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2,412.17153 | Distilled Decoding 1: One-step Sampling of Image Auto-regressive Models
with Flow Matching | ['Enshu Liu', 'Xuefei Ning', 'Yu Wang', 'Zinan Lin'] | ['cs.CV', 'cs.LG'] | Autoregressive (AR) models have achieved state-of-the-art performance in text
and image generation but suffer from slow generation due to the token-by-token
process. We ask an ambitious question: can a pre-trained AR model be adapted to
generate outputs in just one or two steps? If successful, this would
significantly ... | 2024-12-22T20:21:54Z | null | null | null | null | null | null | null | null | null | null |
2,412.17295 | Friends-MMC: A Dataset for Multi-modal Multi-party Conversation
Understanding | ['Yueqian Wang', 'Xiaojun Meng', 'Yuxuan Wang', 'Jianxin Liang', 'Qun Liu', 'Dongyan Zhao'] | ['cs.CL'] | Multi-modal multi-party conversation (MMC) is a less studied yet important
topic of research due to that it well fits real-world scenarios and thus
potentially has more widely-used applications. Compared with the traditional
multi-modal conversations, MMC requires stronger character-centered
understanding abilities as ... | 2024-12-23T05:32:48Z | Published at AAAI 2025 | null | null | Friends-MMC: A Dataset for Multi-modal Multi-party Conversation Understanding | ['Yueqian Wang', 'Xiaojun Meng', 'Yuxuan Wang', 'Jianxin Liang', 'Qun Liu', 'Dongyan Zhao'] | 2,024 | AAAI Conference on Artificial Intelligence | 1 | 35 | ['Computer Science'] |
2,412.17364 | Efficient fine-tuning methodology of text embedding models for
information retrieval: contrastive learning penalty (clp) | ['Jeongsu Yu'] | ['cs.IR', 'cs.AI', '68T50, 68P20', 'H.3.3; I.2.7'] | Text embedding models play a crucial role in natural language processing,
particularly in information retrieval, and their importance is further
highlighted with the recent utilization of RAG (Retrieval- Augmented
Generation). This study presents an efficient fine-tuning methodology
encompassing data selection, loss fu... | 2024-12-23T07:55:22Z | null | null | null | null | null | null | null | null | null | null |
2,412.17395 | WarriorCoder: Learning from Expert Battles to Augment Code Large
Language Models | ['Huawen Feng', 'Pu Zhao', 'Qingfeng Sun', 'Can Xu', 'Fangkai Yang', 'Lu Wang', 'Qianli Ma', 'Qingwei Lin', 'Saravan Rajmohan', 'Dongmei Zhang', 'Qi Zhang'] | ['cs.CL'] | Despite recent progress achieved by code large language models (LLMs), their
remarkable abilities are largely dependent on fine-tuning on the high-quality
data, posing challenges for data collection and annotation. To address this,
current methods often design various data flywheels to collect complex code
instructions... | 2024-12-23T08:47:42Z | null | null | null | null | null | null | null | null | null | null |
2,412.17417 | Multimodal Preference Data Synthetic Alignment with Reward Model | ['Robert Wijaya', 'Ngoc-Bao Nguyen', 'Ngai-Man Cheung'] | ['cs.CV'] | Multimodal large language models (MLLMs) have significantly advanced tasks
like caption generation and visual question answering by integrating visual and
textual data. However, they sometimes produce misleading or hallucinate content
due to discrepancies between their pre-training data and real user prompts.
Existing ... | 2024-12-23T09:29:40Z | Project Page: https://pds-dpo.github.io/ | null | null | null | null | null | null | null | null | null |
2,412.17449 | Applying LLM and Topic Modelling in Psychotherapeutic Contexts | ['Alexander Vanin', 'Vadim Bolshev', 'Anastasia Panfilova'] | ['cs.LG', 'cs.AI', 'I.2.7, J.4'] | This study explores the use of Large language models to analyze therapist
remarks in a psychotherapeutic setting. The paper focuses on the application of
BERTopic, a machine learning-based topic modeling tool, to the dialogue of two
different groups of therapists (classical and modern), which makes it possible
to ident... | 2024-12-23T10:14:32Z | 18 pages, 4 figures | null | null | null | null | null | null | null | null | null |
2,412.17498 | DRT: Deep Reasoning Translation via Long Chain-of-Thought | ['Jiaan Wang', 'Fandong Meng', 'Yunlong Liang', 'Jie Zhou'] | ['cs.CL', 'cs.AI'] | Recently, O1-like models have emerged as representative examples,
illustrating the effectiveness of long chain-of-thought (CoT) in reasoning
tasks such as math and coding tasks. In this paper, we introduce DRT, an
attempt to bring the success of long CoT to neural machine translation (MT).
Specifically, in view of the ... | 2024-12-23T11:55:33Z | null | null | null | null | null | null | null | null | null | null |
2,412.17596 | LiveIdeaBench: Evaluating LLMs' Divergent Thinking for Scientific Idea
Generation with Minimal Context | ['Kai Ruan', 'Xuan Wang', 'Jixiang Hong', 'Peng Wang', 'Yang Liu', 'Hao Sun'] | ['cs.CL', 'cs.AI'] | While Large Language Models (LLMs) demonstrate remarkable capabilities in
scientific tasks such as literature analysis and experimental design (e.g.,
accurately extracting key findings from papers or generating coherent
experimental procedures), existing evaluation benchmarks primarily assess
performance using rich con... | 2024-12-23T14:13:44Z | Updated manuscript and title | null | null | null | null | null | null | null | null | null |
2,412.17606 | SBS Figures: Pre-training Figure QA from Stage-by-Stage Synthesized
Images | ['Risa Shinoda', 'Kuniaki Saito', 'Shohei Tanaka', 'Tosho Hirasawa', 'Yoshitaka Ushiku'] | ['cs.CV'] | Building a large-scale figure QA dataset requires a considerable amount of
work, from gathering and selecting figures to extracting attributes like text,
numbers, and colors, and generating QAs. Although recent developments in LLMs
have led to efforts to synthesize figures, most of these focus primarily on QA
generatio... | 2024-12-23T14:25:33Z | AAAI-25 Workshop on Document Understanding and Intelligence. Dataset
and code: https://github.com/omron-sinicx/SBSFigures | null | null | null | null | null | null | null | null | null |
2,412.17644 | DreamFit: Garment-Centric Human Generation via a Lightweight
Anything-Dressing Encoder | ['Ente Lin', 'Xujie Zhang', 'Fuwei Zhao', 'Yuxuan Luo', 'Xin Dong', 'Long Zeng', 'Xiaodan Liang'] | ['cs.CV'] | Diffusion models for garment-centric human generation from text or image
prompts have garnered emerging attention for their great application potential.
However, existing methods often face a dilemma: lightweight approaches, such as
adapters, are prone to generate inconsistent textures; while finetune-based
methods inv... | 2024-12-23T15:21:28Z | Accepted at AAAI 2025 | null | null | null | null | null | null | null | null | null |
2,412.17726 | VidTwin: Video VAE with Decoupled Structure and Dynamics | ['Yuchi Wang', 'Junliang Guo', 'Xinyi Xie', 'Tianyu He', 'Xu Sun', 'Jiang Bian'] | ['cs.CV', 'cs.AI', 'cs.LG'] | Recent advancements in video autoencoders (Video AEs) have significantly
improved the quality and efficiency of video generation. In this paper, we
propose a novel and compact video autoencoder, VidTwin, that decouples video
into two distinct latent spaces: Structure latent vectors, which capture
overall content and gl... | 2024-12-23T17:16:58Z | Accepted by CVPR 2025; Project page: https://vidtwin.github.io/;
Code: https://github.com/microsoft/VidTok/tree/main/vidtwin | null | null | null | null | null | null | null | null | null |
2,412.17743 | YuLan-Mini: An Open Data-efficient Language Model | ['Yiwen Hu', 'Huatong Song', 'Jia Deng', 'Jiapeng Wang', 'Jie Chen', 'Kun Zhou', 'Yutao Zhu', 'Jinhao Jiang', 'Zican Dong', 'Wayne Xin Zhao', 'Ji-Rong Wen'] | ['cs.CL'] | Effective pre-training of large language models (LLMs) has been challenging
due to the immense resource demands and the complexity of the technical
processes involved. This paper presents a detailed technical report on
YuLan-Mini, a highly capable base model with 2.42B parameters that achieves
top-tier performance amon... | 2024-12-23T17:47:53Z | null | null | null | null | null | null | null | null | null | null |
2,412.17762 | The Superposition of Diffusion Models Using the Itô Density Estimator | ['Marta Skreta', 'Lazar Atanackovic', 'Avishek Joey Bose', 'Alexander Tong', 'Kirill Neklyudov'] | ['cs.LG'] | The Cambrian explosion of easily accessible pre-trained diffusion models
suggests a demand for methods that combine multiple different pre-trained
diffusion models without incurring the significant computational burden of
re-training a larger combined model. In this paper, we cast the problem of
combining multiple pre-... | 2024-12-23T18:18:07Z | Accepted as a Spotlight Presentation at the International Conference
on Learning Representations 2025 | null | null | The Superposition of Diffusion Models Using the Itô Density Estimator | ['Marta Skreta', 'Lazar Atanackovic', 'A. Bose', 'Alexander Tong', 'Kirill Neklyudov'] | 2,024 | arXiv.org | 12 | 0 | ['Computer Science'] |
