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2,412.04318 | The Hyperfitting Phenomenon: Sharpening and Stabilizing LLMs for
Open-Ended Text Generation | ['Fredrik Carlsson', 'Fangyu Liu', 'Daniel Ward', 'Murathan Kurfali', 'Joakim Nivre'] | ['cs.CL', 'cs.AI'] | This paper introduces the counter-intuitive generalization results of
overfitting pre-trained large language models (LLMs) on very small datasets. In
the setting of open-ended text generation, it is well-documented that LLMs tend
to generate repetitive and dull sequences, a phenomenon that is especially
apparent when g... | 2024-12-05T16:34:20Z | Under review at ICLR | null | null | The Hyperfitting Phenomenon: Sharpening and Stabilizing LLMs for Open-Ended Text Generation | ['Fredrik Carlsson', 'Fangyu Liu', 'Daniel Ward', 'Murathan Kurfali', 'Joakim Nivre'] | 2,024 | International Conference on Learning Representations | 3 | 27 | ['Computer Science'] |
2,412.04332 | Liquid: Language Models are Scalable and Unified Multi-modal Generators | ['Junfeng Wu', 'Yi Jiang', 'Chuofan Ma', 'Yuliang Liu', 'Hengshuang Zhao', 'Zehuan Yuan', 'Song Bai', 'Xiang Bai'] | ['cs.CV'] | We present Liquid, an auto-regressive generation paradigm that seamlessly
integrates visual comprehension and generation by tokenizing images into
discrete codes and learning these code embeddings alongside text tokens within
a shared feature space for both vision and language. Unlike previous multimodal
large language... | 2024-12-05T16:48:16Z | Technical report. Project page:
https://foundationvision.github.io/Liquid/ | null | null | Liquid: Language Models are Scalable and Unified Multi-modal Generators | ['Junfeng Wu', 'Yi Jiang', 'Chuofan Ma', 'Yuliang Liu', 'Hengshuang Zhao', 'Zehuan Yuan', 'Song Bai', 'Xiang Bai'] | 2,024 | null | 9 | 83 | ['Computer Science'] |
2,412.04418 | ACE2-SOM: Coupling an ML atmospheric emulator to a slab ocean and
learning the sensitivity of climate to changed CO$_2$ | ['Spencer K. Clark', 'Oliver Watt-Meyer', 'Anna Kwa', 'Jeremy McGibbon', 'Brian Henn', 'W. Andre Perkins', 'Elynn Wu', 'Lucas M. Harris', 'Christopher S. Bretherton'] | ['physics.ao-ph'] | While autoregressive machine-learning-based emulators have been trained to
produce stable and accurate rollouts in the climate of the present-day and
recent past, none so far have been trained to emulate the sensitivity of
climate to substantial changes in CO$_2$ or other greenhouse gases. As an
initial step we couple ... | 2024-12-05T18:44:33Z | 31 pages, 13 figures | null | null | null | null | null | null | null | null | null |
2,412.04431 | Infinity: Scaling Bitwise AutoRegressive Modeling for High-Resolution
Image Synthesis | ['Jian Han', 'Jinlai Liu', 'Yi Jiang', 'Bin Yan', 'Yuqi Zhang', 'Zehuan Yuan', 'Bingyue Peng', 'Xiaobing Liu'] | ['cs.CV'] | We present Infinity, a Bitwise Visual AutoRegressive Modeling capable of
generating high-resolution, photorealistic images following language
instruction. Infinity redefines visual autoregressive model under a bitwise
token prediction framework with an infinite-vocabulary tokenizer & classifier
and bitwise self-correct... | 2024-12-05T18:53:02Z | 17 pages, 14 figures | null | null | null | null | null | null | null | null | null |
2,412.04432 | Divot: Diffusion Powers Video Tokenizer for Comprehension and Generation | ['Yuying Ge', 'Yizhuo Li', 'Yixiao Ge', 'Ying Shan'] | ['cs.CV'] | In recent years, there has been a significant surge of interest in unifying
image comprehension and generation within Large Language Models (LLMs). This
growing interest has prompted us to explore extending this unification to
videos. The core challenge lies in developing a versatile video tokenizer that
captures both ... | 2024-12-05T18:53:04Z | Project released at: https://github.com/TencentARC/Divot | null | null | Divot: Diffusion Powers Video Tokenizer for Comprehension and Generation | ['Yuying Ge', 'Yizhuo Li', 'Yixiao Ge', 'Ying Shan'] | 2,024 | arXiv.org | 3 | 0 | ['Computer Science'] |
2,412.04445 | Moto: Latent Motion Token as the Bridging Language for Learning Robot
Manipulation from Videos | ['Yi Chen', 'Yuying Ge', 'Weiliang Tang', 'Yizhuo Li', 'Yixiao Ge', 'Mingyu Ding', 'Ying Shan', 'Xihui Liu'] | ['cs.RO', 'cs.AI', 'cs.CL', 'cs.CV', 'cs.LG'] | Recent developments in Large Language Models pre-trained on extensive corpora
have shown significant success in various natural language processing tasks
with minimal fine-tuning. This success offers new promise for robotics, which
has long been constrained by the high cost of action-labeled data. We ask:
given the abu... | 2024-12-05T18:57:04Z | Project released at: https://chenyi99.github.io/moto/ Code released
at: https://github.com/TencentARC/Moto Update: Added content related to
real-world robot experiments and learning from human videos; Modified author
information | null | null | Moto: Latent Motion Token as the Bridging Language for Learning Robot Manipulation from Videos | ['Yi Chen', 'Yuying Ge', 'Weiliang Tang', 'Yizhuo Li', 'Yixiao Ge', 'Mingyu Ding', 'Ying Shan', 'Xihui Liu'] | 2,024 | null | 3 | 59 | ['Computer Science'] |
2,412.04446 | DiCoDe: Diffusion-Compressed Deep Tokens for Autoregressive Video
Generation with Language Models | ['Yizhuo Li', 'Yuying Ge', 'Yixiao Ge', 'Ping Luo', 'Ying Shan'] | ['cs.CV'] | Videos are inherently temporal sequences by their very nature. In this work,
we explore the potential of modeling videos in a chronological and scalable
manner with autoregressive (AR) language models, inspired by their success in
natural language processing. We introduce DiCoDe, a novel approach that
leverages Diffusi... | 2024-12-05T18:57:06Z | Project Page: https://liyz15.github.io/DiCoDe | null | null | null | null | null | null | null | null | null |
2,412.04448 | MEMO: Memory-Guided Diffusion for Expressive Talking Video Generation | ['Longtao Zheng', 'Yifan Zhang', 'Hanzhong Guo', 'Jiachun Pan', 'Zhenxiong Tan', 'Jiahao Lu', 'Chuanxin Tang', 'Bo An', 'Shuicheng Yan'] | ['cs.CV'] | Recent advances in video diffusion models have unlocked new potential for
realistic audio-driven talking video generation. However, achieving seamless
audio-lip synchronization, maintaining long-term identity consistency, and
producing natural, audio-aligned expressions in generated talking videos remain
significant ch... | 2024-12-05T18:57:26Z | Project Page: https://memoavatar.github.io | null | null | null | null | null | null | null | null | null |
2,412.04449 | p-MoD: Building Mixture-of-Depths MLLMs via Progressive Ratio Decay | ['Jun Zhang', 'Desen Meng', 'Ji Qi', 'Zhenpeng Huang', 'Tao Wu', 'Limin Wang'] | ['cs.CV', 'cs.CL'] | Despite the remarkable performance of multimodal large language models
(MLLMs) across diverse tasks, the substantial training and inference costs
impede their advancement. The majority of computation stems from the
overwhelming volume of vision tokens processed by the transformer decoder. In
this paper, we propose to b... | 2024-12-05T18:58:03Z | Technical Report; Code released at https://github.com/MCG-NJU/p-MoD | null | null | p-MoD: Building Mixture-of-Depths MLLMs via Progressive Ratio Decay | ['Jun Zhang', 'Desen Meng', 'Ji Qi', 'Zhenpeng Huang', 'Tao Wu', 'Limin Wang'] | 2,024 | arXiv.org | 4 | 0 | ['Computer Science'] |
2,412.04455 | Code-as-Monitor: Constraint-aware Visual Programming for Reactive and
Proactive Robotic Failure Detection | ['Enshen Zhou', 'Qi Su', 'Cheng Chi', 'Zhizheng Zhang', 'Zhongyuan Wang', 'Tiejun Huang', 'Lu Sheng', 'He Wang'] | ['cs.RO', 'cs.AI', 'cs.CV', 'cs.LG'] | Automatic detection and prevention of open-set failures are crucial in
closed-loop robotic systems. Recent studies often struggle to simultaneously
identify unexpected failures reactively after they occur and prevent
foreseeable ones proactively. To this end, we propose Code-as-Monitor (CaM), a
novel paradigm leveragin... | 2024-12-05T18:58:27Z | Accepted by CVPR 2025. Project page:
https://zhoues.github.io/Code-as-Monitor/ | null | null | Code-as-Monitor: Constraint-aware Visual Programming for Reactive and Proactive Robotic Failure Detection | ['Enshen Zhou', 'Qi Su', 'Cheng Chi', 'Zhizheng Zhang', 'Zhongyuan Wang', 'Tiejun Huang', 'Lu Sheng', 'He Wang'] | 2,024 | Computer Vision and Pattern Recognition | 8 | 78 | ['Computer Science'] |
2,412.04468 | NVILA: Efficient Frontier Visual Language Models | ['Zhijian Liu', 'Ligeng Zhu', 'Baifeng Shi', 'Zhuoyang Zhang', 'Yuming Lou', 'Shang Yang', 'Haocheng Xi', 'Shiyi Cao', 'Yuxian Gu', 'Dacheng Li', 'Xiuyu Li', 'Yunhao Fang', 'Yukang Chen', 'Cheng-Yu Hsieh', 'De-An Huang', 'An-Chieh Cheng', 'Vishwesh Nath', 'Jinyi Hu', 'Sifei Liu', 'Ranjay Krishna', 'Daguang Xu', 'Xiaolo... | ['cs.CV'] | Visual language models (VLMs) have made significant advances in accuracy in
recent years. However, their efficiency has received much less attention. This
paper introduces NVILA, a family of open VLMs designed to optimize both
efficiency and accuracy. Building on top of VILA, we improve its model
architecture by first ... | 2024-12-05T18:59:55Z | null | null | null | null | null | null | null | null | null | null |
2,412.04506 | Arctic-Embed 2.0: Multilingual Retrieval Without Compromise | ['Puxuan Yu', 'Luke Merrick', 'Gaurav Nuti', 'Daniel Campos'] | ['cs.CL', 'cs.IR', 'cs.LG'] | This paper presents the training methodology of Arctic-Embed 2.0, a set of
open-source text embedding models built for accurate and efficient multilingual
retrieval. While prior works have suffered from degraded English retrieval
quality, Arctic-Embed 2.0 delivers competitive retrieval quality on
multilingual and Engli... | 2024-12-03T22:59:36Z | 10 pages, 5 figures, 3 tables | null | null | Arctic-Embed 2.0: Multilingual Retrieval Without Compromise | ['Puxuan Yu', 'Luke Merrick', 'Gaurav Nuti', 'Daniel Campos'] | 2,024 | arXiv.org | 15 | 0 | ['Computer Science'] |
2,412.04533 | Mask-Adapter: The Devil is in the Masks for Open-Vocabulary Segmentation | ['Yongkang Li', 'Tianheng Cheng', 'Bin Feng', 'Wenyu Liu', 'Xinggang Wang'] | ['cs.CV'] | Recent open-vocabulary segmentation methods adopt mask generators to predict
segmentation masks and leverage pre-trained vision-language models, e.g., CLIP,
to classify these masks via mask pooling. Although these approaches show
promising results, it is counterintuitive that accurate masks often fail to
yield accurate... | 2024-12-05T17:42:37Z | Accepted by CVPR 2025; Code & models:
https://github.com/hustvl/MaskAdapter | null | null | null | null | null | null | null | null | null |
2,412.04814 | LiFT: Leveraging Human Feedback for Text-to-Video Model Alignment | ['Yibin Wang', 'Zhiyu Tan', 'Junyan Wang', 'Xiaomeng Yang', 'Cheng Jin', 'Hao Li'] | ['cs.CV'] | Recent advances in text-to-video (T2V) generative models have shown
impressive capabilities. However, these models are still inadequate in aligning
synthesized videos with human preferences (e.g., accurately reflecting text
descriptions), which is particularly difficult to address, as human preferences
