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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2,506.06281 | TerraFM: A Scalable Foundation Model for Unified Multisensor Earth
Observation | ['Muhammad Sohail Danish', 'Muhammad Akhtar Munir', 'Syed Roshaan Ali Shah', 'Muhammad Haris Khan', 'Rao Muhammad Anwer', 'Jorma Laaksonen', 'Fahad Shahbaz Khan', 'Salman Khan'] | ['cs.CV'] | Modern Earth observation (EO) increasingly leverages deep learning to harness
the scale and diversity of satellite imagery across sensors and regions. While
recent foundation models have demonstrated promising generalization across EO
tasks, many remain limited by the scale, geographical coverage, and spectral
diversit... | 2025-06-06T17:59:50Z | null | null | null | null | null | null | null | null | null | null |
2,506.06962 | AR-RAG: Autoregressive Retrieval Augmentation for Image Generation | ['Jingyuan Qi', 'Zhiyang Xu', 'Qifan Wang', 'Lifu Huang'] | ['cs.CV'] | We introduce Autoregressive Retrieval Augmentation (AR-RAG), a novel paradigm
that enhances image generation by autoregressively incorporating knearest
neighbor retrievals at the patch level. Unlike prior methods that perform a
single, static retrieval before generation and condition the entire generation
on fixed refe... | 2025-06-08T01:33:05Z | Image Generation, Retrieval Augmented Generation | null | null | null | null | null | null | null | null | null |
2,506.07032 | A Culturally-diverse Multilingual Multimodal Video Benchmark & Model | ['Bhuiyan Sanjid Shafique', 'Ashmal Vayani', 'Muhammad Maaz', 'Hanoona Abdul Rasheed', 'Dinura Dissanayake', 'Mohammed Irfan Kurpath', 'Yahya Hmaiti', 'Go Inoue', 'Jean Lahoud', 'Md. Safirur Rashid', 'Shadid Intisar Quasem', 'Maheen Fatima', 'Franco Vidal', 'Mykola Maslych', 'Ketan Pravin More', 'Sanoojan Baliah', 'Has... | ['cs.CL', 'cs.CV'] | Large multimodal models (LMMs) have recently gained attention due to their
effectiveness to understand and generate descriptions of visual content. Most
existing LMMs are in English language. While few recent works explore
multilingual image LMMs, to the best of our knowledge, moving beyond the
English language for cul... | 2025-06-08T07:52:20Z | null | null | null | null | null | null | null | null | null | null |
2,506.07044 | Lingshu: A Generalist Foundation Model for Unified Multimodal Medical
Understanding and Reasoning | ['LASA Team', 'Weiwen Xu', 'Hou Pong Chan', 'Long Li', 'Mahani Aljunied', 'Ruifeng Yuan', 'Jianyu Wang', 'Chenghao Xiao', 'Guizhen Chen', 'Chaoqun Liu', 'Zhaodonghui Li', 'Yu Sun', 'Junao Shen', 'Chaojun Wang', 'Jie Tan', 'Deli Zhao', 'Tingyang Xu', 'Hao Zhang', 'Yu Rong'] | ['cs.CL', 'cs.AI', 'cs.CV'] | Multimodal Large Language Models (MLLMs) have demonstrated impressive
capabilities in understanding common visual elements, largely due to their
large-scale datasets and advanced training strategies. However, their
effectiveness in medical applications remains limited due to the inherent
discrepancies between data and ... | 2025-06-08T08:47:30Z | Technical Report, 53 pages, 25 tables, and 16 figures. Our webpage is
https://alibaba-damo-academy.github.io/lingshu/ | null | null | null | null | null | null | null | null | null |
2,506.0708 | FLAIR-HUB: Large-scale Multimodal Dataset for Land Cover and Crop
Mapping | ['Anatol Garioud', 'Sébastien Giordano', 'Nicolas David', 'Nicolas Gonthier'] | ['cs.CV'] | The growing availability of high-quality Earth Observation (EO) data enables
accurate global land cover and crop type monitoring. However, the volume and
heterogeneity of these datasets pose major processing and annotation
challenges. To address this, the French National Institute of Geographical and
Forest Information... | 2025-06-08T10:48:51Z | null | null | null | null | null | null | null | null | null | null |
2,506.0731 | AllTracker: Efficient Dense Point Tracking at High Resolution | ['Adam W. Harley', 'Yang You', 'Xinglong Sun', 'Yang Zheng', 'Nikhil Raghuraman', 'Yunqi Gu', 'Sheldon Liang', 'Wen-Hsuan Chu', 'Achal Dave', 'Pavel Tokmakov', 'Suya You', 'Rares Ambrus', 'Katerina Fragkiadaki', 'Leonidas J. Guibas'] | ['cs.CV'] | We introduce AllTracker: a model that estimates long-range point tracks by
