', 'Ying Shan', 'Yuexian Zou'] | ['cs.CV', 'cs.AI', 'cs.MM'] | Element-level visual manipulation is essential in digital content creation,
but current diffusion-based methods lack the precision and flexibility of
traditional tools. In this work, we introduce BlobCtrl, a framework that
unifies element-level generation and editing using a probabilistic blob-based
representation. By ... | 2025-03-17T17:58:05Z | Project Webpage: https://liyaowei-stu.github.io/project/BlobCtrl/ | null | null | BlobCtrl: A Unified and Flexible Framework for Element-level Image Generation and Editing | ['Yaowei Li', 'Lingen Li', 'Zhaoyang Zhang', 'Xiaoyu Li', 'Guangzhi Wang', 'Hongxiang Li', 'Xiaodong Cun', 'Ying Shan', 'Yuexian Zou'] | 2,025 | arXiv.org | 2 | 49 | ['Computer Science'] |
2,503.13439 | Amodal3R: Amodal 3D Reconstruction from Occluded 2D Images | ['Tianhao Wu', 'Chuanxia Zheng', 'Frank Guan', 'Andrea Vedaldi', 'Tat-Jen Cham'] | ['cs.CV'] | Most image-based 3D object reconstructors assume that objects are fully
visible, ignoring occlusions that commonly occur in real-world scenarios. In
this paper, we introduce Amodal3R, a conditional 3D generative model designed
to reconstruct 3D objects from partial observations. We start from a
"foundation" 3D generati... | 2025-03-17T17:59:01Z | Project Page: https://sm0kywu.github.io/Amodal3R/ | null | null | null | null | null | null | null | null | null |
2,503.1344 | MaTVLM: Hybrid Mamba-Transformer for Efficient Vision-Language Modeling | ['Yingyue Li', 'Bencheng Liao', 'Wenyu Liu', 'Xinggang Wang'] | ['cs.CV'] | With the advancement of RNN models with linear complexity, the quadratic
complexity challenge of transformers has the potential to be overcome. Notably,
the emerging Mamba-2 has demonstrated competitive performance, bridging the gap
between RNN models and transformers. However, due to sequential processing and
vanishin... | 2025-03-17T17:59:01Z | Code and model are available at http://github.com/hustvl/MaTVLM | null | null | null | null | null | null | null | null | null |
2,503.13444 | VideoMind: A Chain-of-LoRA Agent for Long Video Reasoning | ['Ye Liu', 'Kevin Qinghong Lin', 'Chang Wen Chen', 'Mike Zheng Shou'] | ['cs.CV', 'cs.AI'] | Videos, with their unique temporal dimension, demand precise grounded
understanding, where answers are directly linked to visual, interpretable
evidence. Despite significant breakthroughs in reasoning capabilities within
Large Language Models, multi-modal reasoning - especially for videos - remains
unexplored. In this ... | 2025-03-17T17:59:33Z | Project Page: https://videomind.github.io/ | null | null | VideoMind: A Chain-of-LoRA Agent for Long Video Reasoning | ['Ye Liu', 'Kevin Qinghong Lin', 'Chang Wen Chen', 'Mike Zheng Shou'] | 2,025 | arXiv.org | 6 | 103 | ['Computer Science'] |
2,503.13661 | Pensez: Less Data, Better Reasoning -- Rethinking French LLM | ['Huy Hoang Ha'] | ['cs.CL'] | Large language models (LLMs) have demonstrated remarkable capabilities in
various natural language processing tasks. However, achieving strong
performance in specialized domains like mathematical reasoning and non-English
languages often requires extensive training on massive datasets. This paper
investigates a contras... | 2025-03-17T19:09:11Z | null | null | null | null | null | null | null | null | null | null |
2,503.13939 | Med-R1: Reinforcement Learning for Generalizable Medical Reasoning in
Vision-Language Models | ['Yuxiang Lai', 'Jike Zhong', 'Ming Li', 'Shitian Zhao', 'Xiaofeng Yang'] | ['cs.CV'] | Vision-language models (VLMs) have achieved impressive progress in natural
image reasoning, yet their potential in medical imaging remains underexplored.