are subjective a... | 2024-12-06T07:16:14Z | Project page: https://codegoat24.github.io/LiFT | null | null | null | null | null | null | null | null | null |
2,412.04862 | EXAONE 3.5: Series of Large Language Models for Real-world Use Cases | ['LG AI Research', 'Soyoung An', 'Kyunghoon Bae', 'Eunbi Choi', 'Kibong Choi', 'Stanley Jungkyu Choi', 'Seokhee Hong', 'Junwon Hwang', 'Hyojin Jeon', 'Gerrard Jeongwon Jo', 'Hyunjik Jo', 'Jiyeon Jung', 'Yountae Jung', 'Hyosang Kim', 'Joonkee Kim', 'Seonghwan Kim', 'Soyeon Kim', 'Sunkyoung Kim', 'Yireun Kim', 'Yongil Ki... | ['cs.CL'] | This technical report introduces the EXAONE 3.5 instruction-tuned language
models, developed and released by LG AI Research. The EXAONE 3.5 language
models are offered in three configurations: 32B, 7.8B, and 2.4B. These models
feature several standout capabilities: 1) exceptional instruction following
capabilities in r... | 2024-12-06T08:53:46Z | arXiv admin note: text overlap with arXiv:2408.03541 | null | null | EXAONE 3.5: Series of Large Language Models for Real-world Use Cases | ['LG AI Research', 'Soyoung An', 'Kyunghoon Bae', 'Eunbi Choi', 'Kibong Choi', 'Stanley Jungkyu Choi', 'Seokhee Hong', 'Junwon Hwang', 'Hyojin Jeon', 'Gerrard Jeongwon Jo', 'Hyunjik Jo', 'Jiyeon Jung', 'Yountae Jung', 'Hyosang Kim', 'Joonkee Kim', 'Seonghwan Kim', 'Soyeon Kim', 'SunKyoung Kim', 'Yireun Kim', 'Yongil Ki... | 2,024 | arXiv.org | 16 | 0 | ['Computer Science'] |
2,412.04871 | Building a Family of Data Augmentation Models for Low-cost LLM
Fine-tuning on the Cloud | ['Yuanhao Yue', 'Chengyu Wang', 'Jun Huang', 'Peng Wang'] | ['cs.CL'] | Specializing LLMs in various domain-specific tasks has emerged as a critical
step towards achieving high performance. However, the construction and
annotation of datasets in specific domains are always very costly. Apart from
using superior and expensive closed-source LLM APIs to construct datasets, some
open-source mo... | 2024-12-06T09:04:12Z | coling 2025 industry track | null | null | null | null | null | null | null | null | null |
2,412.0488 | MozzaVID: Mozzarella Volumetric Image Dataset | ['Pawel Tomasz Pieta', 'Peter Winkel Rasmussen', 'Anders Bjorholm Dahl', 'Jeppe Revall Frisvad', 'Siavash Arjomand Bigdeli', 'Carsten Gundlach', 'Anders Nymark Christensen'] | ['cs.CV', 'eess.IV'] | Influenced by the complexity of volumetric imaging, there is a shortage of
established datasets useful for benchmarking volumetric deep-learning models.
As a consequence, new and existing models are not easily comparable, limiting
the development of architectures optimized specifically for volumetric data. To
counterac... | 2024-12-06T09:23:31Z | null | null | null | null | null | null | null | null | null | null |
2,412.04905 | DEMO: Reframing Dialogue Interaction with Fine-grained Element Modeling | ['Minzheng Wang', 'Xinghua Zhang', 'Kun Chen', 'Nan Xu', 'Haiyang Yu', 'Fei Huang', 'Wenji Mao', 'Yongbin Li'] | ['cs.CL', 'cs.AI', 'cs.LG'] | Large language models (LLMs) enabled dialogue systems have become one of the
central modes in human-machine interaction, which bring about vast amounts of
conversation logs and increasing demand for dialogue generation. The dialogue's
life-cycle spans from $\textit{Prelude}$ through $\textit{Interlocution}$ to
$\textit... | 2024-12-06T10:01:38Z | ACL 2025 Findings. We release the code and data at
https://github.com/MozerWang/DEMO | null | null | null | null | null | null | null | null | null |
2,412.05237 | MAmmoTH-VL: Eliciting Multimodal Reasoning with Instruction Tuning at
Scale | ['Jarvis Guo', 'Tuney Zheng', 'Yuelin Bai', 'Bo Li', 'Yubo Wang', 'King Zhu', 'Yizhi Li', 'Graham Neubig', 'Wenhu Chen', 'Xiang Yue'] | ['cs.CL', 'cs.CV'] | Open-source multimodal large language models (MLLMs) have shown significant
potential in a broad range of multimodal tasks. However, their reasoning
capabilities remain constrained by existing instruction-tuning datasets, which
were predominately repurposed from academic datasets such as VQA, AI2D, and
ChartQA. These d... | 2024-12-06T18:14:24Z | ACL 2025 Main | null | null | null | null | null | null | null | null | null |
2,412.0527 | APOLLO: SGD-like Memory, AdamW-level Performance | ['Hanqing Zhu', 'Zhenyu Zhang', 'Wenyan Cong', 'Xi Liu', 'Sem Park', 'Vikas Chandra', 'Bo Long', 'David Z. Pan', 'Zhangyang Wang', 'Jinwon Lee'] | ['cs.LG', 'cs.AI', 'cs.PF'] | Large language models (LLMs) are notoriously memory-intensive during
training, particularly with the popular AdamW optimizer. This memory burden
necessitates using more or higher-end GPUs or reducing batch sizes, limiting
training scalability and throughput. To address this, various memory-efficient
optimizers have bee... | 2024-12-06T18:55:34Z | Accepted to MLSys 2025; the newest version with new experiments | null | null | null | null | null | null | null | null | null |
2,412.05271 | Expanding Performance Boundaries of Open-Source Multimodal Models with
Model, Data, and Test-Time Scaling | ['Zhe Chen', 'Weiyun Wang', 'Yue Cao', 'Yangzhou Liu', 'Zhangwei Gao', 'Erfei Cui', 'Jinguo Zhu', 'Shenglong Ye', 'Hao Tian', 'Zhaoyang Liu', 'Lixin Gu', 'Xuehui Wang', 'Qingyun Li', 'Yimin Ren', 'Zixuan Chen', 'Jiapeng Luo', 'Jiahao Wang', 'Tan Jiang', 'Bo Wang', 'Conghui He', 'Botian Shi', 'Xingcheng Zhang', 'Han Lv'... | ['cs.CV'] | We introduce InternVL 2.5, an advanced multimodal large language model (MLLM)
series that builds upon InternVL 2.0, maintaining its core model architecture
while introducing significant enhancements in training and testing strategies
as well as data quality. In this work, we delve into the relationship between
model sc... | 2024-12-06T18:57:08Z | Technical Report | null | null | null | null | null | null | null | null | null |
2,412.05337 | ACT-Bench: Towards Action Controllable World Models for Autonomous
Driving | ['Hidehisa Arai', 'Keishi Ishihara', 'Tsubasa Takahashi', 'Yu Yamaguchi'] | ['cs.CV', 'cs.LG', 'cs.RO'] | World models have emerged as promising neural simulators for autonomous
driving, with the potential to supplement scarce real-world data and enable
closed-loop evaluations. However, current research primarily evaluates these
models based on visual realism or downstream task performance, with limited
focus on fidelity t... | 2024-12-06T01:06:28Z | null | null | null | ACT-Bench: Towards Action Controllable World Models for Autonomous Driving | ['Hidehisa Arai', 'Keishi Ishihara', 'Tsubasa Takahashi', 'Yu Yamaguchi'] | 2,024 | arXiv.org | 3 | 0 | ['Computer Science'] |
2,412.05435 | UniScene: Unified Occupancy-centric Driving Scene Generation | ['Bohan Li', 'Jiazhe Guo', 'Hongsi Liu', 'Yingshuang Zou', 'Yikang Ding', 'Xiwu Chen', 'Hu Zhu', 'Feiyang Tan', 'Chi Zhang', 'Tiancai Wang', 'Shuchang Zhou', 'Li Zhang', 'Xiaojuan Qi', 'Hao Zhao', 'Mu Yang', 'Wenjun Zeng', 'Xin Jin'] | ['cs.CV'] | Generating high-fidelity, controllable, and annotated training data is
critical for autonomous driving. Existing methods typically generate a single
data form directly from a coarse scene layout, which not only fails to output
rich data forms required for diverse downstream tasks but also struggles to
model the direct ... | 2024-12-06T21:41:52Z | CVPR 2025 | null | null | UniScene: Unified Occupancy-centric Driving Scene Generation | ['Bo Li', 'Jiazhe Guo', 'Hongsi Liu', 'Yingshuang Zou', 'Yikang Ding', 'Xiwu Chen', 'Hu Zhu', 'Feiyang Tan', 'Chi Zhang', 'Tiancai Wang', 'Shuchang Zhou', 'Li Zhang', 'Xiaojuan Qi', 'Hao Zhao', 'Mu Yang', 'Wenjun Zeng', 'Xin Jin'] | 2,024 | arXiv.org | 18 | 0 | ['Computer Science'] |
2,412.05479 | LATTE: Learning to Think with Vision Specialists | ['Zixian Ma', 'Jianguo Zhang', 'Zhiwei Liu', 'Jieyu Zhang', 'Juntao Tan', 'Manli Shu', 'Juan Carlos Niebles', 'Shelby Heinecke', 'Huan Wang', 'Caiming Xiong', 'Ranjay Krishna', 'Silvio Savarese'] | ['cs.CV'] | While open-source vision-language models perform well on simple
question-answering, they still struggle with complex questions that require
both perceptual and reasoning capabilities. We propose LATTE, a family of
vision-language models that have LeArned to Think wiTh vision spEcialists. By
offloading perception to sta... | 2024-12-07T00:42:04Z | null | null | null | LATTE: Learning to Think with Vision Specialists | ['Zixian Ma', 'Jianguo Zhang', 'Zhiwei Liu', 'Jieyu Zhang', 'Juntao Tan', 'Manli Shu', 'Juan Carlos Niebles', 'Shelby Heinecke', 'Huan Wang', 'Caiming Xiong', 'Ranjay Krishna', 'Silvio Savarese'] | 2,024 | null | 3 | 47 | ['Computer Science'] |
2,412.05756 | Compositional Image Retrieval via Instruction-Aware Contrastive Learning | ['Wenliang Zhong', 'Weizhi An', 'Feng Jiang', 'Hehuan Ma', 'Yuzhi Guo', 'Junzhou Huang'] | ['cs.CV'] | Composed Image Retrieval (CIR) involves retrieving a target image based on a
composed query of an image paired with text that specifies modifications or
changes to the visual reference. CIR is inherently an instruction-following
task, as the model needs to interpret and apply modifications to the image. In
practice, du... | 2024-12-07T22:46:52Z | 9 pages, 8 figures | null | null | null | null | null | null | null | null | null |
2,412.05888 | MCP-MedSAM: A Powerful Lightweight Medical Segment Anything Model
Trained with a Single GPU in Just One Day | ['Donghang Lyu', 'Ruochen Gao', 'Marius Staring'] | ['cs.CV'] | Medical image segmentation involves partitioning medical images into
meaningful regions, with a focus on identifying anatomical structures and
lesions. It has broad applications in healthcare, and deep learning methods
have enabled significant advancements in automating this process. Recently, the
introduction of the S... | 2024-12-08T10:50:59Z | Accepted for publication at the Journal of Machine Learning for
Biomedical Imaging (MELBA) | Machine.Learning.for.Biomedical.Imaging. 3 (2025) | 10.59275/j.melba.2025-4849 | null | null | null | null | null | null | null |
2,412.05983 | Chimera: Improving Generalist Model with Domain-Specific Experts | ['Tianshuo Peng', 'Mingsheng Li', 'Hongbin Zhou', 'Renqiu Xia', 'Renrui Zhang', 'Lei Bai', 'Song Mao', 'Bin Wang', 'Conghui He', 'Aojun Zhou', 'Botian Shi', 'Tao Chen', 'Bo Zhang', 'Xiangyu Yue'] | ['cs.CV'] | Recent advancements in Large Multi-modal Models (LMMs) underscore the
importance of scaling by increasing image-text paired data, achieving
impressive performance on general tasks. Despite their effectiveness in broad
applications, generalist models are primarily trained on web-scale datasets
dominated by natural image... | 2024-12-08T16:10:42Z | Chimera Homepage: https://alpha-innovator.github.io/chimera_page | null | null | null | null | null | null | null | null | null |
2,412.06089 | GraPE: A Generate-Plan-Edit Framework for Compositional T2I Synthesis | ['Ashish Goswami', 'Satyam Kumar Modi', 'Santhosh Rishi Deshineni', 'Harman Singh', 'Prathosh A. P', 'Parag Singla'] | ['cs.CV'] | Text-to-image (T2I) generation has seen significant progress with diffusion
models, enabling generation of photo-realistic images from text prompts.