2,412.1778 | PepTune: De Novo Generation of Therapeutic Peptides with
Multi-Objective-Guided Discrete Diffusion | ['Sophia Tang', 'Yinuo Zhang', 'Pranam Chatterjee'] | ['q-bio.BM', 'cs.AI'] | We present PepTune, a multi-objective discrete diffusion model for
simultaneous generation and optimization of therapeutic peptide SMILES. Built
on the Masked Discrete Language Model (MDLM) framework, PepTune ensures valid
peptide structures with a novel bond-dependent masking schedule and invalid
loss function. To gui... | 2024-12-23T18:38:49Z | Published at ICML 2025. (Proceedings of the 42nd International
Conference on Machine Learning, Vancouver, Canada) | null | null | null | null | null | null | null | null | null |
2,412.178 | Comprehensive Multi-Modal Prototypes are Simple and Effective
Classifiers for Vast-Vocabulary Object Detection | ['Yitong Chen', 'Wenhao Yao', 'Lingchen Meng', 'Sihong Wu', 'Zuxuan Wu', 'Yu-Gang Jiang'] | ['cs.CV'] | Enabling models to recognize vast open-world categories has been a
longstanding pursuit in object detection. By leveraging the generalization
capabilities of vision-language models, current open-world detectors can
recognize a broader range of vocabularies, despite being trained on limited
categories. However, when the... | 2024-12-23T18:57:43Z | Code is available at https://github.com/Row11n/Prova/tree/main | null | null | null | null | null | null | null | null | null |
2,412.17933 | BenCzechMark : A Czech-centric Multitask and Multimetric Benchmark for
Large Language Models with Duel Scoring Mechanism | ['Martin Fajcik', 'Martin Docekal', 'Jan Dolezal', 'Karel Ondrej', 'Karel Beneš', 'Jan Kapsa', 'Pavel Smrz', 'Alexander Polok', 'Michal Hradis', 'Zuzana Neverilova', 'Ales Horak', 'Radoslav Sabol', 'Michal Stefanik', 'Adam Jirkovsky', 'David Adamczyk', 'Petr Hyner', 'Jan Hula', 'Hynek Kydlicek'] | ['cs.CL', 'cs.AI'] | We present BenCzechMark (BCM), the first comprehensive Czech language
benchmark designed for large language models, offering diverse tasks, multiple
task formats, and multiple evaluation metrics. Its duel scoring system is
grounded in statistical significance theory and uses aggregation across tasks
inspired by social ... | 2024-12-23T19:45:20Z | Accepted to TACL | null | null | BenCzechMark : A Czech-centric Multitask and Multimetric Benchmark for Large Language Models with Duel Scoring Mechanism | ['Martin Fajcik', 'Martin Docekal', 'Jan Dolezal', 'Karel Ondrej', 'Karel Benevs', 'Jan Kapsa', 'Pavel Smrz', 'Alexander Polok', 'Michal Hradis', 'Zuzana Neverilova', 'Aleš Horák', 'Radoslav Sabol', 'Michal Stefanik', 'Adam Jirkovský', 'D. Adamczyk', 'Petr Hyner', 'Jan Hula', 'Hynek Kydlícek'] | 2,024 | arXiv.org | 2 | 91 | ['Computer Science'] |
2,412.18148 | Are We in the AI-Generated Text World Already? Quantifying and
Monitoring AIGT on Social Media | ['Zhen Sun', 'Zongmin Zhang', 'Xinyue Shen', 'Ziyi Zhang', 'Yule Liu', 'Michael Backes', 'Yang Zhang', 'Xinlei He'] | ['cs.AI', 'cs.CL', 'cs.CR', 'cs.SI'] | Social media platforms are experiencing a growing presence of AI-Generated
Texts (AIGTs). However, the misuse of AIGTs could have profound implications
for public opinion, such as spreading misinformation and manipulating
narratives. Despite its importance, it remains unclear how prevalent AIGTs are
on social media. To... | 2024-12-24T04:04:54Z | Accepted at ACL 2025 Main Conference. 29 pages, 21 figures, 12 tables | null | null | Are We in the AI-Generated Text World Already? Quantifying and Monitoring AIGT on Social Media | ['Zhen Sun', 'Zongmin Zhang', 'Xinyue Shen', 'Ziyi Zhang', 'Yule Liu', 'Michael Backes', 'Yang Zhang', 'Xinlei He'] | 2,024 | arXiv.org | 8 | 60 | ['Computer Science'] |
2,412.18165 | Parallel Neural Computing for Scene Understanding from LiDAR Perception
in Autonomous Racing | ['Suwesh Prasad Sah'] | ['cs.CV'] | Autonomous driving in high-speed racing, as opposed to urban environments,
presents significant challenges in scene understanding due to rapid changes in
the track environment. Traditional sequential network approaches may struggle
to meet the real-time knowledge and decision-making demands of an autonomous
agent cover... | 2024-12-24T04:56:32Z | IEEE/ISED 2024 | 12th International Conference on Intelligent Systems and Embedded
Design (ISED-2024) | 10.1109/ISED63599.2024.10956572 | null | null | null | null | null | null | null |
2,412.18319 | Mulberry: Empowering MLLM with o1-like Reasoning and Reflection via
Collective Monte Carlo Tree Search | ['Huanjin Yao', 'Jiaxing Huang', 'Wenhao Wu', 'Jingyi Zhang', 'Yibo Wang', 'Shunyu Liu', 'Yingjie Wang', 'Yuxin Song', 'Haocheng Feng', 'Li Shen', 'Dacheng Tao'] | ['cs.CV', 'cs.AI'] | In this work, we aim to develop an MLLM that understands and solves questions
by learning to create each intermediate step of the reasoning involved till the
final answer. To this end, we propose Collective Monte Carlo Tree Search
(CoMCTS), a new learning-to-reason method for MLLMs, which introduces the
concept of coll... | 2024-12-24T10:07:51Z | Technical report | null | null | Mulberry: Empowering MLLM with o1-like Reasoning and Reflection via Collective Monte Carlo Tree Search | ['Huanjin Yao', 'Jiaxing Huang', 'Wenhao Wu', 'Jingyi Zhang', 'Yibo Wang', 'Shunyu Liu', 'Yingjie Wang', 'Yuxin Song', 'Haocheng Feng', 'Li Shen', 'Dacheng Tao'] | 2,024 | arXiv.org | 54 | 79 | ['Computer Science'] |
2,412.1845 | 3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D
Scene Understanding | ['Tatiana Zemskova', 'Dmitry Yudin'] | ['cs.CV'] | A 3D scene graph represents a compact scene model, storing information about
the objects and the semantic relationships between them, making its use
promising for robotic tasks. When interacting with a user, an embodied
intelligent agent should be capable of responding to various queries about the
scene formulated in n... | 2024-12-24T14:21:58Z | null | null | null | 3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding | ['T. Zemskova', 'Dmitry A. Yudin'] | 2,024 | arXiv.org | 4 | 0 | ['Computer Science'] |
2,412.18525 | Explanatory Instructions: Towards Unified Vision Tasks Understanding and
Zero-shot Generalization | ['Yang Shen', 'Xiu-Shen Wei', 'Yifan Sun', 'Yuxin Song', 'Tao Yuan', 'Jian Jin', 'Heyang Xu', 'Yazhou Yao', 'Errui Ding'] | ['cs.CV'] | Computer Vision (CV) has yet to fully achieve the zero-shot task
generalization observed in Natural Language Processing (NLP), despite following
many of the milestones established in NLP, such as large transformer models,
extensive pre-training, and the auto-regression paradigm, among others. In this
paper, we explore ... | 2024-12-24T16:08:25Z | ICML'25, 44 pages | null | null | null | null | null | null | null | null | null |
2,412.18552 | Distilling Fine-grained Sentiment Understanding from Large Language
Models | ['Yice Zhang', 'Guangyu Xie', 'Hongling Xu', 'Kaiheng Hou', 'Jianzhu Bao', 'Qianlong Wang', 'Shiwei Chen', 'Ruifeng Xu'] | ['cs.CL'] | Fine-grained sentiment analysis (FSA) aims to extract and summarize user
opinions from vast opinionated text. Recent studies demonstrate that large
language models (LLMs) possess exceptional sentiment understanding
capabilities. However, directly deploying LLMs for FSA applications incurs high
inference costs. Therefor... | 2024-12-24T17:05:26Z | null | null | null | null | null | null | null | null | null | null |
2,412.18565 | 3DEnhancer: Consistent Multi-View Diffusion for 3D Enhancement | ['Yihang Luo', 'Shangchen Zhou', 'Yushi Lan', 'Xingang Pan', 'Chen Change Loy'] | ['cs.CV'] | Despite advances in neural rendering, due to the scarcity of high-quality 3D
datasets and the inherent limitations of multi-view diffusion models, view
synthesis and 3D model generation are restricted to low resolutions with
suboptimal multi-view consistency. In this study, we present a novel 3D
enhancement pipeline, d... | 2024-12-24T17:36:34Z | Project page: https://yihangluo.com/projects/3DEnhancer | null | null | 3DEnhancer: Consistent Multi-View Diffusion for 3D Enhancement | ['Yihang Luo', 'Shangchen Zhou', 'Yushi Lan', 'Xingang Pan', 'Chen Change Loy'] | 2,024 | arXiv.org | 0 | 95 | ['Computer Science'] |
2,412.18605 | Orient Anything: Learning Robust Object Orientation Estimation from
Rendering 3D Models | ['Zehan Wang', 'Ziang Zhang', 'Tianyu Pang', 'Chao Du', 'Hengshuang Zhao', 'Zhou Zhao'] | ['cs.CV'] | Orientation is a key attribute of objects, crucial for understanding their
spatial pose and arrangement in images. However, practical solutions for
accurate orientation estimation from a single image remain underexplored. In
this work, we introduce Orient Anything, the first expert and foundational