Medical vision-language tasks demand precise understanding and clinically
coherent answers, which are difficult to achieve due to the complexity of
medical data and t... | 2025-03-18T06:12:38Z | null | null | null | Med-R1: Reinforcement Learning for Generalizable Medical Reasoning in Vision-Language Models | ['Yuxiang Lai', 'Jike Zhong', 'Ming Li', 'Shitian Zhao', 'Xiaofen Yang'] | 2,025 | arXiv.org | 31 | 37 | ['Computer Science'] |
2,503.13988 | Empowering Smaller Models: Tuning LLaMA and Gemma with Chain-of-Thought
for Ukrainian Exam Tasks | ['Mykyta Syromiatnikov', 'Victoria Ruvinskaya', 'Nataliia Komleva'] | ['cs.CL', 'cs.AI'] | Leading large language models have demonstrated impressive capabilities in
reasoning-intensive tasks, such as standardized educational testing. However,
they often require extensive training in low-resource settings with
inaccessible infrastructure. Small or compact models, though more efficient,
frequently lack suffic... | 2025-03-18T07:44:49Z | 12 pages, 6 tables, 2 figures | null | null | null | null | null | null | null | null | null |
2,503.14002 | MeshFleet: Filtered and Annotated 3D Vehicle Dataset for Domain Specific
Generative Modeling | ['Damian Boborzi', 'Phillip Mueller', 'Jonas Emrich', 'Dominik Schmid', 'Sebastian Mueller', 'Lars Mikelsons'] | ['cs.CV', 'cs.AI', 'cs.LG'] | Generative models have recently made remarkable progress in the field of 3D
objects. However, their practical application in fields like engineering
remains limited since they fail to deliver the accuracy, quality, and
controllability needed for domain-specific tasks. Fine-tuning large generative
models is a promising ... | 2025-03-18T08:09:24Z | null | null | null | null | null | null | null | null | null | null |
2,503.14136 | CARE: A QLoRA-Fine Tuned Multi-Domain Chatbot With Fast Learning On
Minimal Hardware | ['Ankit Dutta', 'Nabarup Ghosh', 'Ankush Chatterjee'] | ['cs.CL', 'cs.AI'] | Large Language models have demonstrated excellent domain-specific
question-answering capabilities when finetuned with a particular dataset of
that specific domain. However, fine-tuning the models requires a significant
amount of training time and a considerable amount of hardware. In this work, we
propose CARE (Custome... | 2025-03-18T10:58:10Z | null | null | null | null | null | null | null | null | null | null |
2,503.14173 | NERCat: Fine-Tuning for Enhanced Named Entity Recognition in Catalan | ['Guillem Cadevall Ferreres', 'Marc Serrano Sanz', 'Marc Bardeli Gámez', 'Pol Gerdt Basullas', 'Francesc Tarres Ruiz', 'Raul Quijada Ferrero'] | ['cs.CL', '68T50', 'I.2.7'] | Named Entity Recognition (NER) is a critical component of Natural Language
Processing (NLP) for extracting structured information from unstructured text.
However, for low-resource languages like Catalan, the performance of NER
systems often suffers due to the lack of high-quality annotated datasets. This
paper introduc... | 2025-03-18T11:44:19Z | 7 pages, 1 table | null | null | NERCat: Fine-Tuning for Enhanced Named Entity Recognition in Catalan | ['Guillem Cadevall Ferreres', 'Marc Serrano Sanz', "Marc Bardeli G'amez", 'Pol Gerdt Basullas', 'Francesc Tarres-Ruiz', 'Raul Quijada Ferrero'] | 2,025 | arXiv.org | 0 | 4 | ['Computer Science'] |
2,503.14189 | Towards Harmless Multimodal Assistants with Blind Preference
Optimization | ['Yongqi Li', 'Lu Yang', 'Jian Wang', 'Runyang You', 'Wenjie Li', 'Liqiang Nie'] | ['cs.CL', 'cs.CV'] | Multimodal Large Language Models (MLLMs) have demonstrated impressive
capabilities in multimodal understanding, reasoning, and interaction. Given the
extensive applications of MLLMs, the associated safety issues have become
increasingly critical. Due to the effectiveness of preference optimization in
aligning MLLMs wit... | 2025-03-18T12:02:38Z | null | null | null | null | null | null | null | null | null | null |
2,503.14325 | LeanVAE: An Ultra-Efficient Reconstruction VAE for Video Diffusion
Models | ['Yu Cheng', 'Fajie Yuan'] | ['cs.CV', 'eess.IV'] | Recent advances in Latent Video Diffusion Models (LVDMs) have revolutionized
video generation by leveraging Video Variational Autoencoders (Video VAEs) to
compress intricate video data into a compact latent space. However, as LVDM
training scales, the computational overhead of Video VAEs becomes a critical
bottleneck, ... | 2025-03-18T14:58:59Z | null | null | null | null | null | null | null | null | null | null |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.