way of estimating the flow field between a query frame and every other frame of
a video. Unlike existing point tracking methods, our approach delivers
high-resolution and dense (all-pixel) correspondence fields, which can be
visualized as flow m... | 2025-06-08T22:55:06Z | null | null | null | null | null | null | null | null | null | null |
2,506.07434 | Well Begun is Half Done: Low-resource Preference Alignment by
Weak-to-Strong Decoding | ['Feifan Song', 'Shaohang Wei', 'Wen Luo', 'Yuxuan Fan', 'Tianyu Liu', 'Guoyin Wang', 'Houfeng Wang'] | ['cs.CL', 'cs.AI'] | Large Language Models (LLMs) require alignment with human preferences to
avoid generating offensive, false, or meaningless content. Recently,
low-resource methods for LLM alignment have been popular, while still facing
challenges in obtaining both high-quality and aligned content. Motivated by the
observation that the ... | 2025-06-09T05:21:22Z | Accepted by ACL 2025 Findings | null | null | null | null | null | null | null | null | null |
2,506.07438 | LGAI-EMBEDDING-Preview Technical Report | ['Jooyoung Choi', 'Hyun Kim', 'Hansol Jang', 'Changwook Jun', 'Kyunghoon Bae', 'Hyewon Choi', 'Stanley Jungkyu Choi', 'Honglak Lee', 'Chulmin Yun'] | ['cs.CL'] | This report presents a unified instruction-based framework for learning
generalized text embeddings optimized for both information retrieval (IR) and
non-IR tasks. Built upon a decoder-only large language model (Mistral-7B), our
approach combines in-context learning, soft supervision, and adaptive
hard-negative mining ... | 2025-06-09T05:30:35Z | 10 pages | null | null | LG-ANNA-Embedding technical report | ['Jooyoung Choi', 'Hyun Kim', 'Hansol Jang', 'Changwook Jun', 'Kyunghoon Bae', 'Hyewon Choi', 'Stanley Jungkyu Choi', 'Honglak Lee', 'Chulmin Yun'] | 2,025 | null | 0 | 35 | ['Computer Science'] |
2,506.07491 | SpatialLM: Training Large Language Models for Structured Indoor Modeling | ['Yongsen Mao', 'Junhao Zhong', 'Chuan Fang', 'Jia Zheng', 'Rui Tang', 'Hao Zhu', 'Ping Tan', 'Zihan Zhou'] | ['cs.CV'] | SpatialLM is a large language model designed to process 3D point cloud data
and generate structured 3D scene understanding outputs. These outputs include
architectural elements like walls, doors, windows, and oriented object boxes
with their semantic categories. Unlike previous methods which exploit
task-specific netwo... | 2025-06-09T07:10:58Z | null | null | null | SpatialLM: Training Large Language Models for Structured Indoor Modeling | ['Yongsen Mao', 'Junhao Zhong', 'Chuan Fang', 'Jia Zheng', 'Rui Tang', 'Hao Zhu', 'Ping Tan', 'Zihan Zhou'] | 2,025 | arXiv.org | 1 | 68 | ['Computer Science'] |
2,506.0752 | LeVo: High-Quality Song Generation with Multi-Preference Alignment | ['Shun Lei', 'Yaoxun Xu', 'Zhiwei Lin', 'Huaicheng Zhang', 'Wei Tan', 'Hangting Chen', 'Jianwei Yu', 'Yixuan Zhang', 'Chenyu Yang', 'Haina Zhu', 'Shuai Wang', 'Zhiyong Wu', 'Dong Yu'] | ['cs.SD', 'cs.AI', 'eess.AS'] | Recent advances in large language models (LLMs) and audio language models
have significantly improved music generation, particularly in lyrics-to-song
generation. However, existing approaches still struggle with the complex
composition of songs and the scarcity of high-quality data, leading to
limitations in sound qual... | 2025-06-09T07:57:24Z | null | null | null | null | null | null | null | null | null | null |
2,506.07527 | Learning What Reinforcement Learning Can't: Interleaved Online
Fine-Tuning for Hardest Questions | ['Lu Ma', 'Hao Liang', 'Meiyi Qiang', 'Lexiang Tang', 'Xiaochen Ma', 'Zhen Hao Wong', 'Junbo Niu', 'Chengyu Shen', 'Runming He', 'Bin Cui', 'Wentao Zhang'] | ['cs.AI', 'cs.LG'] | Recent advances in large language model (LLM) reasoning have shown that
sophisticated behaviors such as planning and self-reflection can emerge through
reinforcement learning (RL). However, despite these successes, RL in its
current form remains insufficient to induce capabilities that exceed the