model designed to es... | 2024-12-24T18:58:43Z | Project Page: https://orient-anything.github.io/ | null | null | Orient Anything: Learning Robust Object Orientation Estimation from Rendering 3D Models | ['Zehan Wang', 'Ziang Zhang', 'Tianyu Pang', 'Chao Du', 'Hengshuang Zhao', 'Zhou Zhao'] | 2,024 | arXiv.org | 10 | 0 | ['Computer Science'] |
2,412.18609 | Video-Panda: Parameter-efficient Alignment for Encoder-free
Video-Language Models | ['Jinhui Yi', 'Syed Talal Wasim', 'Yanan Luo', 'Muzammal Naseer', 'Juergen Gall'] | ['cs.CV'] | We present an efficient encoder-free approach for video-language
understanding that achieves competitive performance while significantly
reducing computational overhead. Current video-language models typically rely
on heavyweight image encoders (300M-1.1B parameters) or video encoders (1B-1.4B
parameters), creating a s... | 2024-12-24T18:59:56Z | CVPR 2025 camera-ready version | null | null | Video-Panda: Parameter-efficient Alignment for Encoder-free Video-Language Models | ['Jinhui Yi', 'Syed Talal Wasim', 'Yanan Luo', 'Muzammal Naseer', 'Juergen Gall'] | 2,024 | arXiv.org | 0 | 53 | ['Computer Science'] |
2,412.1886 | Bootstrap Your Own Context Length | ['Liang Wang', 'Nan Yang', 'Xingxing Zhang', 'Xiaolong Huang', 'Furu Wei'] | ['cs.CL', 'cs.IR'] | We introduce a bootstrapping approach to train long-context language models
by exploiting their short-context capabilities only. Our method utilizes a
simple agent workflow to synthesize diverse long-context instruction tuning
data, thereby eliminating the necessity for manual data collection and
annotation. The propos... | 2024-12-25T10:08:54Z | 19 pages | null | null | null | null | null | null | null | null | null |
2,412.18925 | HuatuoGPT-o1, Towards Medical Complex Reasoning with LLMs | ['Junying Chen', 'Zhenyang Cai', 'Ke Ji', 'Xidong Wang', 'Wanlong Liu', 'Rongsheng Wang', 'Jianye Hou', 'Benyou Wang'] | ['cs.CL', 'cs.AI', 'cs.LG'] | The breakthrough of OpenAI o1 highlights the potential of enhancing reasoning
to improve LLM. Yet, most research in reasoning has focused on mathematical
tasks, leaving domains like medicine underexplored. The medical domain, though
distinct from mathematics, also demands robust reasoning to provide reliable
answers, g... | 2024-12-25T15:12:34Z | null | null | null | null | null | null | null | null | null | null |
2,412.18928 | UNIC-Adapter: Unified Image-instruction Adapter with Multi-modal
Transformer for Image Generation | ['Lunhao Duan', 'Shanshan Zhao', 'Wenjun Yan', 'Yinglun Li', 'Qing-Guo Chen', 'Zhao Xu', 'Weihua Luo', 'Kaifu Zhang', 'Mingming Gong', 'Gui-Song Xia'] | ['cs.CV', 'cs.LG'] | Recently, text-to-image generation models have achieved remarkable
advancements, particularly with diffusion models facilitating high-quality
image synthesis from textual descriptions. However, these models often struggle
with achieving precise control over pixel-level layouts, object appearances,
and global styles whe... | 2024-12-25T15:19:02Z | null | null | null | null | null | null | null | null | null | null |
2,412.18945 | Single Trajectory Distillation for Accelerating Image and Video Style
Transfer | ['Sijie Xu', 'Runqi Wang', 'Wei Zhu', 'Dejia Song', 'Nemo Chen', 'Xu Tang', 'Yao Hu'] | ['cs.CV'] | Diffusion-based stylization methods typically denoise from a specific partial
noise state for image-to-image and video-to-video tasks. This multi-step
diffusion process is computationally expensive and hinders real-world
application. A promising solution to speed up the process is to obtain few-step
consistency models ... | 2024-12-25T16:40:23Z | null | null | null | Single Trajectory Distillation for Accelerating Image and Video Style Transfer | ['Sijie Xu', 'Runqi Wang', 'Wei Zhu', 'Dejia Song', 'Nemo Chen', 'Xu Tang', 'Yao Hu'] | 2,024 | arXiv.org | 0 | 39 | ['Computer Science'] |
2,412.19048 | Jasper and Stella: distillation of SOTA embedding models | ['Dun Zhang', 'Jiacheng Li', 'Ziyang Zeng', 'Fulong Wang'] | ['cs.IR'] | A crucial component in many deep learning applications, such as Frequently
Asked Questions (FAQ) and Retrieval-Augmented Generation (RAG), is dense
retrieval. In this process, embedding models transform raw text into numerical
vectors. However, the embedding models that currently excel on text embedding
benchmarks, lik... | 2024-12-26T04:05:28Z | 7 pages, 1 figure | null | null | Jasper and Stella: distillation of SOTA embedding models | ['Dun Zhang', 'Jiacheng Li', 'Ziyang Zeng', 'Fulong Wang'] | 2,024 | arXiv.org | 35 | 0 | ['Computer Science'] |
2,412.19326 | Task Preference Optimization: Improving Multimodal Large Language Models
with Vision Task Alignment | ['Ziang Yan', 'Zhilin Li', 'Yinan He', 'Chenting Wang', 'Kunchang Li', 'Xinhao Li', 'Xiangyu Zeng', 'Zilei Wang', 'Yali Wang', 'Yu Qiao', 'Limin Wang', 'Yi Wang'] | ['cs.CV'] | Current multimodal large language models (MLLMs) struggle with fine-grained
or precise understanding of visuals although they give comprehensive perception
and reasoning in a spectrum of vision applications. Recent studies either
develop tool-using or unify specific visual tasks into the autoregressive
framework, often... | 2024-12-26T18:56:05Z | CVPR2025 | null | null | null | null | null | null | null | null | null |
2,412.19412 | MINIMA: Modality Invariant Image Matching | ['Jiangwei Ren', 'Xingyu Jiang', 'Zizhuo Li', 'Dingkang Liang', 'Xin Zhou', 'Xiang Bai'] | ['cs.CV'] | Image matching for both cross-view and cross-modality plays a critical role
in multimodal perception. In practice, the modality gap caused by different
imaging systems/styles poses great challenges to the matching task. Existing
works try to extract invariant features for specific modalities and train on
limited datase... | 2024-12-27T02:39:50Z | Accepted to CVPR 2025. The dataset and code are available at
https://github.com/LSXI7/MINIMA | null | null | null | null | null | null | null | null | null |
2,412.19437 | DeepSeek-V3 Technical Report | ['DeepSeek-AI', 'Aixin Liu', 'Bei Feng', 'Bing Xue', 'Bingxuan Wang', 'Bochao Wu', 'Chengda Lu', 'Chenggang Zhao', 'Chengqi Deng', 'Chenyu Zhang', 'Chong Ruan', 'Damai Dai', 'Daya Guo', 'Dejian Yang', 'Deli Chen', 'Dongjie Ji', 'Erhang Li', 'Fangyun Lin', 'Fucong Dai', 'Fuli Luo', 'Guangbo Hao', 'Guanting Chen', 'Guowe... | ['cs.CL', 'cs.AI'] | We present DeepSeek-V3, a strong Mixture-of-Experts (MoE) language model with
671B total parameters with 37B activated for each token. To achieve efficient
inference and cost-effective training, DeepSeek-V3 adopts Multi-head Latent
Attention (MLA) and DeepSeekMoE architectures, which were thoroughly validated
in DeepSe... | 2024-12-27T04:03:16Z | null | null | null | DeepSeek-V3 Technical Report | ['DeepSeek-AI', 'A. Liu', 'Bei Feng', 'Bing Xue', 'Bing-Li Wang', 'Bochao Wu', 'Chengda Lu', 'Chenggang Zhao', 'C. Deng', 'Chenyu Zhang', 'C. Ruan', 'Damai Dai', 'Daya Guo', 'Dejian Yang', 'Deli Chen', 'Dong-Li Ji', 'Erhang Li', 'Fangyun Lin', 'Fucong Dai', 'Fuli Luo', 'Guangbo Hao', 'Guanting Chen', 'Guowei Li', 'H. Z... | 2,024 | arXiv.org | 821 | 0 | ['Computer Science'] |
2,412.19505 | DrivingWorld: Constructing World Model for Autonomous Driving via Video
GPT | ['Xiaotao Hu', 'Wei Yin', 'Mingkai Jia', 'Junyuan Deng', 'Xiaoyang Guo', 'Qian Zhang', 'Xiaoxiao Long', 'Ping Tan'] | ['cs.CV'] | Recent successes in autoregressive (AR) generation models, such as the GPT
series in natural language processing, have motivated efforts to replicate this
success in visual tasks. Some works attempt to extend this approach to
autonomous driving by building video-based world models capable of generating
realistic future... | 2024-12-27T07:44:07Z | null | null | null | DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT | ['Xiaotao Hu', 'Wei Yin', 'Mingkai Jia', 'Junyuan Deng', 'Xiaoyang Guo', 'Qian Zhang', 'Xiaoxiao Long', 'Ping Tan'] | 2,024 | arXiv.org | 14 | 46 | ['Computer Science'] |
2,412.19628 | RecConv: Efficient Recursive Convolutions for Multi-Frequency
Representations | ['Mingshu Zhao', 'Yi Luo', 'Yong Ouyang'] | ['cs.CV'] | Recent advances in vision transformers (ViTs) have demonstrated the advantage
of global modeling capabilities, prompting widespread integration of
large-kernel convolutions for enlarging the effective receptive field (ERF).
However, the quadratic scaling of parameter count and computational complexity
(FLOPs) with resp... | 2024-12-27T13:13:52Z | Tech report; Added supplementary material; | null | null | null | null | null | null | null | null | null |
2,412.19637 | ReNeg: Learning Negative Embedding with Reward Guidance | ['Xiaomin Li', 'Yixuan Liu', 'Takashi Isobe', 'Xu Jia', 'Qinpeng Cui', 'Dong Zhou', 'Dong Li', 'You He', 'Huchuan Lu', 'Zhongdao Wang', 'Emad Barsoum'] | ['cs.CV'] | In text-to-image (T2I) generation applications, negative embeddings have
proven to be a simple yet effective approach for enhancing generation quality.