Despite this progress, existing methods still face challenges in following
complex text prompts, especially those requiring compositional and multi-step
reasoning. Given s... | 2024-12-08T22:29:56Z | null | null | null | null | null | null | null | null | null | null |
2,412.06234 | Generative Densification: Learning to Densify Gaussians for
High-Fidelity Generalizable 3D Reconstruction | ['Seungtae Nam', 'Xiangyu Sun', 'Gyeongjin Kang', 'Younggeun Lee', 'Seungjun Oh', 'Eunbyung Park'] | ['cs.CV', 'cs.GR'] | Generalized feed-forward Gaussian models have achieved significant progress
in sparse-view 3D reconstruction by leveraging prior knowledge from large
multi-view datasets. However, these models often struggle to represent
high-frequency details due to the limited number of Gaussians. While the
densification strategy use... | 2024-12-09T06:20:51Z | Project page: https://stnamjef.github.io/GenerativeDensification/ | null | null | Generative Densification: Learning to Densify Gaussians for High-Fidelity Generalizable 3D Reconstruction | ['Seungtae Nam', 'Xiangyu Sun', 'Gyeongjin Kang', 'Younggeun Lee', 'Seungjun Oh', 'Eunbyung Park'] | 2,024 | arXiv.org | 0 | 47 | ['Computer Science'] |
2,412.06244 | Unbiased Region-Language Alignment for Open-Vocabulary Dense Prediction | ['Yunheng Li', 'Yuxuan Li', 'Quansheng Zeng', 'Wenhai Wang', 'Qibin Hou', 'Ming-Ming Cheng'] | ['cs.CV'] | Pre-trained vision-language models (VLMs), such as CLIP, have demonstrated
impressive zero-shot recognition capability, but still underperform in dense
prediction tasks. Self-distillation recently is emerging as a promising
approach for fine-tuning VLMs to better adapt to local regions without
requiring extensive annot... | 2024-12-09T06:34:23Z | null | null | null | null | null | null | null | null | null | null |
2,412.06272 | Evaluating LLM-based Approaches to Legal Citation Prediction:
Domain-specific Pre-training, Fine-tuning, or RAG? A Benchmark and an
Australian Law Case Study | ['Jiuzhou Han', 'Paul Burgess', 'Ehsan Shareghi'] | ['cs.CL', 'cs.AI', 'cs.IR'] | Large Language Models (LLMs) have demonstrated strong potential across legal
tasks, yet the problem of legal citation prediction remains under-explored. At
its core, this task demands fine-grained contextual understanding and precise
identification of relevant legislation or precedent. We introduce the AusLaw
Citation ... | 2024-12-09T07:46:14Z | For code, data, and models see https://auslawbench.github.io | null | null | null | null | null | null | null | null | null |
2,412.06322 | LLaVA-SpaceSGG: Visual Instruct Tuning for Open-vocabulary Scene Graph
Generation with Enhanced Spatial Relations | ['Mingjie Xu', 'Mengyang Wu', 'Yuzhi Zhao', 'Jason Chun Lok Li', 'Weifeng Ou'] | ['cs.CV'] | Scene Graph Generation (SGG) converts visual scenes into structured graph
representations, providing deeper scene understanding for complex vision tasks.
However, existing SGG models often overlook essential spatial relationships and
struggle with generalization in open-vocabulary contexts. To address these
limitations... | 2024-12-09T09:18:32Z | Accepted by the WACV 2025, including supplementary material | null | null | null | null | null | null | null | null | null |
2,412.06329 | Normalizing Flows are Capable Generative Models | ['Shuangfei Zhai', 'Ruixiang Zhang', 'Preetum Nakkiran', 'David Berthelot', 'Jiatao Gu', 'Huangjie Zheng', 'Tianrong Chen', 'Miguel Angel Bautista', 'Navdeep Jaitly', 'Josh Susskind'] | ['cs.CV', 'cs.LG'] | Normalizing Flows (NFs) are likelihood-based models for continuous inputs.
They have demonstrated promising results on both density estimation and
generative modeling tasks, but have received relatively little attention in
recent years. In this work, we demonstrate that NFs are more powerful than
previously believed. W... | 2024-12-09T09:28:06Z | ICML 2025 | null | null | null | null | null | null | null | null | null |
2,412.0641 | BatchTopK Sparse Autoencoders | ['Bart Bussmann', 'Patrick Leask', 'Neel Nanda'] | ['cs.LG', 'cs.AI', 'stat.ML'] | Sparse autoencoders (SAEs) have emerged as a powerful tool for interpreting
language model activations by decomposing them into sparse, interpretable
features. A popular approach is the TopK SAE, that uses a fixed number of the
most active latents per sample to reconstruct the model activations. We
introduce BatchTopK ... | 2024-12-09T11:39:00Z | null | null | null | null | null | null | null | null | null | null |
2,412.06464 | Gated Delta Networks: Improving Mamba2 with Delta Rule | ['Songlin Yang', 'Jan Kautz', 'Ali Hatamizadeh'] | ['cs.CL', 'cs.LG'] | Linear Transformers have gained attention as efficient alternatives to
standard Transformers, but their performance in retrieval and long-context
tasks has been limited. To address these limitations, recent work has explored
two distinct mechanisms: gating for adaptive memory control and the delta
update rule for preci... | 2024-12-09T13:09:04Z | ICLR 2025 camera ready | null | null | null | null | null | null | null | null | null |
2,412.06484 | Small Languages, Big Models: A Study of Continual Training on Languages
of Norway | ['David Samuel', 'Vladislav Mikhailov', 'Erik Velldal', 'Lilja Øvrelid', 'Lucas Georges Gabriel Charpentier', 'Andrey Kutuzov', 'Stephan Oepen'] | ['cs.CL'] | Training large language models requires vast amounts of data, posing a
challenge for less widely spoken languages like Norwegian and even more so for
truly low-resource languages like Northern S\'ami. To address this issue, we
present a novel three-stage continual training approach that substantially
improves the downs... | 2024-12-09T13:34:23Z | Published at NoDaLiDa 2025 | Proceedings of the 25th Nordic Conference on Computational
Linguistics (NoDaLiDa 2025). Tallinn, Estonia | null | null | null | null | null | null | null | null |
2,412.06559 | ProcessBench: Identifying Process Errors in Mathematical Reasoning | ['Chujie Zheng', 'Zhenru Zhang', 'Beichen Zhang', 'Runji Lin', 'Keming Lu', 'Bowen Yu', 'Dayiheng Liu', 'Jingren Zhou', 'Junyang Lin'] | ['cs.AI', 'cs.CL', 'cs.LG'] | As language models regularly make mistakes when solving math problems,
automated identification of errors in the reasoning process becomes
increasingly significant for their scalable oversight. In this paper, we
introduce ProcessBench for measuring the ability to identify erroneous steps in
mathematical reasoning. It c... | 2024-12-09T15:11:40Z | ACL 2025 | null | null | ProcessBench: Identifying Process Errors in Mathematical Reasoning | ['Chujie Zheng', 'Zhenru Zhang', 'Beichen Zhang', 'Runji Lin', 'Keming Lu', 'Bowen Yu', 'Dayiheng Liu', 'Jingren Zhou', 'Junyang Lin'] | 2,024 | arXiv.org | 77 | 29 | ['Computer Science'] |
2,412.06699 | You See it, You Got it: Learning 3D Creation on Pose-Free Videos at
Scale | ['Baorui Ma', 'Huachen Gao', 'Haoge Deng', 'Zhengxiong Luo', 'Tiejun Huang', 'Lulu Tang', 'Xinlong Wang'] | ['cs.CV'] | Recent 3D generation models typically rely on limited-scale 3D `gold-labels'
or 2D diffusion priors for 3D content creation. However, their performance is
upper-bounded by constrained 3D priors due to the lack of scalable learning
paradigms. In this work, we present See3D, a visual-conditional multi-view
diffusion mode... | 2024-12-09T17:44:56Z | Accepted by CVPR 2025, Project Page: https://vision.baai.ac.cn/see3d | null | null | null | null | null | null | null | null | null |
2,412.06769 | Training Large Language Models to Reason in a Continuous Latent Space | ['Shibo Hao', 'Sainbayar Sukhbaatar', 'DiJia Su', 'Xian Li', 'Zhiting Hu', 'Jason Weston', 'Yuandong Tian'] | ['cs.CL'] | Large language models (LLMs) are restricted to reason in the "language
space", where they typically express the reasoning process with a
chain-of-thought (CoT) to solve a complex reasoning problem. However, we argue
that language space may not always be optimal for reasoning. For example, most
word tokens are primarily... | 2024-12-09T18:55:56Z | null | null | null | null | null | null | null | null | null | null |
2,412.06781 | Around the World in 80 Timesteps: A Generative Approach to Global Visual
Geolocation | ['Nicolas Dufour', 'David Picard', 'Vicky Kalogeiton', 'Loic Landrieu'] | ['cs.CV', 'cs.LG'] | Global visual geolocation predicts where an image was captured on Earth.