limitations of the bas... | 2025-06-09T08:11:20Z | 12 pages, 5 figures | null | null | Learning What Reinforcement Learning Can't: Interleaved Online Fine-Tuning for Hardest Questions | ['Lu Ma', 'Hao Liang', 'Meiyi Qiang', 'Lexiang Tang', 'Xiaochen Ma', 'Zhen Hao Wong', 'Junbo Niu', 'Chengyu Shen', 'Runming He', 'Bin Cui', 'Wentao Zhang'] | 2,025 | arXiv.org | 0 | 31 | ['Computer Science'] |
2,506.0753 | BitVLA: 1-bit Vision-Language-Action Models for Robotics Manipulation | ['Hongyu Wang', 'Chuyan Xiong', 'Ruiping Wang', 'Xilin Chen'] | ['cs.RO', 'cs.CV'] | Vision-Language-Action (VLA) models have shown impressive capabilities across
a wide range of robotics manipulation tasks. However, their growing model size
poses significant challenges for deployment on resource-constrained robotic
systems. While 1-bit pretraining has proven effective for enhancing the
inference effic... | 2025-06-09T08:15:11Z | Work in progress | null | null | BitVLA: 1-bit Vision-Language-Action Models for Robotics Manipulation | ['Hongyu Wang', 'Chuyan Xiong', 'Ruiping Wang', 'Xilin Chen'] | 2,025 | arXiv.org | 0 | 46 | ['Computer Science'] |
2,506.07597 | Instructing Large Language Models for Low-Resource Languages: A
Systematic Study for Basque | ['Oscar Sainz', 'Naiara Perez', 'Julen Etxaniz', 'Joseba Fernandez de Landa', 'Itziar Aldabe', 'Iker García-Ferrero', 'Aimar Zabala', 'Ekhi Azurmendi', 'German Rigau', 'Eneko Agirre', 'Mikel Artetxe', 'Aitor Soroa'] | ['cs.CL'] | Instructing language models with user intent requires large instruction
datasets, which are only available for a limited set of languages. In this
paper, we explore alternatives to conventional instruction adaptation pipelines
in low-resource scenarios. We assume a realistic scenario for low-resource
languages, where o... | 2025-06-09T09:54:47Z | Under review | null | null | null | null | null | null | null | null | null |
2,506.07621 | LoRMA: Low-Rank Multiplicative Adaptation for LLMs | ['Harsh Bihany', 'Shubham Patel', 'Ashutosh Modi'] | ['cs.CL', 'cs.AI', 'cs.LG'] | Large Language Models have shown remarkable capabilities in the NLP domain.
Their effectiveness can mainly be attributed to their ability to adapt to an
array of downstream tasks. However, generally, full fine-tuning is a
computationally expensive job. To mitigate this, many techniques have been
developed that prime ef... | 2025-06-09T10:36:46Z | Accepted at ACL Findings 2025; 21 pages (9 main paper + 5 pages
references + 7 pages appendix) | null | null | null | null | null | null | null | null | null |
2,506.07634 | SongBloom: Coherent Song Generation via Interleaved Autoregressive
Sketching and Diffusion Refinement | ['Chenyu Yang', 'Shuai Wang', 'Hangting Chen', 'Wei Tan', 'Jianwei Yu', 'Haizhou Li'] | ['eess.AS', 'cs.MM'] | Generating music with coherent structure, harmonious instrumental and vocal
elements remains a significant challenge in song generation. Existing language
models and diffusion-based methods often struggle to balance global coherence
with local fidelity, resulting in outputs that lack musicality or suffer from
incoheren... | 2025-06-09T11:01:01Z | Submitted to NeurIPS2025 | null | null | null | null | null | null | null | null | null |
2,506.07636 | SWE-Dev: Building Software Engineering Agents with Training and
Inference Scaling | ['Haoran Wang', 'Zhenyu Hou', 'Yao Wei', 'Jie Tang', 'Yuxiao Dong'] | ['cs.AI'] | Large language models (LLMs) have advanced rapidly from conversational
problem solving to addressing real-world tasks involving tool use, such as
software engineering (SWE). Recent LLM-powered toolkits, such as OpenAI Codex
and Cursor, have offered end-to-end automation of the software development
process. However, bui... | 2025-06-09T11:03:16Z | Accepted to Findings of ACL'25 | null | null | null | null | null | null | null | null | null |
2,506.07643 | Synthetic Visual Genome | ['Jae Sung Park', 'Zixian Ma', 'Linjie Li', 'Chenhao Zheng', 'Cheng-Yu Hsieh', 'Ximing Lu', 'Khyathi Chandu', 'Quan Kong', 'Norimasa Kobori', 'Ali Farhadi', 'Yejin Choi', 'Ranjay Krishna'] | ['cs.CV'] | Reasoning over visual relationships-spatial, functional, interactional,
social, etc.-is considered to be a fundamental component of human cognition.