Typically, these negative embeddings are derived from user-defined negative
prompts, which, while being functional, are not necessarily optimal. In this
paper, we intro... | 2024-12-27T13:31:55Z | Code: https://github.com/AMD-AIG-AIMA/ReNeg | null | null | null | null | null | null | null | null | null |
2,412.19638 | Xmodel-2 Technical Report | ['Wang Qun', 'Liu Yang', 'Lin Qingquan', 'Qu Zhijiu', 'Jiang Ling'] | ['cs.AI'] | Xmodel-2 is a 1.2-billion-parameter large language model designed
specifically for reasoning tasks. Its architecture enables different model
scales to share a unified set of hyperparameters, allowing for extensive
experimentation on smaller models and seamless transfer of optimal
configurations to larger models. To max... | 2024-12-27T13:32:10Z | null | null | null | null | null | null | null | null | null | null |
2,412.19712 | From Elements to Design: A Layered Approach for Automatic Graphic Design
Composition | ['Jiawei Lin', 'Shizhao Sun', 'Danqing Huang', 'Ting Liu', 'Ji Li', 'Jiang Bian'] | ['cs.CV'] | In this work, we investigate automatic design composition from multimodal
graphic elements. Although recent studies have developed various generative
models for graphic design, they usually face the following limitations: they
only focus on certain subtasks and are far from achieving the design
composition task; they d... | 2024-12-27T16:13:08Z | Project Page:
$\href{https://elements2design.github.io/}{\text{elements2design}}$ | null | null | From Elements to Design: A Layered Approach for Automatic Graphic Design Composition | ['Jiawei Lin', 'Shizhao Sun', 'Danqing Huang', 'Ting Liu', 'Ji Li', 'Jiang Bian'] | 2,024 | arXiv.org | 0 | 0 | ['Computer Science'] |
2,412.19723 | OS-Genesis: Automating GUI Agent Trajectory Construction via Reverse
Task Synthesis | ['Qiushi Sun', 'Kanzhi Cheng', 'Zichen Ding', 'Chuanyang Jin', 'Yian Wang', 'Fangzhi Xu', 'Zhenyu Wu', 'Chengyou Jia', 'Liheng Chen', 'Zhoumianze Liu', 'Ben Kao', 'Guohao Li', 'Junxian He', 'Yu Qiao', 'Zhiyong Wu'] | ['cs.AI', 'cs.CL', 'cs.CV', 'cs.HC'] | Graphical User Interface (GUI) agents powered by Vision-Language Models
(VLMs) have demonstrated human-like computer control capability. Despite their
utility in advancing digital automation, a critical bottleneck persists:
collecting high-quality trajectory data for training. Common practices for
collecting such data ... | 2024-12-27T16:21:58Z | ACL 2025 Camera Ready | null | null | OS-Genesis: Automating GUI Agent Trajectory Construction via Reverse Task Synthesis | ['Qiushi Sun', 'Kanzhi Cheng', 'Zichen Ding', 'Chuanyang Jin', 'Yian Wang', 'Fangzhi Xu', 'Zhenyu Wu', 'Chengyou Jia', 'Liheng Chen', 'Zhoumianze Liu', 'Ben Kao', 'Guohao Li', 'Junxian He', 'Yu Qiao', 'Zhiyong Wu'] | 2,024 | arXiv.org | 26 | 54 | ['Computer Science'] |
2,412.20404 | Open-Sora: Democratizing Efficient Video Production for All | ['Zangwei Zheng', 'Xiangyu Peng', 'Tianji Yang', 'Chenhui Shen', 'Shenggui Li', 'Hongxin Liu', 'Yukun Zhou', 'Tianyi Li', 'Yang You'] | ['cs.CV'] | Vision and language are the two foundational senses for humans, and they
build up our cognitive ability and intelligence. While significant
breakthroughs have been made in AI language ability, artificial visual
intelligence, especially the ability to generate and simulate the world we see,
is far lagging behind. To fac... | 2024-12-29T08:52:49Z | null | null | null | null | null | null | null | null | null | null |
2,412.20597 | GliLem: Leveraging GliNER for Contextualized Lemmatization in Estonian | ['Aleksei Dorkin', 'Kairit Sirts'] | ['cs.CL'] | We present GliLem -- a novel hybrid lemmatization system for Estonian that
enhances the highly accurate rule-based morphological analyzer Vabamorf with an
external disambiguation module based on GliNER -- an open vocabulary NER model
that is able to match text spans with text labels in natural language. We
leverage the... | 2024-12-29T22:02:00Z | Accepted to NoDaLiDa/Baltic-HLT 2025. Minor presentation and
formatting fixes | null | null | GliLem: Leveraging GliNER for Contextualized Lemmatization in Estonian | ['Aleksei Dorkin', 'Kairit Sirts'] | 2,024 | arXiv.org | 0 | 29 | ['Computer Science'] |
2,412.21037 | TangoFlux: Super Fast and Faithful Text to Audio Generation with Flow
Matching and Clap-Ranked Preference Optimization | ['Chia-Yu Hung', 'Navonil Majumder', 'Zhifeng Kong', 'Ambuj Mehrish', 'Amir Ali Bagherzadeh', 'Chuan Li', 'Rafael Valle', 'Bryan Catanzaro', 'Soujanya Poria'] | ['cs.SD', 'cs.AI', 'cs.CL', 'eess.AS'] | We introduce TangoFlux, an efficient Text-to-Audio (TTA) generative model
with 515M parameters, capable of generating up to 30 seconds of 44.1kHz audio
in just 3.7 seconds on a single A40 GPU. A key challenge in aligning TTA models
lies in the difficulty of creating preference pairs, as TTA lacks structured
mechanisms ... | 2024-12-30T16:02:44Z | https://tangoflux.github.io/ | null | null | TangoFlux: Super Fast and Faithful Text to Audio Generation with Flow Matching and Clap-Ranked Preference Optimization | ['Chia-Yu Hung', 'Navonil Majumder', 'Zhifeng Kong', 'Ambuj Mehrish', 'Rafael Valle', 'Bryan Catanzaro', 'Soujanya Poria'] | 2,024 | arXiv.org | 10 | 54 | ['Computer Science', 'Engineering'] |
2,412.21139 | Training Software Engineering Agents and Verifiers with SWE-Gym | ['Jiayi Pan', 'Xingyao Wang', 'Graham Neubig', 'Navdeep Jaitly', 'Heng Ji', 'Alane Suhr', 'Yizhe Zhang'] | ['cs.SE', 'cs.CL'] | We present SWE-Gym, the first environment for training real-world software
engineering (SWE) agents. SWE-Gym contains 2,438 real-world Python task
instances, each comprising a codebase with an executable runtime environment,
unit tests, and a task specified in natural language. We use SWE-Gym to train
language model ba... | 2024-12-30T18:15:39Z | Accepted at ICML 2025. Code at https://github.com/SWE-Gym/SWE-Gym | null | null | Training Software Engineering Agents and Verifiers with SWE-Gym | ['Jiayi Pan', 'Xingyao Wang', 'Graham Neubig', 'N. Jaitly', 'Heng Ji', 'Alane Suhr', 'Yizhe Zhang'] | 2,024 | arXiv.org | 50 | 51 | ['Computer Science'] |
2,412.2114 | Facilitating large language model Russian adaptation with Learned
Embedding Propagation | ['Mikhail Tikhomirov', 'Daniil Chernyshev'] | ['cs.CL', 'cs.AI'] | Rapid advancements of large language model (LLM) technologies led to the
introduction of powerful open-source instruction-tuned LLMs that have the same
text generation quality as the state-of-the-art counterparts such as GPT-4.
While the emergence of such models accelerates the adoption of LLM technologies
in sensitive... | 2024-12-30T18:15:45Z | Preprint version of an article published in the Journal of Language
and Education. Copyright held by the owner/author(s). Publication rights
licensed to the Journal of Language and Education | null | null | Facilitating large language model Russian adaptation with Learned Embedding Propagation | ['M. Tikhomirov', 'D. Chernyshev'] | 2,024 | Journal of Language and Education | 1 | 41 | ['Computer Science'] |
2,501.00062 | ELECTRA and GPT-4o: Cost-Effective Partners for Sentiment Analysis | ['James P. Beno'] | ['cs.CL', 'cs.AI', 'I.2.7'] | Bidirectional transformers excel at sentiment analysis, and Large Language
Models (LLM) are effective zero-shot learners. Might they perform better as a
team? This paper explores collaborative approaches between ELECTRA and GPT-4o
for three-way sentiment classification. We fine-tuned (FT) four models (ELECTRA
Base/Larg... | 2024-12-29T05:29:52Z | 19 pages, 4 figures. Source code and data available at
https://github.com/jbeno/sentiment | Proceedings of the 4th International Workshop on
Knowledge-Augmented Methods for Natural Language Processing, Association for
Computational Linguistics, Albuquerque, New Mexico, USA (2025) 18-36 | null | null | null | null | null | null | null | null |
2,501.00114 | DiCoW: Diarization-Conditioned Whisper for Target Speaker Automatic
Speech Recognition | ['Alexander Polok', 'Dominik Klement', 'Martin Kocour', 'Jiangyu Han', 'Federico Landini', 'Bolaji Yusuf', 'Matthew Wiesner', 'Sanjeev Khudanpur', 'Jan Černocký', 'Lukáš Burget'] | ['eess.AS', 'cs.SD'] | Speaker-attributed automatic speech recognition (ASR) in multi-speaker
environments remains a significant challenge, particularly when systems
conditioned on speaker embeddings fail to generalize to unseen speakers. In
this work, we propose Diarization-Conditioned Whisper (DiCoW), a novel approach
to target-speaker ASR... | 2024-12-30T19:24:15Z | null | null | null | null | null | null | null | null | null | null |
2,501.00243 | Cross-Layer Cache Aggregation for Token Reduction in Ultra-Fine-Grained
Image Recognition | ['Edwin Arkel Rios', 'Jansen Christopher Yuanda', 'Vincent Leon Ghanz', 'Cheng-Wei Yu', 'Bo-Cheng Lai', 'Min-Chun Hu'] | ['cs.CV', 'I.2; I.4'] | Ultra-fine-grained image recognition (UFGIR) is a challenging task that
involves classifying images within a macro-category. While traditional FGIR
deals with classifying different species, UFGIR goes beyond by classifying
sub-categories within a species such as cultivars of a plant. In recent times
the usage of Vision... | 2024-12-31T03:19:38Z | Accepted to ICASSP 2025. Main: 5 pages, 4 figures, 1 table | null | null | null | null | null | null | null | null | null |
2,501.00353 | RAG-Instruct: Boosting LLMs with Diverse Retrieval-Augmented
Instructions | ['Wanlong Liu', 'Junying Chen', 'Ke Ji', 'Li Zhou', 'Wenyu Chen', 'Benyou Wang'] | ['cs.CL', 'cs.AI', 'cs.LG'] | Retrieval-Augmented Generation (RAG) has emerged as a key paradigm for
enhancing large language models (LLMs) by incorporating external knowledge.
However, current RAG methods face two limitations: (1) they only cover limited
RAG scenarios. (2) They suffer from limited task diversity due to the lack of a
general RAG da... | 2024-12-31T09:00:51Z | null | null | null | RAG-Instruct: Boosting LLMs with Diverse Retrieval-Augmented Instructions | ['Wanlong Liu', 'Junying Chen', 'Ke Ji', 'Li Zhou', 'Wenyu Chen', 'Benyou Wang'] | 2,024 | arXiv.org | 7 | 0 | ['Computer Science'] |
2,501.00513 | CaReBench: A Fine-Grained Benchmark for Video Captioning and Retrieval | ['Yifan Xu', 'Xinhao Li', 'Yichun Yang', 'Desen Meng', 'Rui Huang', 'Limin Wang'] | ['cs.CV', 'cs.IR', 'cs.LG'] | Video understanding, including video captioning and retrieval, is still a
great challenge for video-language models (VLMs). The existing video retrieval
and caption benchmarks only include short descriptions, limits their ability of
detailed video understanding evaluation. To address this problem, we present
CaReBench,... | 2024-12-31T15:53:50Z | null | null | null | CaReBench: A Fine-Grained Benchmark for Video Captioning and Retrieval | ['Yifan Xu', 'Xinhao Li', 'Yichun Yang', 'Desen Meng', 'Rui Huang', 'Limin Wang'] | 2,024 | null | 0 | 38 | ['Computer Science'] |
2,501.00569 | Probing Visual Language Priors in VLMs | ['Tiange Luo', 'Ang Cao', 'Gunhee Lee', 'Justin Johnson', 'Honglak Lee'] | ['cs.CV', 'cs.LG'] | Despite recent advances in Vision-Language Models (VLMs), they may over-rely
on visual language priors existing in their training data rather than true
visual reasoning. To investigate this, we introduce ViLP, a benchmark featuring
deliberately out-of-distribution images synthesized via image generation models
and out-... | 2024-12-31T17:54:29Z | Project Page: https://vilp-team.github.io/ | null | null | Probing Visual Language Priors in VLMs | ['Tiange Luo', 'Ang Cao', 'Gunhee Lee', 'Justin Johnson', 'Honglak Lee'] | 2,024 | arXiv.org | 2 | 97 | ['Computer Science'] |
2,501.00574 | VideoChat-Flash: Hierarchical Compression for Long-Context Video
Modeling | ['Xinhao Li', 'Yi Wang', 'Jiashuo Yu', 'Xiangyu Zeng', 'Yuhan Zhu', 'Haian Huang', 'Jianfei Gao', 'Kunchang Li', 'Yinan He', 'Chenting Wang', 'Yu Qiao', 'Yali Wang', 'Limin Wang'] | ['cs.CV', 'cs.LG'] | Long-context video modeling is critical for multimodal large language models
(MLLMs), enabling them to process movies, online video streams, and so on.