Since images vary in how precisely they can be localized, this task inherently
involves a significant degree of ambiguity. However, existing approaches are
deterministic and overlook this aspect. In this paper, we aim to close the gap
between trad... | 2024-12-09T18:59:04Z | Project page: https://nicolas-dufour.github.io/plonk | null | null | Around the World in 80 Timesteps: A Generative Approach to Global Visual Geolocation | ['Nicolas Dufour', 'David Picard', 'Vicky Kalogeiton', 'Loic Landrieu'] | 2,024 | arXiv.org | 2 | 0 | ['Computer Science'] |
2,412.06782 | CARP: Visuomotor Policy Learning via Coarse-to-Fine Autoregressive
Prediction | ['Zhefei Gong', 'Pengxiang Ding', 'Shangke Lyu', 'Siteng Huang', 'Mingyang Sun', 'Wei Zhao', 'Zhaoxin Fan', 'Donglin Wang'] | ['cs.RO', 'cs.CV'] | In robotic visuomotor policy learning, diffusion-based models have achieved
significant success in improving the accuracy of action trajectory generation
compared to traditional autoregressive models. However, they suffer from
inefficiency due to multiple denoising steps and limited flexibility from
complex constraints... | 2024-12-09T18:59:18Z | null | null | null | null | null | null | null | null | null | null |
2,412.06787 | [MASK] is All You Need | ['Vincent Tao Hu', 'Björn Ommer'] | ['cs.CV', 'cs.AI'] | In generative models, two paradigms have gained attraction in various
applications: next-set prediction-based Masked Generative Models and next-noise
prediction-based Non-Autoregressive Models, e.g., Diffusion Models. In this
work, we propose using discrete-state models to connect them and explore their
scalability in ... | 2024-12-09T18:59:56Z | Technical Report (WIP), Project Page(code, model, dataset):
https://compvis.github.io/mask/ | null | null | null | null | null | null | null | null | null |
2,412.06845 | 7B Fully Open Source Moxin-LLM/VLM -- From Pretraining to GRPO-based
Reinforcement Learning Enhancement | ['Pu Zhao', 'Xuan Shen', 'Zhenglun Kong', 'Yixin Shen', 'Sung-En Chang', 'Arash Akbari', 'Timothy Rupprecht', 'Lei Lu', 'Enfu Nan', 'Changdi Yang', 'Yumei He', 'Weiyan Shi', 'Xingchen Xu', 'Yu Huang', 'Wei Jiang', 'Wei Wang', 'Yue Chen', 'Yong He', 'Yanzhi Wang'] | ['cs.CL', 'cs.AI', 'cs.LG'] | Recently, Large Language Models (LLMs) have undergone a significant
transformation, marked by a rapid rise in both their popularity and
capabilities. Leading this evolution are proprietary LLMs like GPT-4 and
GPT-o1, which have captured widespread attention in the AI community due to
their remarkable performance and ve... | 2024-12-08T02:01:46Z | null | null | null | 7B Fully Open Source Moxin-LLM/VLM -- From Pretraining to GRPO-based Reinforcement Learning Enhancement | ['Pu Zhao', 'Xuan Shen', 'Zhenglun Kong', 'Yixin Shen', 'Sung-En Chang', 'Timothy Rupprecht', 'Lei Lu', 'Enfu Nan', 'Changdi Yang', 'Yumei He', 'Xingchen Xu', 'Yu Huang', 'Wei Wang', 'Yue Chen', 'Yongchun He', 'Yanzhi Wang'] | 2,024 | null | 1 | 130 | ['Computer Science'] |
2,412.06974 | MV-DUSt3R+: Single-Stage Scene Reconstruction from Sparse Views In 2
Seconds | ['Zhenggang Tang', 'Yuchen Fan', 'Dilin Wang', 'Hongyu Xu', 'Rakesh Ranjan', 'Alexander Schwing', 'Zhicheng Yan'] | ['cs.CV', 'cs.AI'] | Recent sparse multi-view scene reconstruction advances like DUSt3R and MASt3R
no longer require camera calibration and camera pose estimation. However, they
only process a pair of views at a time to infer pixel-aligned pointmaps. When
dealing with more than two views, a combinatorial number of error prone
pairwise reco... | 2024-12-09T20:34:55Z | null | null | null | MV-DUSt3R+: Single-Stage Scene Reconstruction from Sparse Views In 2 Seconds | ['Zhenggang Tang', 'Yuchen Fan', 'Dilin Wang', 'Hongyu Xu', 'Rakesh Ranjan', 'Alexander G. Schwing', 'Zhicheng Yan'] | 2,024 | arXiv.org | 18 | 0 | ['Computer Science'] |
2,412.06993 | Toward AI-Driven Digital Organism: Multiscale Foundation Models for
Predicting, Simulating and Programming Biology at All Levels | ['Le Song', 'Eran Segal', 'Eric Xing'] | ['cs.AI', 'cs.LG', 'q-bio.QM'] | We present an approach of using AI to model and simulate biology and life.
Why is it important? Because at the core of medicine, pharmacy, public health,
longevity, agriculture and food security, environmental protection, and clean
energy, it is biology at work. Biology in the physical world is too complex to
manipulat... | 2024-12-09T20:59:59Z | null | null | null | null | null | null | null | null | null | null |
2,412.07112 | Maya: An Instruction Finetuned Multilingual Multimodal Model | ['Nahid Alam', 'Karthik Reddy Kanjula', 'Surya Guthikonda', 'Timothy Chung', 'Bala Krishna S Vegesna', 'Abhipsha Das', 'Anthony Susevski', 'Ryan Sze-Yin Chan', 'S M Iftekhar Uddin', 'Shayekh Bin Islam', 'Roshan Santhosh', 'Snegha A', 'Drishti Sharma', 'Chen Liu', 'Isha Chaturvedi', 'Genta Indra Winata', 'Ashvanth. S', ... | ['cs.CV', 'cs.CL'] | The rapid development of large Vision-Language Models (VLMs) has led to
impressive results on academic benchmarks, primarily in widely spoken
languages. However, significant gaps remain in the ability of current VLMs to
handle low-resource languages and varied cultural contexts, largely due to a
lack of high-quality, d... | 2024-12-10T01:57:17Z | null | null | null | null | null | null | null | null | null | null |
2,412.07338 | Contextualized Counterspeech: Strategies for Adaptation,
Personalization, and Evaluation | ['Lorenzo Cima', 'Alessio Miaschi', 'Amaury Trujillo', 'Marco Avvenuti', "Felice Dell'Orletta", 'Stefano Cresci'] | ['cs.HC', 'cs.AI', 'cs.SI'] | AI-generated counterspeech offers a promising and scalable strategy to curb
online toxicity through direct replies that promote civil discourse. However,
current counterspeech is one-size-fits-all, lacking adaptation to the
moderation context and the users involved. We propose and evaluate multiple
strategies for gener... | 2024-12-10T09:29:52Z | Article published in WebConf 25, 34th ACM Web Conference. Please,
cite the published version | WebConf 2025, 34th ACM Web Conference | 10.1145/3696410.3714507 | null | null | null | null | null | null | null |
2,412.0736 | Efficient 3D Recognition with Event-driven Spike Sparse Convolution | ['Xuerui Qiu', 'Man Yao', 'Jieyuan Zhang', 'Yuhong Chou', 'Ning Qiao', 'Shibo Zhou', 'Bo Xu', 'Guoqi Li'] | ['cs.CV'] | Spiking Neural Networks (SNNs) provide an energy-efficient way to extract 3D
spatio-temporal features. Point clouds are sparse 3D spatial data, which
suggests that SNNs should be well-suited for processing them. However, when
applying SNNs to point clouds, they often exhibit limited performance and fewer
application sc... | 2024-12-10T09:55:15Z | Accepted by AAAI 2025 | null | null | null | null | null | null | null | null | null |
2,412.07371 | PRM: Photometric Stereo based Large Reconstruction Model | ['Wenhang Ge', 'Jiantao Lin', 'Guibao Shen', 'Jiawei Feng', 'Tao Hu', 'Xinli Xu', 'Ying-Cong Chen'] | ['cs.CV', 'cs.GR'] | We propose PRM, a novel photometric stereo based large reconstruction model
to reconstruct high-quality meshes with fine-grained local details. Unlike
previous large reconstruction models that prepare images under fixed and simple
lighting as both input and supervision, PRM renders photometric stereo images
by varying ... | 2024-12-10T10:11:15Z | https://wenhangge.github.io/PRM/ | null | null | PRM: Photometric Stereo based Large Reconstruction Model | ['Wenhang Ge', 'Jiantao Lin', 'Guibao Shen', 'Jiawei Feng', 'Tao Hu', 'Xinli Xu', 'Ying-Cong Chen'] | 2,024 | arXiv.org | 2 | 51 | ['Computer Science'] |
2,412.07589 | DiffSensei: Bridging Multi-Modal LLMs and Diffusion Models for
Customized Manga Generation | ['Jianzong Wu', 'Chao Tang', 'Jingbo Wang', 'Yanhong Zeng', 'Xiangtai Li', 'Yunhai Tong'] | ['cs.CV'] | Story visualization, the task of creating visual narratives from textual
descriptions, has seen progress with text-to-image generation models. However,
these models often lack effective control over character appearances and
interactions, particularly in multi-character scenes. To address these
limitations, we propose ... | 2024-12-10T15:24:12Z | [CVPR 2025] The project page is
https://jianzongwu.github.io/projects/diffsensei/ | null | null | DiffSensei: Bridging Multi-Modal LLMs and Diffusion Models for Customized Manga Generation | ['Jianzong Wu', 'Chao Tang', 'Jingbo Wang', 'Yanhong Zeng', 'Xiangtai Li', 'Yunhai Tong'] | 2,024 | arXiv.org | 5 | 52 | ['Computer Science'] |
2,412.07633 | ChocoLlama: Lessons Learned From Teaching Llamas Dutch | ['Matthieu Meeus', 'Anthony Rathé', 'François Remy', 'Pieter Delobelle', 'Jens-Joris Decorte', 'Thomas Demeester'] | ['cs.CL'] | While Large Language Models (LLMs) have shown remarkable capabilities in
natural language understanding and generation, their performance often lags in
lower-resource, non-English languages due to biases in the training data. In