Yet, despite the major advances in visual comprehension in multimodal language
models (MLMs), precise reasoning over relationships and their generations
remains a challeng... | 2025-06-09T11:09:10Z | CVPR 2025 | null | null | null | null | null | null | null | null | null |
2,506.07833 | Improving Large Language Models with Concept-Aware Fine-Tuning | ['Michael K. Chen', 'Xikun Zhang', 'Jiaxing Huang', 'Dacheng Tao'] | ['cs.LG', 'cs.AI', 'cs.CL'] | Large language models (LLMs) have become the cornerstone of modern AI.
However, the existing paradigm of next-token prediction fundamentally limits
their ability to form coherent, high-level concepts, making it a critical
barrier to human-like understanding and reasoning. Take the phrase "ribonucleic
acid" as an exampl... | 2025-06-09T14:55:00Z | null | null | null | Improving Large Language Models with Concept-Aware Fine-Tuning | ['Michael Chen', 'Xikun Zhang', 'Jiaxing Huang', 'Dacheng Tao'] | 2,025 | arXiv.org | 0 | 63 | ['Computer Science'] |
2,506.07837 | HAIBU-ReMUD: Reasoning Multimodal Ultrasound Dataset and Model Bridging
to General Specific Domains | ['Shijie Wang', 'Yilun Zhang', 'Zeyu Lai', 'Dexing Kong'] | ['cs.AI'] | Multimodal large language models (MLLMs) have shown great potential in
general domains but perform poorly in some specific domains due to a lack of
domain-specific data, such as image-text data or vedio-text data. In some
specific domains, there is abundant graphic and textual data scattered around,
but lacks standardi... | 2025-06-09T15:01:38Z | null | null | null | null | null | null | null | null | null | null |
2,506.079 | MiniCPM4: Ultra-Efficient LLMs on End Devices | ['MiniCPM Team', 'Chaojun Xiao', 'Yuxuan Li', 'Xu Han', 'Yuzhuo Bai', 'Jie Cai', 'Haotian Chen', 'Wentong Chen', 'Xin Cong', 'Ganqu Cui', 'Ning Ding', 'Shengdan Fan', 'Yewei Fang', 'Zixuan Fu', 'Wenyu Guan', 'Yitong Guan', 'Junshao Guo', 'Yufeng Han', 'Bingxiang He', 'Yuxiang Huang', 'Cunliang Kong', 'Qiuzuo Li', 'Siyu... | ['cs.CL', 'cs.AI'] | This paper introduces MiniCPM4, a highly efficient large language model (LLM)
designed explicitly for end-side devices. We achieve this efficiency through
systematic innovation in four key dimensions: model architecture, training
data, training algorithms, and inference systems. Specifically, in terms of
model architec... | 2025-06-09T16:16:50Z | MiniCPM4 Technical Report | null | null | null | null | null | null | null | null | null |
2,506.07905 | WeThink: Toward General-purpose Vision-Language Reasoning via
Reinforcement Learning | ['Jie Yang', 'Feipeng Ma', 'Zitian Wang', 'Dacheng Yin', 'Kang Rong', 'Fengyun Rao', 'Ruimao Zhang'] | ['cs.CV'] | Building on the success of text-based reasoning models like DeepSeek-R1,
extending these capabilities to multimodal reasoning holds great promise. While
recent works have attempted to adapt DeepSeek-R1-style reinforcement learning
(RL) training paradigms to multimodal large language models (MLLM), focusing on
domain-sp... | 2025-06-09T16:20:54Z | null | null | null | WeThink: Toward General-purpose Vision-Language Reasoning via Reinforcement Learning | ['Jie Yang', 'Feipeng Ma', 'Zitian Wang', 'Dacheng Yin', 'Kang Rong', 'Fengyun Rao', 'Ruimao Zhang'] | 2,025 | arXiv.org | 0 | 96 | ['Computer Science'] |
2,506.07918 | CausalPFN: Amortized Causal Effect Estimation via In-Context Learning | ['Vahid Balazadeh', 'Hamidreza Kamkari', 'Valentin Thomas', 'Benson Li', 'Junwei Ma', 'Jesse C. Cresswell', 'Rahul G. Krishnan'] | ['cs.LG', 'stat.ML'] | Causal effect estimation from observational data is fundamental across
various applications. However, selecting an appropriate estimator from dozens
of specialized methods demands substantial manual effort and domain expertise.