Despite its advances, handling long videos remains challenging due to the
difficulty in efficiently understanding the extremely long video context. This
paper aims to a... | 2024-12-31T18:01:23Z | null | null | null | null | null | null | null | null | null | null |
2,501.00584 | Online Video Understanding: OVBench and VideoChat-Online | ['Zhenpeng Huang', 'Xinhao Li', 'Jiaqi Li', 'Jing Wang', 'Xiangyu Zeng', 'Cheng Liang', 'Tao Wu', 'Xi Chen', 'Liang Li', 'Limin Wang'] | ['cs.CV', 'cs.LG'] | Multimodal Large Language Models (MLLMs) have significantly progressed in
offline video understanding. However, applying these models to real-world
scenarios, such as autonomous driving and human-computer interaction, presents
unique challenges due to the need for real-time processing of continuous online
video streams... | 2024-12-31T18:17:05Z | CVPR 2025 Camera Ready Version. Project Page:
https://videochat-online.github.io | null | null | Online Video Understanding: OVBench and VideoChat-Online | ['Zhenpeng Huang', 'Xinhao Li', 'Jiaqi Li', 'Jing Wang', 'Xiangyun Zeng', 'Cheng Liang', 'Tao Wu', 'Xi Chen', 'Liang Li', 'Limin Wang'] | 2,024 | Computer Vision and Pattern Recognition | 0 | 63 | ['Computer Science'] |
2,501.00599 | VideoRefer Suite: Advancing Spatial-Temporal Object Understanding with
Video LLM | ['Yuqian Yuan', 'Hang Zhang', 'Wentong Li', 'Zesen Cheng', 'Boqiang Zhang', 'Long Li', 'Xin Li', 'Deli Zhao', 'Wenqiao Zhang', 'Yueting Zhuang', 'Jianke Zhu', 'Lidong Bing'] | ['cs.CV', 'cs.AI', 'cs.LG'] | Video Large Language Models (Video LLMs) have recently exhibited remarkable
capabilities in general video understanding. However, they mainly focus on
holistic comprehension and struggle with capturing fine-grained spatial and
temporal details. Besides, the lack of high-quality object-level video
instruction data and a... | 2024-12-31T18:56:46Z | 17 pages, 14 figures, technical report | null | null | null | null | null | null | null | null | null |
2,501.00656 | 2 OLMo 2 Furious | ['Team OLMo', 'Pete Walsh', 'Luca Soldaini', 'Dirk Groeneveld', 'Kyle Lo', 'Shane Arora', 'Akshita Bhagia', 'Yuling Gu', 'Shengyi Huang', 'Matt Jordan', 'Nathan Lambert', 'Dustin Schwenk', 'Oyvind Tafjord', 'Taira Anderson', 'David Atkinson', 'Faeze Brahman', 'Christopher Clark', 'Pradeep Dasigi', 'Nouha Dziri', 'Micha... | ['cs.CL', 'cs.LG'] | We present OLMo 2, the next generation of our fully open language models.
OLMo 2 includes dense autoregressive models with improved architecture and
training recipe, pretraining data mixtures, and instruction tuning recipes. Our
modified model architecture and training recipe achieve both better training
stability and ... | 2024-12-31T21:55:10Z | Model demo available at playground.allenai.org | null | null | null | null | null | null | null | null | null |
2,501.00658 | Understanding and Mitigating Bottlenecks of State Space Models through
the Lens of Recency and Over-smoothing | ['Peihao Wang', 'Ruisi Cai', 'Yuehao Wang', 'Jiajun Zhu', 'Pragya Srivastava', 'Zhangyang Wang', 'Pan Li'] | ['cs.LG'] | Structured State Space Models (SSMs) have emerged as alternatives to
transformers. While SSMs are often regarded as effective in capturing
long-sequence dependencies, we rigorously demonstrate that they are inherently
limited by strong recency bias. Our empirical studies also reveal that this
bias impairs the models' a... | 2024-12-31T22:06:39Z | International Conference on Learning Representations (ICLR), 2025 | null | null | null | null | null | null | null | null | null |
2,501.00874 | LUSIFER: Language Universal Space Integration for Enhanced Multilingual
Embeddings with Large Language Models | ['Hieu Man', 'Nghia Trung Ngo', 'Viet Dac Lai', 'Ryan A. Rossi', 'Franck Dernoncourt', 'Thien Huu Nguyen'] | ['cs.CL', 'cs.IR'] | Recent advancements in large language models (LLMs) based embedding models
have established new state-of-the-art benchmarks for text embedding tasks,
particularly in dense vector-based retrieval. However, these models
predominantly focus on English, leaving multilingual embedding capabilities
largely unexplored. To add... | 2025-01-01T15:43:07Z | null | null | null | null | null | null | null | null | null | null |
2,501.00895 | Text2Earth: Unlocking Text-driven Remote Sensing Image Generation with a
Global-Scale Dataset and a Foundation Model | ['Chenyang Liu', 'Keyan Chen', 'Rui Zhao', 'Zhengxia Zou', 'Zhenwei Shi'] | ['cs.CV'] | Generative foundation models have advanced large-scale text-driven natural
image generation, becoming a prominent research trend across various vertical
domains. However, in the remote sensing field, there is still a lack of
research on large-scale text-to-image (text2image) generation technology.
Existing remote sensi... | 2025-01-01T16:56:43Z | null | null | null | Text2Earth: Unlocking Text-driven Remote Sensing Image Generation with a Global-Scale Dataset and a Foundation Model | ['Chenyang Liu', 'Ke-Yu Chen', 'Ruiyun Zhao', 'Zhengxia Zou', 'Z. Shi'] | 2,025 | IEEE Geoscience and Remote Sensing Magazine | 12 | 0 | ['Computer Science'] |
2,501.01028 | KaLM-Embedding: Superior Training Data Brings A Stronger Embedding Model | ['Xinshuo Hu', 'Zifei Shan', 'Xinping Zhao', 'Zetian Sun', 'Zhenyu Liu', 'Dongfang Li', 'Shaolin Ye', 'Xinyuan Wei', 'Qian Chen', 'Baotian Hu', 'Haofen Wang', 'Jun Yu', 'Min Zhang'] | ['cs.CL'] | As retrieval-augmented generation prevails in large language models,
embedding models are becoming increasingly crucial. Despite the growing number
of general embedding models, prior work often overlooks the critical role of
training data quality. In this work, we introduce KaLM-Embedding, a general
multilingual embedd... | 2025-01-02T03:17:51Z | Technical Report. 23 pages, 6 figures, 10 tables | null | null | KaLM-Embedding: Superior Training Data Brings A Stronger Embedding Model | ['Xinshuo Hu', 'Zifei Shan', 'Xinping Zhao', 'Zetian Sun', 'Zhenyu Liu', 'Dongfang Li', 'Shaolin Ye', 'Xinyuan Wei', 'Qian Chen', 'Baotian Hu', 'Haofen Wang', 'Jun Yu', 'Min Zhang'] | 2,025 | arXiv.org | 3 | 0 | ['Computer Science'] |
2,501.01034 | Advancing Singlish Understanding: Bridging the Gap with Datasets and
Multimodal Models | ['Bin Wang', 'Xunlong Zou', 'Shuo Sun', 'Wenyu Zhang', 'Yingxu He', 'Zhuohan Liu', 'Chengwei Wei', 'Nancy F. Chen', 'AiTi Aw'] | ['cs.CL', 'cs.SD', 'eess.AS'] | Singlish, a Creole language rooted in English, is a key focus in linguistic
research within multilingual and multicultural contexts. However, its spoken
form remains underexplored, limiting insights into its linguistic structure and
applications. To address this gap, we standardize and annotate the largest
spoken Singl... | 2025-01-02T03:28:52Z | Open-Source: https://github.com/AudioLLMs/Singlish | null | null | Advancing Singlish Understanding: Bridging the Gap with Datasets and Multimodal Models | ['Bin Wang', 'Xunlong Zou', 'Shuo Sun', 'Wenyu Zhang', 'Yingxu He', 'Zhuohan Liu', 'Chengwei Wei', 'Nancy F. Chen', 'AiTi Aw'] | 2,025 | arXiv.org | 4 | 0 | ['Computer Science', 'Engineering'] |
2,501.01054 | Dynamic Scaling of Unit Tests for Code Reward Modeling | ['Zeyao Ma', 'Xiaokang Zhang', 'Jing Zhang', 'Jifan Yu', 'Sijia Luo', 'Jie Tang'] | ['cs.CL', 'cs.SE'] | Current large language models (LLMs) often struggle to produce accurate
responses on the first attempt for complex reasoning tasks like code
generation. Prior research tackles this challenge by generating multiple
candidate solutions and validating them with LLM-generated unit tests. The
execution results of unit tests... | 2025-01-02T04:33:31Z | Homepage: https://code-reward-model.github.io/ | null | null | null | null | null | null | null | null | null |
2,501.01097 | EliGen: Entity-Level Controlled Image Generation with Regional Attention | ['Hong Zhang', 'Zhongjie Duan', 'Xingjun Wang', 'Yingda Chen', 'Yu Zhang'] | ['cs.CV'] | Recent advancements in diffusion models have significantly advanced
text-to-image generation, yet global text prompts alone remain insufficient for
achieving fine-grained control over individual entities within an image. To
address this limitation, we present EliGen, a novel framework for Entity-level
controlled image ... | 2025-01-02T06:46:13Z | null | null | null | EliGen: Entity-Level Controlled Image Generation with Regional Attention | ['Hong Zhang', 'Zhongjie Duan', 'Xingjun Wang', 'Yingda Chen', 'Yu Zhang'] | 2,025 | arXiv.org | 6 | 36 | ['Computer Science'] |
2,501.0132 | SeedVR: Seeding Infinity in Diffusion Transformer Towards Generic Video
Restoration | ['Jianyi Wang', 'Zhijie Lin', 'Meng Wei', 'Yang Zhao', 'Ceyuan Yang', 'Fei Xiao', 'Chen Change Loy', 'Lu Jiang'] | ['cs.CV'] | Video restoration poses non-trivial challenges in maintaining fidelity while
recovering temporally consistent details from unknown degradations in the wild.