this work, we explore strategies for adapting the primarily English LLMs
(Llama-2 and Llama... | 2024-12-10T16:13:58Z | null | null | null | null | null | null | null | null | null | null |
2,412.07679 | RADIOv2.5: Improved Baselines for Agglomerative Vision Foundation Models | ['Greg Heinrich', 'Mike Ranzinger', 'Hongxu', 'Yin', 'Yao Lu', 'Jan Kautz', 'Andrew Tao', 'Bryan Catanzaro', 'Pavlo Molchanov'] | ['cs.CV', 'cs.AI'] | Agglomerative models have recently emerged as a powerful approach to training
vision foundation models, leveraging multi-teacher distillation from existing
models such as CLIP, DINO, and SAM. This strategy enables the efficient
creation of robust models, combining the strengths of individual teachers while
significantl... | 2024-12-10T17:06:41Z | null | null | null | RADIOv2.5: Improved Baselines for Agglomerative Vision Foundation Models | ['Greg Heinrich', 'Michael Ranzinger', 'Hongxu Yin', 'Yao Lu', 'Jan Kautz', 'Andrew Tao', 'Bryan Catanzaro', 'Pavlo Molchanov'] | 2,024 | null | 4 | 0 | ['Computer Science'] |
2,412.07689 | DriveMM: All-in-One Large Multimodal Model for Autonomous Driving | ['Zhijian Huang', 'Chengjian Feng', 'Feng Yan', 'Baihui Xiao', 'Zequn Jie', 'Yujie Zhong', 'Xiaodan Liang', 'Lin Ma'] | ['cs.CV', 'cs.MM', 'cs.RO'] | Large Multimodal Models (LMMs) have demonstrated exceptional comprehension
and interpretation capabilities in Autonomous Driving (AD) by incorporating
large language models. Despite the advancements, current data-driven AD
approaches tend to concentrate on a single dataset and specific tasks,
neglecting their overall c... | 2024-12-10T17:27:32Z | null | null | null | null | null | null | null | null | null | null |
2,412.07724 | Granite Guardian | ['Inkit Padhi', 'Manish Nagireddy', 'Giandomenico Cornacchia', 'Subhajit Chaudhury', 'Tejaswini Pedapati', 'Pierre Dognin', 'Keerthiram Murugesan', 'Erik Miehling', 'Martín Santillán Cooper', 'Kieran Fraser', 'Giulio Zizzo', 'Muhammad Zaid Hameed', 'Mark Purcell', 'Michael Desmond', 'Qian Pan', 'Zahra Ashktorab', 'Inge... | ['cs.CL'] | We introduce the Granite Guardian models, a suite of safeguards designed to
provide risk detection for prompts and responses, enabling safe and responsible
use in combination with any large language model (LLM). These models offer
comprehensive coverage across multiple risk dimensions, including social bias,
profanity,... | 2024-12-10T18:17:02Z | null | null | null | Granite Guardian | ['Inkit Padhi', 'Manish Nagireddy', 'Giandomenico Cornacchia', 'Subhajit Chaudhury', 'Tejaswini Pedapati', 'Pierre L. Dognin', 'K. Murugesan', 'Erik Miehling', 'Martín Santillán Cooper', 'Kieran Fraser', 'Giulio Zizzo', 'Muhammad Zaid Hameed', 'Mark Purcell', 'Michael Desmond', 'Qian Pan', 'Inge Vejsbjerg', 'Elizabeth ... | 2,024 | arXiv.org | 6 | 0 | ['Computer Science'] |
2,412.07755 | SAT: Dynamic Spatial Aptitude Training for Multimodal Language Models | ['Arijit Ray', 'Jiafei Duan', 'Ellis Brown', 'Reuben Tan', 'Dina Bashkirova', 'Rose Hendrix', 'Kiana Ehsani', 'Aniruddha Kembhavi', 'Bryan A. Plummer', 'Ranjay Krishna', 'Kuo-Hao Zeng', 'Kate Saenko'] | ['cs.CV', 'cs.AI', 'cs.GR', 'cs.RO'] | Reasoning about motion and space is a fundamental cognitive capability that
is required by multiple real-world applications. While many studies highlight
that large multimodal language models (MLMs) struggle to reason about space,
they only focus on static spatial relationships, and not dynamic awareness of
motion and ... | 2024-12-10T18:52:45Z | Project webpage: https://arijitray.com/SAT/ | null | null | null | null | null | null | null | null | null |
2,412.07761 | Repurposing Pre-trained Video Diffusion Models for Event-based Video
Interpolation | ['Jingxi Chen', 'Brandon Y. Feng', 'Haoming Cai', 'Tianfu Wang', 'Levi Burner', 'Dehao Yuan', 'Cornelia Fermuller', 'Christopher A. Metzler', 'Yiannis Aloimonos'] | ['cs.CV'] | Video Frame Interpolation aims to recover realistic missing frames between
observed frames, generating a high-frame-rate video from a low-frame-rate
video. However, without additional guidance, the large motion between frames
makes this problem ill-posed. Event-based Video Frame Interpolation (EVFI)
addresses this chal... | 2024-12-10T18:55:30Z | Accepted to CVPR 2025 | null | null | Repurposing Pre-trained Video Diffusion Models for Event-based Video Interpolation | ['Jingxi Chen', 'Brandon Y. Feng', 'Haoming Cai', 'Tianfu Wang', 'Levi Burner', 'Dehao Yuan', 'C. Fermüller', 'Christopher A. Metzler', 'Y. Aloimonos'] | 2,024 | arXiv.org | 3 | 54 | ['Computer Science'] |
2,412.07767 | Learning Visual Generative Priors without Text | ['Shuailei Ma', 'Kecheng Zheng', 'Ying Wei', 'Wei Wu', 'Fan Lu', 'Yifei Zhang', 'Chen-Wei Xie', 'Biao Gong', 'Jiapeng Zhu', 'Yujun Shen'] | ['cs.CV'] | Although text-to-image (T2I) models have recently thrived as visual
generative priors, their reliance on high-quality text-image pairs makes
scaling up expensive. We argue that grasping the cross-modality alignment is
not a necessity for a sound visual generative prior, whose focus should be on
texture modeling. Such a... | 2024-12-10T18:59:31Z | Project Page: https://ant-research.github.io/lumos | null | null | Learning Visual Generative Priors without Text | ['Shuailei Ma', 'Kecheng Zheng', 'Ying Wei', 'Wei Wu', 'Fan Lu', 'Yifei Zhang', 'Chen-Wei Xie', 'Biao Gong', 'Jiapeng Zhu', 'Yujun Shen'] | 2,024 | Computer Vision and Pattern Recognition | 3 | 56 | ['Computer Science'] |
2,412.07769 | BiMediX2: Bio-Medical EXpert LMM for Diverse Medical Modalities | ['Sahal Shaji Mullappilly', 'Mohammed Irfan Kurpath', 'Sara Pieri', 'Saeed Yahya Alseiari', 'Shanavas Cholakkal', 'Khaled Aldahmani', 'Fahad Khan', 'Rao Anwer', 'Salman Khan', 'Timothy Baldwin', 'Hisham Cholakkal'] | ['cs.CV'] | This paper introduces BiMediX2, a bilingual (Arabic-English) Bio-Medical
EXpert Large Multimodal Model (LMM) with a unified architecture that integrates
text and visual modalities, enabling advanced image understanding and medical
applications. BiMediX2 leverages the Llama3.1 architecture and integrates text
and visual... | 2024-12-10T18:59:35Z | null | null | null | BiMediX2: Bio-Medical EXpert LMM for Diverse Medical Modalities | ['Sahal Shaji Mullappilly', 'Mohammed Irfan Kurpath', 'Sara Pieri', 'Saeed Yahya Alseiari', 'Shanavas Cholakkal', 'Khaled Aldahmani', 'F. Khan', 'R. Anwer', 'Salman H. Khan', 'Timothy Baldwin', 'Hisham Cholakkal'] | 2,024 | arXiv.org | 3 | 0 | ['Computer Science'] |
2,412.07771 | PETALface: Parameter Efficient Transfer Learning for Low-resolution Face
Recognition | ['Kartik Narayan', 'Nithin Gopalakrishnan Nair', 'Jennifer Xu', 'Rama Chellappa', 'Vishal M. Patel'] | ['cs.CV'] | Pre-training on large-scale datasets and utilizing margin-based loss
functions have been highly successful in training models for high-resolution
face recognition. However, these models struggle with low-resolution face
datasets, in which the faces lack the facial attributes necessary for
distinguishing different faces... | 2024-12-10T18:59:45Z | Accepted to WACV 2025. Project Page:
https://kartik-3004.github.io/PETALface/ | null | null | null | null | null | null | null | null | null |
2,412.07772 | From Slow Bidirectional to Fast Autoregressive Video Diffusion Models | ['Tianwei Yin', 'Qiang Zhang', 'Richard Zhang', 'William T. Freeman', 'Fredo Durand', 'Eli Shechtman', 'Xun Huang'] | ['cs.CV'] | Current video diffusion models achieve impressive generation quality but
struggle in interactive applications due to bidirectional attention
dependencies. The generation of a single frame requires the model to process
the entire sequence, including the future. We address this limitation by
adapting a pretrained bidirec... | 2024-12-10T18:59:50Z | Project Page: https://causvid.github.io/ | null | null | null | null | null | null | null | null | null |
2,412.07992 | Concept Bottleneck Large Language Models | ['Chung-En Sun', 'Tuomas Oikarinen', 'Berk Ustun', 'Tsui-Wei Weng'] | ['cs.CL', 'cs.LG'] | We introduce Concept Bottleneck Large Language Models (CB-LLMs), a novel
framework for building inherently interpretable Large Language Models (LLMs).
In contrast to traditional black-box LLMs that rely on limited post-hoc
interpretations, CB-LLMs integrate intrinsic interpretability directly into the
LLMs -- allowing ... | 2024-12-11T00:04:10Z | Accepted to ICLR 2025. arXiv admin note: substantial text overlap
with arXiv:2407.04307 | null | null | null | null | null | null | null | null | null |
2,412.08347 | SmolTulu: Higher Learning Rate to Batch Size Ratios Can Lead to Better
Reasoning in SLMs | ['Sultan Alrashed'] | ['cs.CL', 'cs.AI'] | We present SmolTulu-1.7b-Instruct, referenced in this report as
SmolTulu-DPO-1130, an instruction-tuned language model that adapts AllenAI's
Tulu 3 post-training pipeline to enhance Huggingface's SmolLM2-1.7B base model.