We present CausalPFN, a single transformer that amortizes this workflow:
trained once on a l... | 2025-06-09T16:31:06Z | null | null | null | CausalPFN: Amortized Causal Effect Estimation via In-Context Learning | ['Vahid Balazadeh', 'Hamidreza Kamkari', 'Valentin Thomas', 'Benson Li', 'Junwei Ma', 'Jesse C. Cresswell', 'Rahul G. Krishnan'] | 2,025 | arXiv.org | 0 | 107 | ['Computer Science', 'Mathematics'] |
2,506.07932 | Squeeze3D: Your 3D Generation Model is Secretly an Extreme Neural
Compressor | ['Rishit Dagli', 'Yushi Guan', 'Sankeerth Durvasula', 'Mohammadreza Mofayezi', 'Nandita Vijaykumar'] | ['cs.GR', 'cs.CV', 'cs.LG'] | We propose Squeeze3D, a novel framework that leverages implicit prior
knowledge learnt by existing pre-trained 3D generative models to compress 3D
data at extremely high compression ratios. Our approach bridges the latent
spaces between a pre-trained encoder and a pre-trained generation model through
trainable mapping ... | 2025-06-09T16:52:10Z | null | null | null | null | null | null | null | null | null | null |
2,506.07966 | SpaCE-10: A Comprehensive Benchmark for Multimodal Large Language Models
in Compositional Spatial Intelligence | ['Ziyang Gong', 'Wenhao Li', 'Oliver Ma', 'Songyuan Li', 'Jiayi Ji', 'Xue Yang', 'Gen Luo', 'Junchi Yan', 'Rongrong Ji'] | ['cs.CV'] | Multimodal Large Language Models (MLLMs) have achieved remarkable progress in
various multimodal tasks. To pursue higher intelligence in space, MLLMs require
integrating multiple atomic spatial capabilities to handle complex and dynamic
tasks. However, existing benchmarks struggle to comprehensively evaluate the
spatia... | 2025-06-09T17:41:36Z | null | null | null | null | null | null | null | null | null | null |
2,506.07986 | Rethinking Cross-Modal Interaction in Multimodal Diffusion Transformers | ['Zhengyao Lv', 'Tianlin Pan', 'Chenyang Si', 'Zhaoxi Chen', 'Wangmeng Zuo', 'Ziwei Liu', 'Kwan-Yee K. Wong'] | ['cs.CV'] | Multimodal Diffusion Transformers (MM-DiTs) have achieved remarkable progress
in text-driven visual generation. However, even state-of-the-art MM-DiT models
like FLUX struggle with achieving precise alignment between text prompts and
generated content. We identify two key issues in the attention mechanism of
MM-DiT, na... | 2025-06-09T17:54:04Z | Project Page: https://vchitect.github.io/TACA/ | null | null | null | null | null | null | null | null | null |
2,506.07999 | MADFormer: Mixed Autoregressive and Diffusion Transformers for
Continuous Image Generation | ['Junhao Chen', 'Yulia Tsvetkov', 'Xiaochuang Han'] | ['cs.CV', 'cs.LG'] | Recent progress in multimodal generation has increasingly combined
autoregressive (AR) and diffusion-based approaches, leveraging their
complementary strengths: AR models capture long-range dependencies and produce
fluent, context-aware outputs, while diffusion models operate in continuous
latent spaces to refine high-... | 2025-06-09T17:59:01Z | null | null | null | null | null | null | null | null | null | null |
2,506.08003 | Audio-Sync Video Generation with Multi-Stream Temporal Control | ['Shuchen Weng', 'Haojie Zheng', 'Zheng Chang', 'Si Li', 'Boxin Shi', 'Xinlong Wang'] | ['cs.CV', 'cs.AI'] | Audio is inherently temporal and closely synchronized with the visual world,
making it a naturally aligned and expressive control signal for controllable
video generation (e.g., movies). Beyond control, directly translating audio
into video is essential for understanding and visualizing rich audio narratives
(e.g., Pod... | 2025-06-09T17:59:42Z | null | null | null | null | null | null | null | null | null | null |
2,506.08007 | Reinforcement Pre-Training | ['Qingxiu Dong', 'Li Dong', 'Yao Tang', 'Tianzhu Ye', 'Yutao Sun', 'Zhifang Sui', 'Furu Wei'] | ['cs.CL'] | In this work, we introduce Reinforcement Pre-Training (RPT) as a new scaling
paradigm for large language models and reinforcement learning (RL).