Despite recent advances in diffusion-based restoration, these methods often
face limitations in generation capability and sampling efficiency. In this
work, we pre... | 2025-01-02T16:19:48Z | CVPR25 CR ver., add a co-author additionally. Project page:
https://iceclear.github.io/projects/seedvr/ | null | null | SeedVR: Seeding Infinity in Diffusion Transformer Towards Generic Video Restoration | ['Jianyi Wang', 'Zhijie Lin', 'Meng Wei', 'Yang Zhao', 'Ceyuan Yang', 'Chen Change Loy', 'Lu Jiang'] | 2,025 | Computer Vision and Pattern Recognition | 7 | 81 | ['Computer Science'] |
2,501.01423 | Reconstruction vs. Generation: Taming Optimization Dilemma in Latent
Diffusion Models | ['Jingfeng Yao', 'Bin Yang', 'Xinggang Wang'] | ['cs.CV', 'cs.LG'] | Latent diffusion models with Transformer architectures excel at generating
high-fidelity images. However, recent studies reveal an optimization dilemma in
this two-stage design: while increasing the per-token feature dimension in
visual tokenizers improves reconstruction quality, it requires substantially
larger diffus... | 2025-01-02T18:59:40Z | Models and codes are available at:
https://github.com/hustvl/LightningDiT | null | null | Reconstruction vs. Generation: Taming Optimization Dilemma in Latent Diffusion Models | ['Jingfeng Yao', 'Xinggang Wang'] | 2,025 | arXiv.org | 32 | 45 | ['Computer Science'] |
2,501.01428 | GPT4Scene: Understand 3D Scenes from Videos with Vision-Language Models | ['Zhangyang Qi', 'Zhixiong Zhang', 'Ye Fang', 'Jiaqi Wang', 'Hengshuang Zhao'] | ['cs.CV'] | In recent years, 2D Vision-Language Models (VLMs) have made significant
strides in image-text understanding tasks. However, their performance in 3D
spatial comprehension, which is critical for embodied intelligence, remains
limited. Recent advances have leveraged 3D point clouds and multi-view images
as inputs, yieldin... | 2025-01-02T18:59:59Z | Project page: https://gpt4scene.github.io/ | null | null | GPT4Scene: Understand 3D Scenes from Videos with Vision-Language Models | ['Zhangyang Qi', 'Zhixiong Zhang', 'Ye Fang', 'Jiaqi Wang', 'Hengshuang Zhao'] | 2,025 | arXiv.org | 16 | 128 | ['Computer Science'] |
2,501.01668 | CoT-based Synthesizer: Enhancing LLM Performance through Answer
Synthesis | ['Bohan Zhang', 'Xiaokang Zhang', 'Jing Zhang', 'Jifan Yu', 'Sijia Luo', 'Jie Tang'] | ['cs.CL'] | Current inference scaling methods, such as Self-consistency and Best-of-N,
have proven effective in improving the accuracy of LLMs on complex reasoning
tasks. However, these methods rely heavily on the quality of candidate
responses and are unable to produce correct answers when all candidates are
incorrect. In this pa... | 2025-01-03T06:50:06Z | Accepted as Main of ACL2025 | null | null | null | null | null | null | null | null | null |
2,501.01709 | MoVE-KD: Knowledge Distillation for VLMs with Mixture of Visual Encoders | ['Jiajun Cao', 'Yuan Zhang', 'Tao Huang', 'Ming Lu', 'Qizhe Zhang', 'Ruichuan An', 'Ningning MA', 'Shanghang Zhang'] | ['cs.CV', 'cs.AI'] | Visual encoders are fundamental components in vision-language models (VLMs),
each showcasing unique strengths derived from various pre-trained visual
foundation models. To leverage the various capabilities of these encoders,
recent studies incorporate multiple encoders within a single VLM, leading to a
considerable inc... | 2025-01-03T09:10:34Z | Accepted by CVPR 2025 | null | null | null | null | null | null | null | null | null |
2,501.01811 | QuantumBind-RBFE: Accurate Relative Binding Free Energy Calculations
Using Neural Network Potentials | ['Francesc Sabanés Zariquiey', 'Stephen E. Farr', 'Stefan Doerr', 'Gianni De Fabritiis'] | ['physics.chem-ph', 'cs.LG', 'physics.comp-ph'] | Accurate prediction of protein-ligand binding affinities is crucial in drug
discovery, particularly during hit-to-lead and lead optimization phases,
however, limitations in ligand force fields continue to impact prediction
accuracy. In this work, we validate relative binding free energy (RBFE)
accuracy using neural net... | 2025-01-03T13:51:02Z | null | null | null | null | null | null | null | null | null | null |
2,501.01895 | EnerVerse: Envisioning Embodied Future Space for Robotics Manipulation | ['Siyuan Huang', 'Liliang Chen', 'Pengfei Zhou', 'Shengcong Chen', 'Zhengkai Jiang', 'Yue Hu', 'Yue Liao', 'Peng Gao', 'Hongsheng Li', 'Maoqing Yao', 'Guanghui Ren'] | ['cs.RO', 'cs.CV', 'cs.LG'] | We introduce EnerVerse, a generative robotics foundation model that
constructs and interprets embodied spaces. EnerVerse employs an autoregressive
video diffusion framework to predict future embodied spaces from instructions,
enhanced by a sparse context memory for long-term reasoning. To model the 3D
robotics world, w... | 2025-01-03T17:00:33Z | Website: https://sites.google.com/view/enerverse | null | null | null | null | null | null | null | null | null |
2,501.01904 | Virgo: A Preliminary Exploration on Reproducing o1-like MLLM | ['Yifan Du', 'Zikang Liu', 'Yifan Li', 'Wayne Xin Zhao', 'Yuqi Huo', 'Bingning Wang', 'Weipeng Chen', 'Zheng Liu', 'Zhongyuan Wang', 'Ji-Rong Wen'] | ['cs.CV', 'cs.AI'] | Recently, slow-thinking reasoning systems, built upon large language models
(LLMs), have garnered widespread attention by scaling the thinking time during
inference. There is also growing interest in adapting this capability to
multimodal large language models (MLLMs). Given that MLLMs handle more complex
data semantic... | 2025-01-03T17:14:16Z | Technical Report on Slow Thinking with LLMs: Visual Reasoning | null | null | Virgo: A Preliminary Exploration on Reproducing o1-like MLLM | ['Yifan Du', 'Zikang Liu', 'Yifan Li', 'Wayne Xin Zhao', 'Yuqi Huo', 'Bingning Wang', 'Weipeng Chen', 'Zheng Liu', 'Zhongyuan Wang', 'Jiahui Wen'] | 2,025 | arXiv.org | 36 | 0 | ['Computer Science'] |
2,501.01957 | VITA-1.5: Towards GPT-4o Level Real-Time Vision and Speech Interaction | ['Chaoyou Fu', 'Haojia Lin', 'Xiong Wang', 'Yi-Fan Zhang', 'Yunhang Shen', 'Xiaoyu Liu', 'Haoyu Cao', 'Zuwei Long', 'Heting Gao', 'Ke Li', 'Long Ma', 'Xiawu Zheng', 'Rongrong Ji', 'Xing Sun', 'Caifeng Shan', 'Ran He'] | ['cs.CV', 'cs.SD', 'eess.AS'] | Recent Multimodal Large Language Models (MLLMs) have typically focused on
integrating visual and textual modalities, with less emphasis placed on the
role of speech in enhancing interaction. However, speech plays a crucial role
in multimodal dialogue systems, and implementing high-performance in both
vision and speech ... | 2025-01-03T18:59:52Z | https://github.com/VITA-MLLM/VITA (2K+ Stars by now) | null | null | VITA-1.5: Towards GPT-4o Level Real-Time Vision and Speech Interaction | ['Chaoyou Fu', 'Haojia Lin', 'Xiong Wang', 'Yi-Fan Zhang', 'Yunhang Shen', 'Xiaoyu Liu', 'Yangze Li', 'Zuwei Long', 'Heting Gao', 'Ke Li', 'Xiawu Zheng', 'Rongrong Ji', 'Xing Sun', 'Caifeng Shan', 'Ran He'] | 2,025 | arXiv.org | 54 | 64 | ['Computer Science', 'Engineering'] |
2,501.02045 | METAGENE-1: Metagenomic Foundation Model for Pandemic Monitoring | ['Ollie Liu', 'Sami Jaghouar', 'Johannes Hagemann', 'Shangshang Wang', 'Jason Wiemels', 'Jeff Kaufman', 'Willie Neiswanger'] | ['q-bio.GN', 'cs.AI', 'cs.CL', 'cs.LG'] | We pretrain METAGENE-1, a 7-billion-parameter autoregressive transformer
model, which we refer to as a metagenomic foundation model, on a novel corpus
of diverse metagenomic DNA and RNA sequences comprising over 1.5 trillion base
pairs. This dataset is sourced from a large collection of human wastewater
samples, proces... | 2025-01-03T18:44:43Z | null | null | null | METAGENE-1: Metagenomic Foundation Model for Pandemic Monitoring | ['Ollie Liu', 'Sami Jaghouar', 'Johannes Hagemann', 'Shangshang Wang', 'Jason Wiemels', 'Jeff Kaufman', 'W. Neiswanger'] | 2,025 | arXiv.org | 6 | 0 | ['Biology', 'Computer Science'] |
2,501.0226 | MagicFace: High-Fidelity Facial Expression Editing with Action-Unit
Control | ['Mengting Wei', 'Tuomas Varanka', 'Xingxun Jiang', 'Huai-Qian Khor', 'Guoying Zhao'] | ['cs.CV'] | We address the problem of facial expression editing by controling the
relative variation of facial action-unit (AU) from the same person. This
enables us to edit this specific person's expression in a fine-grained,
continuous and interpretable manner, while preserving their identity, pose,
background and detailed facia... | 2025-01-04T11:28:49Z | null | null | null | null | null | null | null | null | null | null |
2,501.02393 | Graph-Aware Isomorphic Attention for Adaptive Dynamics in Transformers | ['Markus J. Buehler'] | ['cs.LG', 'cond-mat.mes-hall', 'cond-mat.mtrl-sci', 'cs.AI', 'cs.CL'] | We present an approach to modifying Transformer architectures by integrating
graph-aware relational reasoning into the attention mechanism, merging concepts
from graph neural networks and language modeling. Building on the inherent
connection between attention and graph theory, we reformulate the Transformer's
attentio... | 2025-01-04T22:30:21Z | null | null | null | Graph-Aware Isomorphic Attention for Adaptive Dynamics in Transformers | ['Markus J. Buehler'] | 2,025 | APL Machine Learning | 3 | 72 | ['Computer Science', 'Physics'] |
2,501.02448 | Understand, Solve and Translate: Bridging the Multilingual Mathematical
Reasoning Gap | ['Hyunwoo Ko', 'Guijin Son', 'Dasol Choi'] | ['cs.CL'] | Large language models (LLMs) demonstrate exceptional performance on complex
reasoning tasks. However, despite their strong reasoning capabilities in
high-resource languages (e.g., English and Chinese), a significant performance
gap persists in other languages. To investigate this gap in Korean, we
introduce HRM8K, a be... | 2025-01-05T05:57:22Z | 18 pages, 14 figures, 9 tables | null | null | null | null | null | null | null | null | null |
2,501.02464 | Depth Any Camera: Zero-Shot Metric Depth Estimation from Any Camera | ['Yuliang Guo', 'Sparsh Garg', 'S. Mahdi H. Miangoleh', 'Xinyu Huang', 'Liu Ren'] | ['cs.CV', 'cs.AI', 'cs.RO'] | While recent depth foundation models exhibit strong zero-shot generalization,
achieving accurate metric depth across diverse camera types-particularly those
with large fields of view (FoV) such as fisheye and 360-degree cameras-remains
a significant challenge. This paper presents Depth Any Camera (DAC), a powerful
zero... | 2025-01-05T07:22:40Z | null | null | null | Depth Any Camera: Zero-Shot Metric Depth Estimation from Any Camera | ['Yuliang Guo', 'Sparsh Garg', 'S. Mahdi H. Miangoleh', 'Xinyu Huang', 'Liu Ren'] | 2,025 | arXiv.org | 4 | 62 | ['Computer Science'] |
2,501.02487 | ACE++: Instruction-Based Image Creation and Editing via Context-Aware
Content Filling | ['Chaojie Mao', 'Jingfeng Zhang', 'Yulin Pan', 'Zeyinzi Jiang', 'Zhen Han', 'Yu Liu', 'Jingren Zhou'] | ['cs.CV'] | We report ACE++, an instruction-based diffusion framework that tackles
various image generation and editing tasks. Inspired by the input format for
the inpainting task proposed by FLUX.1-Fill-dev, we improve the Long-context
Condition Unit (LCU) introduced in ACE and extend this input paradigm to any
editing and genera... | 2025-01-05T09:40:58Z | null | null | null | null | null | null | null | null | null | null |
2,501.02523 | Face-MakeUp: Multimodal Facial Prompts for Text-to-Image Generation | ['Dawei Dai', 'Mingming Jia', 'Yinxiu Zhou', 'Hang Xing', 'Chenghang Li'] | ['cs.CV', 'cs.AI'] | Facial images have extensive practical applications. Although the current
large-scale text-image diffusion models exhibit strong generation capabilities,
it is challenging to generate the desired facial images using only text prompt.