Through comprehensive empirical analysis using a 135M parameter model, we
demonstrate that the rela... | 2024-12-11T12:41:36Z | 10 pages, 4 figures, and 13 tables. For the SmolTulu-1.7b-instruct
model, see: https://huggingface.co/SultanR/SmolTulu-1.7b-Instruct | null | null | SmolTulu: Higher Learning Rate to Batch Size Ratios Can Lead to Better Reasoning in SLMs | ['Sultan Alrashed'] | 2,024 | arXiv.org | 2 | 0 | ['Computer Science'] |
2,412.08376 | Reloc3r: Large-Scale Training of Relative Camera Pose Regression for
Generalizable, Fast, and Accurate Visual Localization | ['Siyan Dong', 'Shuzhe Wang', 'Shaohui Liu', 'Lulu Cai', 'Qingnan Fan', 'Juho Kannala', 'Yanchao Yang'] | ['cs.CV'] | Visual localization aims to determine the camera pose of a query image
relative to a database of posed images. In recent years, deep neural networks
that directly regress camera poses have gained popularity due to their fast
inference capabilities. However, existing methods struggle to either generalize
well to new sce... | 2024-12-11T13:36:18Z | CVPR 2025 | null | null | Reloc3r: Large-Scale Training of Relative Camera Pose Regression for Generalizable, Fast, and Accurate Visual Localization | ['Siyan Dong', 'Shuzhe Wang', 'Shaohui Liu', 'Lulu Cai', 'Qingnan Fan', 'Juho Kannala', 'Yanchao Yang'] | 2,024 | arXiv.org | 6 | 135 | ['Computer Science'] |
2,412.08443 | POINTS1.5: Building a Vision-Language Model towards Real World
Applications | ['Yuan Liu', 'Le Tian', 'Xiao Zhou', 'Xinyu Gao', 'Kavio Yu', 'Yang Yu', 'Jie Zhou'] | ['cs.CV', 'cs.MM'] | Vision-language models have made significant strides recently, demonstrating
superior performance across a range of tasks, e.g. optical character
recognition and complex diagram analysis. Building on this trend, we introduce
a new vision-language model, POINTS1.5, designed to excel in various real-world
applications. P... | 2024-12-11T15:08:25Z | null | null | null | POINTS1.5: Building a Vision-Language Model towards Real World Applications | ['Yuan Liu', 'Le Tian', 'Xiao Zhou', 'Xinyu Gao', 'Kavio Yu', 'Yang Yu', 'Jie Zhou'] | 2,024 | arXiv.org | 4 | 0 | ['Computer Science'] |
2,412.08486 | Learning Flow Fields in Attention for Controllable Person Image
Generation | ['Zijian Zhou', 'Shikun Liu', 'Xiao Han', 'Haozhe Liu', 'Kam Woh Ng', 'Tian Xie', 'Yuren Cong', 'Hang Li', 'Mengmeng Xu', 'Juan-Manuel Pérez-Rúa', 'Aditya Patel', 'Tao Xiang', 'Miaojing Shi', 'Sen He'] | ['cs.CV'] | Controllable person image generation aims to generate a person image
conditioned on reference images, allowing precise control over the person's
appearance or pose. However, prior methods often distort fine-grained textural
details from the reference image, despite achieving high overall image quality.
We attribute the... | 2024-12-11T15:51:14Z | github: https://github.com/franciszzj/Leffa, demo:
https://huggingface.co/spaces/franciszzj/Leffa, model:
https://huggingface.co/franciszzj/Leffa | null | null | Learning Flow Fields in Attention for Controllable Person Image Generation | ['Zijian Zhou', 'Shikun Liu', 'Xiao Han', 'Haozhe Liu', 'KamWoh Ng', 'Tian Xie', 'Yuren Cong', 'Hang Li', 'Mengmeng Xu', "Juan-Manuel P'erez-R'ua", 'Aditya Patel', 'Tao Xiang', 'Miaojing Shi', 'Sen He'] | 2,024 | arXiv.org | 2 | 0 | ['Computer Science'] |
2,412.08573 | TryOffAnyone: Tiled Cloth Generation from a Dressed Person | ['Ioannis Xarchakos', 'Theodoros Koukopoulos'] | ['cs.CV'] | The fashion industry is increasingly leveraging computer vision and deep
learning technologies to enhance online shopping experiences and operational
efficiencies. In this paper, we address the challenge of generating
high-fidelity tiled garment images essential for personalized recommendations,
outfit composition, and... | 2024-12-11T17:41:53Z | null | null | null | null | null | null | null | null | null | null |
2,412.08591 | RoomTour3D: Geometry-Aware Video-Instruction Tuning for Embodied
Navigation | ['Mingfei Han', 'Liang Ma', 'Kamila Zhumakhanova', 'Ekaterina Radionova', 'Jingyi Zhang', 'Xiaojun Chang', 'Xiaodan Liang', 'Ivan Laptev'] | ['cs.CV', 'cs.AI', 'cs.RO'] | Vision-and-Language Navigation (VLN) suffers from the limited diversity and
scale of training data, primarily constrained by the manual curation of
existing simulators. To address this, we introduce RoomTour3D, a
video-instruction dataset derived from web-based room tour videos that capture
real-world indoor spaces and... | 2024-12-11T18:10:21Z | CVPR2025 | null | null | null | null | null | null | null | null | null |
2,412.08637 | DMin: Scalable Training Data Influence Estimation for Diffusion Models | ['Huawei Lin', 'Yingjie Lao', 'Weijie Zhao'] | ['cs.CV', 'cs.AI', 'cs.LG'] | Identifying the training data samples that most influence a generated image
is a critical task in understanding diffusion models (DMs), yet existing
influence estimation methods are constrained to small-scale or LoRA-tuned
models due to computational limitations. To address this challenge, we propose
DMin (Diffusion Mo... | 2024-12-11T18:58:40Z | 14 pages, 6 figures, 8 tables. Under Review | null | null | DMin: Scalable Training Data Influence Estimation for Diffusion Models | ['Huawei Lin', 'Yingjie Lao', 'Weijie Zhao'] | 2,024 | arXiv.org | 3 | 39 | ['Computer Science'] |
2,412.08647 | SegFace: Face Segmentation of Long-Tail Classes | ['Kartik Narayan', 'Vibashan VS', 'Vishal M. Patel'] | ['cs.CV'] | Face parsing refers to the semantic segmentation of human faces into key
facial regions such as eyes, nose, hair, etc. It serves as a prerequisite for
various advanced applications, including face editing, face swapping, and
facial makeup, which often require segmentation masks for classes like
eyeglasses, hats, earrin... | 2024-12-11T18:59:57Z | Accepted to AAAI 2025. Project Page:
https://kartik-3004.github.io/SegFace/ | null | null | null | null | null | null | null | null | null |
2,412.08686 | LatentQA: Teaching LLMs to Decode Activations Into Natural Language | ['Alexander Pan', 'Lijie Chen', 'Jacob Steinhardt'] | ['cs.CL', 'cs.CY', 'cs.LG'] | Interpretability methods seek to understand language model representations,
yet the outputs of most such methods -- circuits, vectors, scalars -- are not
immediately human-interpretable. In response, we introduce LatentQA, the task
of answering open-ended questions about model activations in natural language.
Towards s... | 2024-12-11T18:59:33Z | Project page is at https://latentqa.github.io | null | null | null | null | null | null | null | null | null |
2,412.08687 | VisionArena: 230K Real World User-VLM Conversations with Preference
Labels | ['Christopher Chou', 'Lisa Dunlap', 'Koki Mashita', 'Krishna Mandal', 'Trevor Darrell', 'Ion Stoica', 'Joseph E. Gonzalez', 'Wei-Lin Chiang'] | ['cs.CV'] | With the growing adoption and capabilities of vision-language models (VLMs)
comes the need for benchmarks that capture authentic user-VLM interactions. In
response, we create VisionArena, a dataset of 230K real-world conversations
between users and VLMs. Collected from Chatbot Arena - an open-source platform
where user... | 2024-12-11T18:59:46Z | updated for CVPR Camera Ready | null | null | null | null | null | null | null | null | null |
2,412.08737 | Euclid: Supercharging Multimodal LLMs with Synthetic High-Fidelity
Visual Descriptions | ['Jiarui Zhang', 'Ollie Liu', 'Tianyu Yu', 'Jinyi Hu', 'Willie Neiswanger'] | ['cs.CV', 'cs.AI', 'cs.CL'] | Multimodal large language models (MLLMs) have made rapid progress in recent
years, yet continue to struggle with low-level visual perception (LLVP) --
particularly the ability to accurately describe the geometric details of an
image. This capability is crucial for applications in areas such as robotics,
medical image a... | 2024-12-11T19:12:13Z | 33 pages, 22 figures, 5 tables, 7 algorithms | null | null | Euclid: Supercharging Multimodal LLMs with Synthetic High-Fidelity Visual Descriptions | ['Jiarui Zhang', 'Ollie Liu', 'Tianyu Yu', 'Jinyi Hu', 'W. Neiswanger'] | 2,024 | arXiv.org | 4 | 0 | ['Computer Science'] |
2,412.08746 | DocVLM: Make Your VLM an Efficient Reader | ['Mor Shpigel Nacson', 'Aviad Aberdam', 'Roy Ganz', 'Elad Ben Avraham', 'Alona Golts', 'Yair Kittenplon', 'Shai Mazor', 'Ron Litman'] | ['cs.CV', 'cs.LG'] | Vision-Language Models (VLMs) excel in diverse visual tasks but face
challenges in document understanding, which requires fine-grained text
processing. While typical visual tasks perform well with low-resolution inputs,
reading-intensive applications demand high-resolution, resulting in significant
computational overhe... | 2024-12-11T19:35:06Z | null | null | null | null | null | null | null | null | null | null |
2,412.08774 | ProtoOcc: Accurate, Efficient 3D Occupancy Prediction Using Dual Branch
Encoder-Prototype Query Decoder | ['Jungho Kim', 'Changwon Kang', 'Dongyoung Lee', 'Sehwan Choi', 'Jun Won Choi'] | ['cs.CV'] | In this paper, we introduce ProtoOcc, a novel 3D occupancy prediction model
designed to predict the occupancy states and semantic classes of 3D voxels
through a deep semantic understanding of scenes. ProtoOcc consists of two main
components: the Dual Branch Encoder (DBE) and the Prototype Query Decoder
(PQD). The DBE p... | 2024-12-11T20:55:21Z | Accepted to AAAI Conference on Artificial Intelligence 2025, 15
pages, 9 figures | null | null | null | null | null | null | null | null | null |
2,412.08781 | GMem: A Modular Approach for Ultra-Efficient Generative Models | ['Yi Tang', 'Peng Sun', 'Zhenglin Cheng', 'Tao Lin'] | ['cs.CV', 'cs.LG'] | Recent studies indicate that the denoising process in deep generative
diffusion models implicitly learns and memorizes semantic information from the
data distribution. These findings suggest that capturing more complex data
distributions requires larger neural networks, leading to a substantial
increase in computationa... | 2024-12-11T21:23:24Z | 9 pages, 5 figures, 3 tables | null | null | null | null | null | null | null | null | null |