Specifically, we reframe next-token prediction as a reasoning task trained
using RL, where it receives verifiable rewards for correctly predicting the
next token for a given c... | 2025-06-09T17:59:53Z | null | null | null | null | null | null | null | null | null | null |
2,506.08009 | Self Forcing: Bridging the Train-Test Gap in Autoregressive Video
Diffusion | ['Xun Huang', 'Zhengqi Li', 'Guande He', 'Mingyuan Zhou', 'Eli Shechtman'] | ['cs.CV', 'cs.AI', 'cs.LG'] | We introduce Self Forcing, a novel training paradigm for autoregressive video
diffusion models. It addresses the longstanding issue of exposure bias, where
models trained on ground-truth context must generate sequences conditioned on
their own imperfect outputs during inference. Unlike prior methods that denoise
future... | 2025-06-09T17:59:55Z | Project website: http://self-forcing.github.io/ | null | null | null | null | null | null | null | null | null |
2,506.0801 | Vision Transformers Don't Need Trained Registers | ['Nick Jiang', 'Amil Dravid', 'Alexei Efros', 'Yossi Gandelsman'] | ['cs.CV', 'cs.AI'] | We investigate the mechanism underlying a previously identified phenomenon in
Vision Transformers -- the emergence of high-norm tokens that lead to noisy
attention maps. We observe that in multiple models (e.g., CLIP, DINOv2), a
sparse set of neurons is responsible for concentrating high-norm activations on
outlier tok... | 2025-06-09T17:59:57Z | Project page and code: https://avdravid.github.io/test-time-registers | null | null | null | null | null | null | null | null | null |
2,506.08011 | Play to Generalize: Learning to Reason Through Game Play | ['Yunfei Xie', 'Yinsong Ma', 'Shiyi Lan', 'Alan Yuille', 'Junfei Xiao', 'Chen Wei'] | ['cs.CV', 'cs.CL'] | Developing generalizable reasoning capabilities in multimodal large language
models (MLLMs) remains challenging. Motivated by cognitive science literature
suggesting that gameplay promotes transferable cognitive skills, we propose a
novel post-training paradigm, Visual Game Learning, or ViGaL, where MLLMs
develop out-o... | 2025-06-09T17:59:57Z | Project Page: https://yunfeixie233.github.io/ViGaL/ | null | null | Play to Generalize: Learning to Reason Through Game Play | ['Yunfei Xie', 'Yinsong Ma', 'Shiyi Lan', 'Alan L. Yuille', 'Junfei Xiao', 'Chen Wei'] | 2,025 | arXiv.org | 0 | 74 | ['Computer Science'] |
2,506.08293 | Diffusion Sequence Models for Enhanced Protein Representation and
Generation | ['Logan Hallee', 'Nikolaos Rafailidis', 'David B. Bichara', 'Jason P. Gleghorn'] | ['q-bio.BM'] | Proteins are fundamental to biology, executing diverse functions through
complex physicochemical interactions, and they hold transformative potential
across medicine, materials science, and environmental applications. Protein
Language Models (pLMs) aim to unlock insights from the vast space of unlabeled
protein sequenc... | 2025-06-09T23:50:11Z | 20 pages, 15 figures | null | null | null | null | null | null | null | null | null |
2,506.083 | Institutional Books 1.0: A 242B token dataset from Harvard Library's
collections, refined for accuracy and usability | ['Matteo Cargnelutti', 'Catherine Brobston', 'John Hess', 'Jack Cushman', 'Kristi Mukk', 'Aristana Scourtas', 'Kyle Courtney', 'Greg Leppert', 'Amanda Watson', 'Martha Whitehead', 'Jonathan Zittrain'] | ['cs.CL', 'cs.DL'] | Large language models (LLMs) use data to learn about the world in order to
produce meaningful correlations and predictions. As such, the nature, scale,
quality, and diversity of the datasets used to train these models, or to
support their work at inference time, have a direct impact on their quality.