Image prompts are a logical choice. However, current methods of this type
generally fo... | 2025-01-05T12:46:31Z | null | null | null | Face-MakeUp: Multimodal Facial Prompts for Text-to-Image Generation | ['Dawei Dai', 'Mingming Jia', 'Yinxiu Zhou', 'Hang Xing', 'Chenghang Li'] | 2,025 | arXiv.org | 1 | 0 | ['Computer Science'] |
2,501.02576 | DepthMaster: Taming Diffusion Models for Monocular Depth Estimation | ['Ziyang Song', 'Zerong Wang', 'Bo Li', 'Hao Zhang', 'Ruijie Zhu', 'Li Liu', 'Peng-Tao Jiang', 'Tianzhu Zhang'] | ['cs.CV'] | Monocular depth estimation within the diffusion-denoising paradigm
demonstrates impressive generalization ability but suffers from low inference
speed. Recent methods adopt a single-step deterministic paradigm to improve
inference efficiency while maintaining comparable performance. However, they
overlook the gap betwe... | 2025-01-05T15:18:32Z | 11 pages, 6 figures, 6 tables | null | null | null | null | null | null | null | null | null |
2,501.02629 | Layer-Level Self-Exposure and Patch: Affirmative Token Mitigation for
Jailbreak Attack Defense | ['Yang Ouyang', 'Hengrui Gu', 'Shuhang Lin', 'Wenyue Hua', 'Jie Peng', 'Bhavya Kailkhura', 'Meijun Gao', 'Tianlong Chen', 'Kaixiong Zhou'] | ['cs.CR', 'cs.AI', 'cs.CL'] | As large language models (LLMs) are increasingly deployed in diverse
applications, including chatbot assistants and code generation, aligning their
behavior with safety and ethical standards has become paramount. However,
jailbreak attacks, which exploit vulnerabilities to elicit unintended or
harmful outputs, threaten... | 2025-01-05T19:06:03Z | 14 pages, 4 figures, conference | null | null | null | null | null | null | null | null | null |
2,501.02669 | Generalizing from SIMPLE to HARD Visual Reasoning: Can We Mitigate
Modality Imbalance in VLMs? | ['Simon Park', 'Abhishek Panigrahi', 'Yun Cheng', 'Dingli Yu', 'Anirudh Goyal', 'Sanjeev Arora'] | ['cs.CV', 'cs.CL', 'cs.LG'] | Vision Language Models (VLMs) are impressive at visual question answering and
image captioning. But they underperform on multi-step visual reasoning -- even
compared to LLMs on the same tasks presented in text form -- giving rise to
perceptions of modality imbalance or brittleness. Towards a systematic study of
such is... | 2025-01-05T21:36:38Z | null | null | null | null | null | null | null | null | null | null |
2,501.0279 | Segmenting Text and Learning Their Rewards for Improved RLHF in Language
Model | ['Yueqin Yin', 'Shentao Yang', 'Yujia Xie', 'Ziyi Yang', 'Yuting Sun', 'Hany Awadalla', 'Weizhu Chen', 'Mingyuan Zhou'] | ['cs.CL', 'cs.AI'] | Reinforcement learning from human feedback (RLHF) has been widely adopted to
align language models (LMs) with human preference. Prior RLHF works typically
take a bandit formulation, which, though intuitive, ignores the sequential
nature of LM generation and can suffer from the sparse reward issue. While
recent works pr... | 2025-01-06T06:17:56Z | null | null | null | null | null | null | null | null | null | null |
2,501.02976 | STAR: Spatial-Temporal Augmentation with Text-to-Video Models for
Real-World Video Super-Resolution | ['Rui Xie', 'Yinhong Liu', 'Penghao Zhou', 'Chen Zhao', 'Jun Zhou', 'Kai Zhang', 'Zhenyu Zhang', 'Jian Yang', 'Zhenheng Yang', 'Ying Tai'] | ['cs.CV'] | Image diffusion models have been adapted for real-world video
super-resolution to tackle over-smoothing issues in GAN-based methods. However,
these models struggle to maintain temporal consistency, as they are trained on
static images, limiting their ability to capture temporal dynamics effectively.
Integrating text-to... | 2025-01-06T12:36:21Z | null | null | null | null | null | null | null | null | null | null |
2,501.02979 | Registering Source Tokens to Target Language Spaces in Multilingual
Neural Machine Translation | ['Zhi Qu', 'Yiran Wang', 'Jiannan Mao', 'Chenchen Ding', 'Hideki Tanaka', 'Masao Utiyama', 'Taro Watanabe'] | ['cs.CL'] | The multilingual neural machine translation (MNMT) aims for arbitrary
translations across multiple languages. Although MNMT-specific models trained
on parallel data offer low costs in training and deployment, their performance
consistently lags behind that of large language models (LLMs). In this work, we
introduce reg... | 2025-01-06T12:42:54Z | Accepted by ACL 2025 (main) | null | null | Registering Source Tokens to Target Language Spaces in Multilingual Neural Machine Translation | ['Zhi Qu', 'Yiran Wang', 'Jiannan Mao', 'Chenchen Ding', 'Hideki Tanaka', 'Masao Utiyama', 'Taro Watanabe'] | 2,025 | arXiv.org | 0 | 61 | ['Computer Science'] |
2,501.03006 | TransPixeler: Advancing Text-to-Video Generation with Transparency | ['Luozhou Wang', 'Yijun Li', 'Zhifei Chen', 'Jui-Hsien Wang', 'Zhifei Zhang', 'He Zhang', 'Zhe Lin', 'Yingcong Chen'] | ['cs.CV'] | Text-to-video generative models have made significant strides, enabling
diverse applications in entertainment, advertising, and education. However,
generating RGBA video, which includes alpha channels for transparency, remains
a challenge due to limited datasets and the difficulty of adapting existing
models. Alpha cha... | 2025-01-06T13:32:16Z | Project page: https://wileewang.github.io/TransPixar/ | null | null | TransPixeler: Advancing Text-to-Video Generation with Transparency | ['Luozhou Wang', 'Yijun Li', 'Zhifei Chen', 'Jui-Hsien Wang', 'Zhifei Zhang', 'He Zhang', 'Zhe Lin', 'Yingcong Chen'] | 2,025 | arXiv.org | 2 | 0 | ['Computer Science'] |
2,501.03124 | PRMBench: A Fine-grained and Challenging Benchmark for Process-Level
Reward Models | ['Mingyang Song', 'Zhaochen Su', 'Xiaoye Qu', 'Jiawei Zhou', 'Yu Cheng'] | ['cs.CL', 'cs.AI', 'cs.LG'] | Process-level Reward Models (PRMs) are crucial for complex reasoning and
decision-making tasks, where each intermediate step plays an important role in
the reasoning process. Since language models are prone to various types of
errors during the reasoning process, PRMs are required to possess nuanced
capabilities for de... | 2025-01-06T16:31:45Z | Accepted by ACL 2025 Main. Project Page: https://prmbench.github.io/ | null | null | null | null | null | null | null | null | null |
2,501.03172 | GLiREL -- Generalist Model for Zero-Shot Relation Extraction | ['Jack Boylan', 'Chris Hokamp', 'Demian Gholipour Ghalandari'] | ['cs.CL', 'cs.AI', 'cs.LG'] | We introduce GLiREL (Generalist Lightweight model for zero-shot Relation
Extraction), an efficient architecture and training paradigm for zero-shot
relation classification. Inspired by recent advancements in zero-shot named
entity recognition, this work presents an approach to efficiently and
accurately predict zero-sh... | 2025-01-06T17:42:29Z | Submitted to NAACL 2025 | null | null | null | null | null | null | null | null | null |
2,501.03218 | Dispider: Enabling Video LLMs with Active Real-Time Interaction via
Disentangled Perception, Decision, and Reaction | ['Rui Qian', 'Shuangrui Ding', 'Xiaoyi Dong', 'Pan Zhang', 'Yuhang Zang', 'Yuhang Cao', 'Dahua Lin', 'Jiaqi Wang'] | ['cs.CV'] | Active Real-time interaction with video LLMs introduces a new paradigm for
human-computer interaction, where the model not only understands user intent
but also responds while continuously processing streaming video on the fly.