2,412.08802 | jina-clip-v2: Multilingual Multimodal Embeddings for Text and Images | ['Andreas Koukounas', 'Georgios Mastrapas', 'Sedigheh Eslami', 'Bo Wang', 'Mohammad Kalim Akram', 'Michael Günther', 'Isabelle Mohr', 'Saba Sturua', 'Nan Wang', 'Han Xiao'] | ['cs.CL', 'cs.CV', 'cs.IR', '68T50', 'I.2.7; I.2.10'] | Contrastive Language-Image Pretraining (CLIP) has been widely used for
crossmodal information retrieval and multimodal understanding tasks. However,
CLIP models are mainly optimized for crossmodal vision-language tasks and
underperform in single-mode text tasks. Moreover, these models are often
trained on English datas... | 2024-12-11T22:28:12Z | 30 pages, 1-10 main paper, 10-12 refs, 12-30 benchmarks | null | null | jina-clip-v2: Multilingual Multimodal Embeddings for Text and Images | ['Andreas Koukounas', 'Georgios Mastrapas', 'Bo Wang', 'Mohammad Kalim Akram', 'Sedigheh Eslami', 'Michael Gunther', 'Isabelle Mohr', 'Saba Sturua', 'Scott Martens', 'Nan Wang', 'Han Xiao'] | 2,024 | arXiv.org | 10 | 48 | ['Computer Science'] |
2,412.08864 | A Graph-Based Synthetic Data Pipeline for Scaling High-Quality Reasoning
Instructions | ['Jiankang Wang', 'Jianjun Xu', 'Xiaorui Wang', 'Yuxin Wang', 'Mengting Xing', 'Shancheng Fang', 'Zhineng Chen', 'Hongtao Xie', 'Yongdong Zhang'] | ['cs.CL'] | Synthesizing high-quality reasoning data for continual training has been
proven to be effective in enhancing the performance of Large Language Models
(LLMs). However, previous synthetic approaches struggle to easily scale up data
and incur high costs in the pursuit of high quality. In this paper, we propose
the Graph-b... | 2024-12-12T01:52:25Z | null | null | null | A Graph-Based Synthetic Data Pipeline for Scaling High-Quality Reasoning Instructions | ['Jiankang Wang', 'Jianjun Xu', 'Xiaorui Wang', 'Yuxin Wang', 'Mengting Xing', 'Shancheng Fang', 'Zhineng Chen', 'Hongtao Xie', 'Yongdong Zhang'] | 2,024 | arXiv.org | 1 | 46 | ['Computer Science'] |
2,412.08905 | Phi-4 Technical Report | ['Marah Abdin', 'Jyoti Aneja', 'Harkirat Behl', 'Sébastien Bubeck', 'Ronen Eldan', 'Suriya Gunasekar', 'Michael Harrison', 'Russell J. Hewett', 'Mojan Javaheripi', 'Piero Kauffmann', 'James R. Lee', 'Yin Tat Lee', 'Yuanzhi Li', 'Weishung Liu', 'Caio C. T. Mendes', 'Anh Nguyen', 'Eric Price', 'Gustavo de Rosa', 'Olli Sa... | ['cs.CL', 'cs.AI'] | We present phi-4, a 14-billion parameter language model developed with a
training recipe that is centrally focused on data quality. Unlike most language
models, where pre-training is based primarily on organic data sources such as
web content or code, phi-4 strategically incorporates synthetic data throughout
the train... | 2024-12-12T03:37:41Z | null | null | null | null | null | null | null | null | null | null |
2,412.09013 | Arbitrary-steps Image Super-resolution via Diffusion Inversion | ['Zongsheng Yue', 'Kang Liao', 'Chen Change Loy'] | ['cs.CV', 'NA', 'I.4.3'] | This study presents a new image super-resolution (SR) technique based on
diffusion inversion, aiming at harnessing the rich image priors encapsulated in
large pre-trained diffusion models to improve SR performance. We design a
Partial noise Prediction strategy to construct an intermediate state of the
diffusion model, ... | 2024-12-12T07:24:13Z | Accepted by CVPR 2025. Project: https://github.com/zsyOAOA/InvSR | null | null | null | null | null | null | null | null | null |
2,412.09025 | Shiksha: A Technical Domain focused Translation Dataset and Model for
Indian Languages | ['Advait Joglekar', 'Srinivasan Umesh'] | ['cs.CL', 'cs.AI'] | Neural Machine Translation (NMT) models are typically trained on datasets
with limited exposure to Scientific, Technical and Educational domains.
Translation models thus, in general, struggle with tasks that involve
scientific understanding or technical jargon. Their performance is found to be
even worse for low-resour... | 2024-12-12T07:40:55Z | null | null | null | null | null | null | null | null | null | null |
2,412.09262 | LatentSync: Taming Audio-Conditioned Latent Diffusion Models for Lip
Sync with SyncNet Supervision | ['Chunyu Li', 'Chao Zhang', 'Weikai Xu', 'Jingyu Lin', 'Jinghui Xie', 'Weiguo Feng', 'Bingyue Peng', 'Cunjian Chen', 'Weiwei Xing'] | ['cs.CV'] | End-to-end audio-conditioned latent diffusion models (LDMs) have been widely
adopted for audio-driven portrait animation, demonstrating their effectiveness
in generating lifelike and high-resolution talking videos. However, direct
application of audio-conditioned LDMs to lip-synchronization (lip-sync) tasks
results in ... | 2024-12-12T13:20:52Z | null | null | null | null | null | null | null | null | null | null |
2,412.09349 | DisPose: Disentangling Pose Guidance for Controllable Human Image
Animation | ['Hongxiang Li', 'Yaowei Li', 'Yuhang Yang', 'Junjie Cao', 'Zhihong Zhu', 'Xuxin Cheng', 'Long Chen'] | ['cs.CV'] | Controllable human image animation aims to generate videos from reference
images using driving videos. Due to the limited control signals provided by
sparse guidance (e.g., skeleton pose), recent works have attempted to introduce
additional dense conditions (e.g., depth map) to ensure motion alignment.
However, such st... | 2024-12-12T15:15:59Z | ICLR 2025 | null | null | DisPose: Disentangling Pose Guidance for Controllable Human Image Animation | ['Hongxiang Li', 'Yaowei Li', 'Yuhang Yang', 'Junjie Cao', 'Zhihong Zhu', 'Xuxin Cheng', 'Long Chen'] | 2,024 | International Conference on Learning Representations | 12 | 54 | ['Computer Science'] |
2,412.0937 | Word Sense Linking: Disambiguating Outside the Sandbox | ['Andrei Stefan Bejgu', 'Edoardo Barba', 'Luigi Procopio', 'Alberte Fernández-Castro', 'Roberto Navigli'] | ['cs.CL', 'cs.AI'] | Word Sense Disambiguation (WSD) is the task of associating a word in a given
context with its most suitable meaning among a set of possible candidates.
While the task has recently witnessed renewed interest, with systems achieving
performances above the estimated inter-annotator agreement, at the time of
writing it sti... | 2024-12-12T15:38:34Z | null | Findings of the Association for Computational Linguistics ACL
2024, 2024, 14332-14347 | 10.18653/v1/2024.findings-acl.851 | null | null | null | null | null | null | null |
2,412.09401 | SLAM3R: Real-Time Dense Scene Reconstruction from Monocular RGB Videos | ['Yuzheng Liu', 'Siyan Dong', 'Shuzhe Wang', 'Yingda Yin', 'Yanchao Yang', 'Qingnan Fan', 'Baoquan Chen'] | ['cs.CV'] | In this paper, we introduce SLAM3R, a novel and effective system for
real-time, high-quality, dense 3D reconstruction using RGB videos. SLAM3R
provides an end-to-end solution by seamlessly integrating local 3D
reconstruction and global coordinate registration through feed-forward neural
networks. Given an input video, ... | 2024-12-12T16:08:03Z | CVPR 2025 | null | null | SLAM3R: Real-Time Dense Scene Reconstruction from Monocular RGB Videos | ['Yuzheng Liu', 'Siyan Dong', 'Shuzhe Wang', 'Yanchao Yang', 'Qingnan Fan', 'Baoquan Chen'] | 2,024 | arXiv.org | 8 | 79 | ['Computer Science'] |
2,412.09405 | Learned Compression for Compressed Learning | ['Dan Jacobellis', 'Neeraja J. Yadwadkar'] | ['eess.IV', 'cs.CV', 'cs.LG', 'eess.AS', 'eess.SP'] | Modern sensors produce increasingly rich streams of high-resolution data. Due
to resource constraints, machine learning systems discard the vast majority of
this information via resolution reduction. Compressed-domain learning allows
models to operate on compact latent representations, allowing higher effective
resolut... | 2024-12-12T16:09:57Z | Accepted as paper to 2025 IEEE Data Compression Conference | null | null | null | null | null | null | null | null | null |
2,412.09413 | Imitate, Explore, and Self-Improve: A Reproduction Report on
Slow-thinking Reasoning Systems | ['Yingqian Min', 'Zhipeng Chen', 'Jinhao Jiang', 'Jie Chen', 'Jia Deng', 'Yiwen Hu', 'Yiru Tang', 'Jiapeng Wang', 'Xiaoxue Cheng', 'Huatong Song', 'Wayne Xin Zhao', 'Zheng Liu', 'Zhongyuan Wang', 'Ji-Rong Wen'] | ['cs.AI', 'cs.CL'] | Recently, slow-thinking reasoning systems, such as o1, have demonstrated
remarkable capabilities in solving complex reasoning tasks. These systems
typically engage in an extended thinking process before responding to a query,
allowing them to generate more thorough, accurate, and well-reasoned solutions.
These systems ... | 2024-12-12T16:20:36Z | Technical Report on Slow Thinking with LLMs: Part II | null | null | null | null | null | null | null | null | null |
2,412.0956 | Foundational Large Language Models for Materials Research | ['Vaibhav Mishra', 'Somaditya Singh', 'Dhruv Ahlawat', 'Mohd Zaki', 'Vaibhav Bihani', 'Hargun Singh Grover', 'Biswajit Mishra', 'Santiago Miret', 'Mausam', 'N. M. Anoop Krishnan'] | ['cond-mat.mtrl-sci', 'cs.CL', 'cs.IR'] | Materials discovery and development are critical for addressing global
challenges. Yet, the exponential growth in materials science literature
comprising vast amounts of textual data has created significant bottlenecks in
knowledge extraction, synthesis, and scientific reasoning. Large Language
Models (LLMs) offer unpr... | 2024-12-12T18:46:38Z | null | null | null | null | null | null | null | null | null | null |
2,412.09573 | FreeSplatter: Pose-free Gaussian Splatting for Sparse-view 3D
Reconstruction | ['Jiale Xu', 'Shenghua Gao', 'Ying Shan'] | ['cs.CV'] | Existing sparse-view reconstruction models heavily rely on accurate known
camera poses. However, deriving camera extrinsics and intrinsics from
sparse-view images presents significant challenges. In this work, we present
FreeSplatter, a highly scalable, feed-forward reconstruction framework capable
of generating high-q... | 2024-12-12T18:52:53Z | Project page: https://bluestyle97.github.io/projects/freesplatter/ | null | null | null | null | null | null | null | null | null |
2,412.09593 | Neural LightRig: Unlocking Accurate Object Normal and Material
Estimation with Multi-Light Diffusion | ['Zexin He', 'Tengfei Wang', 'Xin Huang', 'Xingang Pan', 'Ziwei Liu'] | ['cs.CV'] | Recovering the geometry and materials of objects from a single image is
challenging due to its under-constrained nature. In this paper, we present
Neural LightRig, a novel framework that boosts intrinsic estimation by
leveraging auxiliary multi-lighting conditions from 2D diffusion priors.