The rapid developm... | 2025-06-10T00:11:30Z | null | null | null | null | null | null | null | null | null | null |
2,506.08388 | Reinforcement Learning Teachers of Test Time Scaling | ['Edoardo Cetin', 'Tianyu Zhao', 'Yujin Tang'] | ['cs.LG', 'cs.AI', 'cs.CL'] | Training reasoning language models (LMs) with reinforcement learning (RL) for
one-hot correctness inherently relies on the LM being able to explore and solve
its task with some chance at initialization. Furthermore, a key use case of
reasoning LMs is to act as teachers for distilling new students and
cold-starting futu... | 2025-06-10T02:53:24Z | Code available at: https://github.com/SakanaAI/RLT | null | null | Reinforcement Learning Teachers of Test Time Scaling | ['Edoardo Cetin', 'Tianyu Zhao', 'Yujin Tang'] | 2,025 | arXiv.org | 0 | 45 | ['Computer Science'] |
2,506.0864 | Orientation Matters: Making 3D Generative Models Orientation-Aligned | ['Yichong Lu', 'Yuzhuo Tian', 'Zijin Jiang', 'Yikun Zhao', 'Yuanbo Yang', 'Hao Ouyang', 'Haoji Hu', 'Huimin Yu', 'Yujun Shen', 'Yiyi Liao'] | ['cs.CV'] | Humans intuitively perceive object shape and orientation from a single image,
guided by strong priors about canonical poses. However, existing 3D generative
models often produce misaligned results due to inconsistent training data,
limiting their usability in downstream tasks. To address this gap, we introduce
the task... | 2025-06-10T09:54:37Z | Project Page: https://xdimlab.github.io/Orientation_Matters | null | null | null | null | null | null | null | null | null |
2,506.08672 | RuleReasoner: Reinforced Rule-based Reasoning via Domain-aware Dynamic
Sampling | ['Yang Liu', 'Jiaqi Li', 'Zilong Zheng'] | ['cs.CL', 'cs.AI', 'cs.LG'] | Rule-based reasoning has been acknowledged as one of the fundamental problems
in reasoning, while deviations in rule formats, types, and complexity in
real-world applications pose severe challenges. Recent studies have shown that
large reasoning models (LRMs) have remarkable reasoning capabilities, and their
performanc... | 2025-06-10T10:31:21Z | 22 pages, 10 figures, 8 tables | null | null | null | null | null | null | null | null | null |
2,506.08897 | PlantDeBERTa: An Open Source Language Model for Plant Science | ['Hiba Khey', 'Amine Lakhder', 'Salma Rouichi', 'Imane El Ghabi', 'Kamal Hejjaoui', 'Younes En-nahli', 'Fahd Kalloubi', 'Moez Amri'] | ['cs.CL', 'cs.AI'] | The rapid advancement of transformer-based language models has catalyzed
breakthroughs in biomedical and clinical natural language processing; however,
plant science remains markedly underserved by such domain-adapted tools. In
this work, we present PlantDeBERTa, a high-performance, open-source language
model specifica... | 2025-06-10T15:24:03Z | null | null | null | null | null | null | null | null | null | null |
2,506.089 | MIRAGE: Multimodal foundation model and benchmark for comprehensive
retinal OCT image analysis | ['José Morano', 'Botond Fazekas', 'Emese Sükei', 'Ronald Fecso', 'Taha Emre', 'Markus Gumpinger', 'Georg Faustmann', 'Marzieh Oghbaie', 'Ursula Schmidt-Erfurth', 'Hrvoje Bogunović'] | ['cs.CV'] | Artificial intelligence (AI) has become a fundamental tool for assisting
clinicians in analyzing ophthalmic images, such as optical coherence tomography
(OCT). However, developing AI models often requires extensive annotation, and
existing models tend to underperform on independent, unseen data. Foundation
models (FMs)... | 2025-06-10T15:25:55Z | null | null | null | MIRAGE: Multimodal foundation model and benchmark for comprehensive retinal OCT image analysis | ['José Morano', 'Botond Fazekas', 'Emese Sukei', 'Ronald Fecso', 'T. Emre', 'Markus Gumpinger', 'Georg Faustmann', 'Marzieh Oghbaie', 'U. Schmidt-Erfurth', "Hrvoje Bogunovi'c"] | 2,025 | arXiv.org | 0 | 0 | ['Computer Science'] |
2,506.08967 | Step-Audio-AQAA: a Fully End-to-End Expressive Large Audio Language
Model | ['Ailin Huang', 'Bingxin Li', 'Bruce Wang', 'Boyong Wu', 'Chao Yan', 'Chengli Feng', 'Heng Wang', 'Hongyu Zhou', 'Hongyuan Wang', 'Jingbei Li', 'Jianjian Sun', 'Joanna Wang', 'Mingrui Chen', 'Peng Liu', 'Ruihang Miao', 'Shilei Jiang', 'Tian Fei', 'Wang You', 'Xi Chen', 'Xuerui Yang', 'Yechang Huang', 'Yuxiang Zhang', '... | ['cs.SD', 'cs.CL', 'eess.AS'] | Large Audio-Language Models (LALMs) have significantly advanced intelligent
human-computer interaction, yet their reliance on text-based outputs limits
their ability to generate natural speech responses directly, hindering seamless
audio interactions. To address this, we introduce Step-Audio-AQAA, a fully
end-to-end LA... | 2025-06-10T16:37:39Z | 12 pages, 3 figures | null | null | null | null | null | null | null | null | null |
2,506.09007 | Branched Schrödinger Bridge Matching | ['Sophia Tang', 'Yinuo Zhang', 'Alexander Tong', 'Pranam Chatterjee'] | ['cs.LG', 'q-bio.QM'] | Predicting the intermediate trajectories between an initial and target
distribution is a central problem in generative modeling. Existing approaches,
such as flow matching and Schr\"odinger Bridge Matching, effectively learn
mappings between two distributions by modeling a single stochastic path.