Unlike offline video LLMs, which analyze the entire video before answering
questions, active... | 2025-01-06T18:55:10Z | null | null | null | Dispider: Enabling Video LLMs with Active Real-Time Interaction via Disentangled Perception, Decision, and Reaction | ['Rui Qian', 'Shuangrui Ding', 'Xiao-wen Dong', 'Pan Zhang', 'Yuhang Zang', 'Yuhang Cao', 'Dahua Lin', 'Jiaqi Wang'] | 2,025 | arXiv.org | 8 | 0 | ['Computer Science'] |
2,501.03468 | MTRAG: A Multi-Turn Conversational Benchmark for Evaluating
Retrieval-Augmented Generation Systems | ['Yannis Katsis', 'Sara Rosenthal', 'Kshitij Fadnis', 'Chulaka Gunasekara', 'Young-Suk Lee', 'Lucian Popa', 'Vraj Shah', 'Huaiyu Zhu', 'Danish Contractor', 'Marina Danilevsky'] | ['cs.CL', 'cs.AI'] | Retrieval-augmented generation (RAG) has recently become a very popular task
for Large Language Models (LLMs). Evaluating them on multi-turn RAG
conversations, where the system is asked to generate a response to a question
in the context of a preceding conversation is an important and often overlooked
task with several... | 2025-01-07T01:52:56Z | null | null | null | null | null | null | null | null | null | null |
2,501.03575 | Cosmos World Foundation Model Platform for Physical AI | ['NVIDIA', ':', 'Niket Agarwal', 'Arslan Ali', 'Maciej Bala', 'Yogesh Balaji', 'Erik Barker', 'Tiffany Cai', 'Prithvijit Chattopadhyay', 'Yongxin Chen', 'Yin Cui', 'Yifan Ding', 'Daniel Dworakowski', 'Jiaojiao Fan', 'Michele Fenzi', 'Francesco Ferroni', 'Sanja Fidler', 'Dieter Fox', 'Songwei Ge', 'Yunhao Ge', 'Jinwei G... | ['cs.CV', 'cs.AI', 'cs.LG', 'cs.RO'] | Physical AI needs to be trained digitally first. It needs a digital twin of
itself, the policy model, and a digital twin of the world, the world model. In
this paper, we present the Cosmos World Foundation Model Platform to help
developers build customized world models for their Physical AI setups. We
position a world ... | 2025-01-07T06:55:50Z | null | null | null | Cosmos World Foundation Model Platform for Physical AI | ['Nvidia Niket Agarwal', 'Arslan Ali', 'Maciej Bala', 'Yogesh Balaji', 'Erik Barker', 'Tiffany Cai', 'Prithvijit Chattopadhyay', 'Yongxin Chen', 'Yin Cui', 'Yifan Ding', 'Daniel Dworakowski', 'Jiaojiao Fan', 'Michele Fenzi', 'Francesco Ferroni', 'Sanja Fidler', 'Dieter Fox', 'Songwei Ge', 'Yunhao Ge', 'Jinwei Gu', 'Sid... | 2,025 | arXiv.org | 129 | 0 | ['Computer Science'] |
2,501.03699 | Motion-Aware Generative Frame Interpolation | ['Guozhen Zhang', 'Yuhan Zhu', 'Yutao Cui', 'Xiaotong Zhao', 'Kai Ma', 'Limin Wang'] | ['cs.CV'] | Flow-based frame interpolation methods ensure motion stability through
estimated intermediate flow but often introduce severe artifacts in complex
motion regions. Recent generative approaches, boosted by large-scale
pre-trained video generation models, show promise in handling intricate scenes.
However, they frequently... | 2025-01-07T11:03:43Z | null | null | null | null | null | null | null | null | null | null |
2,501.03847 | Diffusion as Shader: 3D-aware Video Diffusion for Versatile Video
Generation Control | ['Zekai Gu', 'Rui Yan', 'Jiahao Lu', 'Peng Li', 'Zhiyang Dou', 'Chenyang Si', 'Zhen Dong', 'Qifeng Liu', 'Cheng Lin', 'Ziwei Liu', 'Wenping Wang', 'Yuan Liu'] | ['cs.CV', 'cs.AI', 'cs.GR'] | Diffusion models have demonstrated impressive performance in generating
high-quality videos from text prompts or images. However, precise control over
the video generation process, such as camera manipulation or content editing,
remains a significant challenge. Existing methods for controlled video
generation are typic... | 2025-01-07T15:01:58Z | Project page: https://igl-hkust.github.io/das/ Codes:
https://github.com/IGL-HKUST/DiffusionAsShader | null | null | null | null | null | null | null | null | null |
2,501.03895 | LLaVA-Mini: Efficient Image and Video Large Multimodal Models with One
Vision Token | ['Shaolei Zhang', 'Qingkai Fang', 'Zhe Yang', 'Yang Feng'] | ['cs.CV', 'cs.AI', 'cs.CL'] | The advent of real-time large multimodal models (LMMs) like GPT-4o has
sparked considerable interest in efficient LMMs. LMM frameworks typically
encode visual inputs into vision tokens (continuous representations) and
integrate them and textual instructions into the context of large language
models (LLMs), where large-... | 2025-01-07T16:03:14Z | Accepted to ICLR 2025. Code: https://github.com/ictnlp/LLaVA-Mini
Model: https://huggingface.co/ICTNLP/llava-mini-llama-3.1-8b | null | null | LLaVA-Mini: Efficient Image and Video Large Multimodal Models with One Vision Token | ['Shaolei Zhang', 'Qingkai Fang', 'Zhe Yang', 'Yang Feng'] | 2,025 | International Conference on Learning Representations | 43 | 59 | ['Computer Science'] |
2,501.04001 | Sa2VA: Marrying SAM2 with LLaVA for Dense Grounded Understanding of
Images and Videos | ['Haobo Yuan', 'Xiangtai Li', 'Tao Zhang', 'Zilong Huang', 'Shilin Xu', 'Shunping Ji', 'Yunhai Tong', 'Lu Qi', 'Jiashi Feng', 'Ming-Hsuan Yang'] | ['cs.CV'] | This work presents Sa2VA, the first unified model for dense grounded
understanding of both images and videos. Unlike existing multi-modal large
language models, which are often limited to specific modalities and tasks,
Sa2VA supports a wide range of image and video tasks, including referring
segmentation and conversati... | 2025-01-07T18:58:54Z | Project page: https://lxtgh.github.io/project/sa2va | null | null | null | null | null | null | null | null | null |
2,501.0418 | HIVEX: A High-Impact Environment Suite for Multi-Agent Research
(extended version) | ['Philipp Dominic Siedler'] | ['cs.MA', 'cs.AI', 'cs.GT'] | Games have been vital test beds for the rapid development of Agent-based
research. Remarkable progress has been achieved in the past, but it is unclear
if the findings equip for real-world problems. While pressure grows, some of
the most critical ecological challenges can find mitigation and prevention
solutions throug... | 2025-01-07T23:16:31Z | null | null | null | HIVEX: A High-Impact Environment Suite for Multi-Agent Research (extended version) | ['P. D. Siedler'] | 2,025 | arXiv.org | 1 | 0 | ['Computer Science'] |
2,501.04519 | rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep
Thinking | ['Xinyu Guan', 'Li Lyna Zhang', 'Yifei Liu', 'Ning Shang', 'Youran Sun', 'Yi Zhu', 'Fan Yang', 'Mao Yang'] | ['cs.CL'] | We present rStar-Math to demonstrate that small language models (SLMs) can
rival or even surpass the math reasoning capability of OpenAI o1, without
distillation from superior models. rStar-Math achieves this by exercising "deep
thinking" through Monte Carlo Tree Search (MCTS), where a math policy SLM
performs test-tim... | 2025-01-08T14:12:57Z | null | null | null | rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep Thinking | ['Xinyu Guan', 'L. Zhang', 'Yifei Liu', 'Ning Shang', 'Youran Sun', 'Yi Zhu', 'Fan Yang', 'Mao Yang'] | 2,025 | arXiv.org | 133 | 50 | ['Computer Science'] |
2,501.04561 | OpenOmni: Advancing Open-Source Omnimodal Large Language Models with
Progressive Multimodal Alignment and Real-Time Self-Aware Emotional Speech
Synthesis | ['Run Luo', 'Ting-En Lin', 'Haonan Zhang', 'Yuchuan Wu', 'Xiong Liu', 'Min Yang', 'Yongbin Li', 'Longze Chen', 'Jiaming Li', 'Lei Zhang', 'Yangyi Chen', 'Xiaobo Xia', 'Hamid Alinejad-Rokny', 'Fei Huang'] | ['cs.CL', 'cs.CV'] | Recent advancements in omnimodal learning have significantly improved
understanding and generation across images, text, and speech, yet these
developments remain predominantly confined to proprietary models. The lack of
high-quality omnimodal datasets and the challenges of real-time emotional
speech synthesis have nota... | 2025-01-08T15:18:09Z | null | null | null | null | null | null | null | null | null | null |
2,501.04575 | InfiGUIAgent: A Multimodal Generalist GUI Agent with Native Reasoning
and Reflection | ['Yuhang Liu', 'Pengxiang Li', 'Zishu Wei', 'Congkai Xie', 'Xueyu Hu', 'Xinchen Xu', 'Shengyu Zhang', 'Xiaotian Han', 'Hongxia Yang', 'Fei Wu'] | ['cs.AI', 'cs.CL', 'cs.HC'] | Graphical User Interface (GUI) Agents, powered by multimodal large language
models (MLLMs), have shown great potential for task automation on computing
devices such as computers and mobile phones. However, existing agents face
challenges in multi-step reasoning and reliance on textual annotations,
limiting their effect... | 2025-01-08T15:45:21Z | 14 pages, 7 figures, work in progress | null | null | InfiGUIAgent: A Multimodal Generalist GUI Agent with Native Reasoning and Reflection | ['Yuhang Liu', 'Pengxiang Li', 'Zishu Wei', 'Congkai Xie', 'Xueyu Hu', 'Xinchen Xu', 'Shengyu Zhang', 'Xiaotian Han', 'Hongxia Yang', 'Fei Wu'] | 2,025 | arXiv.org | 22 | 53 | ['Computer Science'] |
2,501.0467 | Are They the Same? Exploring Visual Correspondence Shortcomings of
Multimodal LLMs | ['Yikang Zhou', 'Tao Zhang', 'Shilin Xu', 'Shihao Chen', 'Qianyu Zhou', 'Yunhai Tong', 'Shunping Ji', 'Jiangning Zhang', 'Lu Qi', 'Xiangtai Li'] | ['cs.CV'] | Recent advancements in multimodal large language models (MLLM) have shown a
strong ability in visual perception, reasoning abilities, and vision-language
understanding. However, the visual matching ability of MLLMs is rarely studied,
despite finding the visual correspondence of objects is essential in computer
vision. ... | 2025-01-08T18:30:53Z | Accepted by ICCV2025 | null | null | null | null | null | null | null | null | null |
2,501.04686 | URSA: Understanding and Verifying Chain-of-thought Reasoning in
Multimodal Mathematics | ['Ruilin Luo', 'Zhuofan Zheng', 'Yifan Wang', 'Xinzhe Ni', 'Zicheng Lin', 'Songtao Jiang', 'Yiyao Yu', 'Chufan Shi', 'Ruihang Chu', 'Jin Zeng', 'Yujiu Yang'] | ['cs.CL', 'cs.AI', 'cs.LG'] | Process Reward Models (PRMs) have shown promise in enhancing the mathematical
reasoning capabilities of Large Language Models (LLMs) through Test-Time
Scaling (TTS). However, their integration into multimodal reasoning remains
largely unexplored. In this work, we take the first step toward unlocking the
potential of PR... | 2025-01-08T18:49:41Z | Update version. Project url: https://ursa-math.github.io | null | null | null | null | null | null | null | null | null |
2,501.04689 | SPAR3D: Stable Point-Aware Reconstruction of 3D Objects from Single
Images | ['Zixuan Huang', 'Mark Boss', 'Aaryaman Vasishta', 'James M. Rehg', 'Varun Jampani'] | ['cs.CV', 'cs.GR'] | We study the problem of single-image 3D object reconstruction. Recent works
have diverged into two directions: regression-based modeling and generative
modeling. Regression methods efficiently infer visible surfaces, but struggle
with occluded regions. Generative methods handle uncertain regions better by
modeling dist... | 2025-01-08T18:52:03Z | null | null | null | null | null | null | null | null | null | null |
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