Specifically, 1) we first lev... | 2024-12-12T18:58:09Z | Project page: https://projects.zxhezexin.com/neural-lightrig | null | null | null | null | null | null | null | null | null |
2,412.09596 | InternLM-XComposer2.5-OmniLive: A Comprehensive Multimodal System for
Long-term Streaming Video and Audio Interactions | ['Pan Zhang', 'Xiaoyi Dong', 'Yuhang Cao', 'Yuhang Zang', 'Rui Qian', 'Xilin Wei', 'Lin Chen', 'Yifei Li', 'Junbo Niu', 'Shuangrui Ding', 'Qipeng Guo', 'Haodong Duan', 'Xin Chen', 'Han Lv', 'Zheng Nie', 'Min Zhang', 'Bin Wang', 'Wenwei Zhang', 'Xinyue Zhang', 'Jiaye Ge', 'Wei Li', 'Jingwen Li', 'Zhongying Tu', 'Conghui... | ['cs.CV', 'cs.AI', 'cs.CL'] | Creating AI systems that can interact with environments over long periods,
similar to human cognition, has been a longstanding research goal. Recent
advancements in multimodal large language models (MLLMs) have made significant
strides in open-world understanding. However, the challenge of continuous and
simultaneous s... | 2024-12-12T18:58:30Z | Github Repo:
https://github.com/InternLM/InternLM-XComposer/tree/main/InternLM-XComposer-2.5-OmniLive | null | null | null | null | null | null | null | null | null |
2,412.09602 | Hidden Biases of End-to-End Driving Datasets | ['Julian Zimmerlin', 'Jens Beißwenger', 'Bernhard Jaeger', 'Andreas Geiger', 'Kashyap Chitta'] | ['cs.CV', 'cs.AI', 'cs.LG', 'cs.RO'] | End-to-end driving systems have made rapid progress, but have so far not been
applied to the challenging new CARLA Leaderboard 2.0. Further, while there is a
large body of literature on end-to-end architectures and training strategies,
the impact of the training dataset is often overlooked. In this work, we make a
firs... | 2024-12-12T18:59:13Z | Technical report for the CVPR 2024 Workshop on Foundation Models for
Autonomous Systems. Runner-up of the track 'CARLA Autonomous Driving
Challenge' in the 2024 Autonomous Grand Challenge
(https://opendrivelab.com/challenge2024/) | null | null | Hidden Biases of End-to-End Driving Datasets | ['Julian Zimmerlin', 'Jens Beisswenger', 'Bernhard Jaeger', 'Andreas Geiger', 'Kashyap Chitta'] | 2,024 | arXiv.org | 11 | 33 | ['Computer Science'] |
2,412.09605 | AgentTrek: Agent Trajectory Synthesis via Guiding Replay with Web
Tutorials | ['Yiheng Xu', 'Dunjie Lu', 'Zhennan Shen', 'Junli Wang', 'Zekun Wang', 'Yuchen Mao', 'Caiming Xiong', 'Tao Yu'] | ['cs.CL'] | Graphical User Interface (GUI) agents can automate complex tasks across
digital environments, but their development is hindered by the scarcity of
high-quality trajectory data for training. Existing approaches rely on
expensive human annotation, making them unsustainable at scale. We propose
AgentTrek, a scalable data ... | 2024-12-12T18:59:27Z | ICLR2025 Spotlight https://agenttrek.github.io | null | null | null | null | null | null | null | null | null |
2,412.09612 | Olympus: A Universal Task Router for Computer Vision Tasks | ['Yuanze Lin', 'Yunsheng Li', 'Dongdong Chen', 'Weijian Xu', 'Ronald Clark', 'Philip H. S. Torr'] | ['cs.CV', 'cs.AI', 'cs.CL'] | We introduce Olympus, a new approach that transforms Multimodal Large
Language Models (MLLMs) into a unified framework capable of handling a wide
array of computer vision tasks. Utilizing a controller MLLM, Olympus delegates
over 20 specialized tasks across images, videos, and 3D objects to dedicated
modules. This inst... | 2024-12-12T18:59:40Z | Accepted to CVPR 2025, Project webpage:
http://yuanze-lin.me/Olympus_page/ | null | null | Olympus: A Universal Task Router for Computer Vision Tasks | ['Yuanze Lin', 'Yunsheng Li', 'Dongdong Chen', 'Weijian Xu', 'Ronald Clark', 'Philip Torr'] | 2,024 | arXiv.org | 1 | 94 | ['Computer Science'] |
2,412.09613 | PVC: Progressive Visual Token Compression for Unified Image and Video
Processing in Large Vision-Language Models | ['Chenyu Yang', 'Xuan Dong', 'Xizhou Zhu', 'Weijie Su', 'Jiahao Wang', 'Hao Tian', 'Zhe Chen', 'Wenhai Wang', 'Lewei Lu', 'Jifeng Dai'] | ['cs.CV'] | Large Vision-Language Models (VLMs) have been extended to understand both
images and videos. Visual token compression is leveraged to reduce the
considerable token length of visual inputs. To meet the needs of different
tasks, existing high-performance models usually process images and videos
separately with different ... | 2024-12-12T18:59:40Z | null | null | null | PVC: Progressive Visual Token Compression for Unified Image and Video Processing in Large Vision-Language Models | ['Chenyu Yang', 'Xuan Dong', 'Xizhou Zhu', 'Weijie Su', 'Jiahao Wang', 'Hao Tian', 'Zhe Chen', 'Wenhai Wang', 'Lewei Lu', 'Jifeng Dai'] | 2,024 | arXiv.org | 4 | 0 | ['Computer Science'] |
2,412.09616 | V2PE: Improving Multimodal Long-Context Capability of Vision-Language
Models with Variable Visual Position Encoding | ['Junqi Ge', 'Ziyi Chen', 'Jintao Lin', 'Jinguo Zhu', 'Xihui Liu', 'Jifeng Dai', 'Xizhou Zhu'] | ['cs.CV'] | Vision-Language Models (VLMs) have shown promising capabilities in handling
various multimodal tasks, yet they struggle in long-context scenarios,
particularly in tasks involving videos, high-resolution images, or lengthy
image-text documents. In our work, we first conduct an empirical analysis of
the long-context capa... | 2024-12-12T18:59:46Z | The code and models will be available at
https://github.com/OpenGVLab/V2PE | null | null | V2PE: Improving Multimodal Long-Context Capability of Vision-Language Models with Variable Visual Position Encoding | ['Junqi Ge', 'Ziyi Chen', 'Jintao Lin', 'Jinguo Zhu', 'Xihui Liu', 'Jifeng Dai', 'Xizhou Zhu'] | 2,024 | arXiv.org | 7 | 0 | ['Computer Science'] |
2,412.09618 | EasyRef: Omni-Generalized Group Image Reference for Diffusion Models via
Multimodal LLM | ['Zhuofan Zong', 'Dongzhi Jiang', 'Bingqi Ma', 'Guanglu Song', 'Hao Shao', 'Dazhong Shen', 'Yu Liu', 'Hongsheng Li'] | ['cs.CV'] | Significant achievements in personalization of diffusion models have been
witnessed. Conventional tuning-free methods mostly encode multiple reference
images by averaging their image embeddings as the injection condition, but such
an image-independent operation cannot perform interaction among images to
capture consist... | 2024-12-12T18:59:48Z | Tech report | null | null | EasyRef: Omni-Generalized Group Image Reference for Diffusion Models via Multimodal LLM | ['Zhuofan Zong', 'Dongzhi Jiang', 'Bingqi Ma', 'Guanglu Song', 'Hao Shao', 'Dazhong Shen', 'Yu Liu', 'Hongsheng Li'] | 2,024 | arXiv.org | 8 | 0 | ['Computer Science'] |
2,412.0962 | Learning Camera Movement Control from Real-World Drone Videos | ['Yunzhong Hou', 'Liang Zheng', 'Philip Torr'] | ['cs.CV', 'cs.RO'] | This study seeks to automate camera movement control for filming existing
subjects into attractive videos, contrasting with the creation of non-existent
content by directly generating the pixels. We select drone videos as our test
case due to their rich and challenging motion patterns, distinctive viewing
angles, and p... | 2024-12-12T18:59:54Z | null | null | null | Learning Camera Movement Control from Real-World Drone Videos | ['Yunzhong Hou', 'Liang Zheng', 'Philip H. S. Torr'] | 2,024 | arXiv.org | 4 | 0 | ['Computer Science'] |
2,412.09624 | GenEx: Generating an Explorable World | ['Taiming Lu', 'Tianmin Shu', 'Junfei Xiao', 'Luoxin Ye', 'Jiahao Wang', 'Cheng Peng', 'Chen Wei', 'Daniel Khashabi', 'Rama Chellappa', 'Alan Yuille', 'Jieneng Chen'] | ['cs.CV', 'cs.RO'] | Understanding, navigating, and exploring the 3D physical real world has long
been a central challenge in the development of artificial intelligence. In this
work, we take a step toward this goal by introducing GenEx, a system capable of
planning complex embodied world exploration, guided by its generative
imagination t... | 2024-12-12T18:59:57Z | Website: GenEx.world | null | null | GenEx: Generating an Explorable World | ['Taiming Lu', 'Tianmin Shu', 'Junfei Xiao', 'Luoxin Ye', 'Jiahao Wang', 'Cheng Peng', 'Chen Wei', 'Daniel Khashabi', 'Rama Chellappa', 'Alan L. Yuille', 'Jieneng Chen'] | 2,024 | arXiv.org | 5 | 24 | ['Computer Science'] |
2,412.09754 | ViCaS: A Dataset for Combining Holistic and Pixel-level Video
Understanding using Captions with Grounded Segmentation | ['Ali Athar', 'Xueqing Deng', 'Liang-Chieh Chen'] | ['cs.CV'] | Recent advances in multimodal large language models (MLLMs) have expanded
research in video understanding, primarily focusing on high-level tasks such as
video captioning and question-answering. Meanwhile, a smaller body of work
addresses dense, pixel-precise segmentation tasks, which typically involve
category-guided ... | 2024-12-12T23:10:54Z | Accepted to CVPR 2025. Project page:
https://ali2500.github.io/vicas-project/ | null | null | ViCaS: A Dataset for Combining Holistic and Pixel-level Video Understanding using Captions with Grounded Segmentation | ['Ali Athar', 'Xueqing Deng', 'Liang-Chieh Chen'] | 2,024 | arXiv.org | 5 | 131 | ['Computer Science'] |
2,412.09818 | MERaLiON-AudioLLM: Bridging Audio and Language with Large Language
Models | ['Yingxu He', 'Zhuohan Liu', 'Shuo Sun', 'Bin Wang', 'Wenyu Zhang', 'Xunlong Zou', 'Nancy F. Chen', 'Ai Ti Aw'] | ['cs.CL', 'cs.AI'] | We introduce MERaLiON-AudioLLM (Multimodal Empathetic Reasoning and Learning
in One Network), the first speech-text model tailored for Singapore's
multilingual and multicultural landscape. Developed under the National Large
Language Models Funding Initiative, Singapore, MERaLiON-AudioLLM integrates
advanced speech and ... | 2024-12-13T03:15:05Z | https://huggingface.co/MERaLiON/MERaLiON-AudioLLM-Whisper-SEA-LION | null | null | null | null | null | null | null | null | null |
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