However, these methods... | 2025-06-10T17:29:48Z | null | null | null | null | null | null | null | null | null | null |
2,506.09278 | UFM: A Simple Path towards Unified Dense Correspondence with Flow | ['Yuchen Zhang', 'Nikhil Keetha', 'Chenwei Lyu', 'Bhuvan Jhamb', 'Yutian Chen', 'Yuheng Qiu', 'Jay Karhade', 'Shreyas Jha', 'Yaoyu Hu', 'Deva Ramanan', 'Sebastian Scherer', 'Wenshan Wang'] | ['cs.CV', 'cs.LG', 'cs.RO'] | Dense image correspondence is central to many applications, such as visual
odometry, 3D reconstruction, object association, and re-identification.
Historically, dense correspondence has been tackled separately for
wide-baseline scenarios and optical flow estimation, despite the common goal of
matching content between t... | 2025-06-10T22:32:13Z | Project Page: https://uniflowmatch.github.io/ | null | null | null | null | null | null | null | null | null |
2,506.09344 | Ming-Omni: A Unified Multimodal Model for Perception and Generation | ['Inclusion AI', 'Biao Gong', 'Cheng Zou', 'Chuanyang Zheng', 'Chunluan Zhou', 'Canxiang Yan', 'Chunxiang Jin', 'Chunjie Shen', 'Dandan Zheng', 'Fudong Wang', 'Furong Xu', 'GuangMing Yao', 'Jun Zhou', 'Jingdong Chen', 'Jianxin Sun', 'Jiajia Liu', 'Jianjiang Zhu', 'Jun Peng', 'Kaixiang Ji', 'Kaiyou Song', 'Kaimeng Ren',... | ['cs.AI', 'cs.CL', 'cs.CV', 'cs.LG', 'cs.SD', 'eess.AS'] | We propose Ming-Omni, a unified multimodal model capable of processing
images, text, audio, and video, while demonstrating strong proficiency in both
speech and image generation. Ming-Omni employs dedicated encoders to extract
tokens from different modalities, which are then processed by Ling, an MoE
architecture equip... | 2025-06-11T02:50:49Z | 18 pages,8 figures | null | null | null | null | null | null | null | null | null |
2,506.09366 | SkillBlender: Towards Versatile Humanoid Whole-Body Loco-Manipulation
via Skill Blending | ['Yuxuan Kuang', 'Haoran Geng', 'Amine Elhafsi', 'Tan-Dzung Do', 'Pieter Abbeel', 'Jitendra Malik', 'Marco Pavone', 'Yue Wang'] | ['cs.RO', 'cs.LG'] | Humanoid robots hold significant potential in accomplishing daily tasks
across diverse environments thanks to their flexibility and human-like
morphology. Recent works have made significant progress in humanoid whole-body
control and loco-manipulation leveraging optimal control or reinforcement
learning. However, these... | 2025-06-11T03:24:26Z | null | null | null | SkillBlender: Towards Versatile Humanoid Whole-Body Loco-Manipulation via Skill Blending | ['Yuxuan Kuang', 'Haoran Geng', 'Amine Elhafsi', 'Tan-Dzung Do', 'Pieter Abbeel', 'Jitendra Malik', 'Marco Pavone', 'Yue Wang'] | 2,025 | arXiv.org | 1 | 54 | ['Computer Science'] |
2,506.09369 | ScaleLSD: Scalable Deep Line Segment Detection Streamlined | ['Zeran Ke', 'Bin Tan', 'Xianwei Zheng', 'Yujun Shen', 'Tianfu Wu', 'Nan Xue'] | ['cs.CV'] | This paper studies the problem of Line Segment Detection (LSD) for the
characterization of line geometry in images, with the aim of learning a
domain-agnostic robust LSD model that works well for any natural images. With
the focus of scalable self-supervised learning of LSD, we revisit and
streamline the fundamental de... | 2025-06-11T03:34:21Z | accepted to CVPR 2025; 17 pages, appendices included | null | null | null | null | null | null | null | null | null |
2,506.0944 | GigaChat Family: Efficient Russian Language Modeling Through Mixture of
Experts Architecture | ['GigaChat team', 'Mamedov Valentin', 'Evgenii Kosarev', 'Gregory Leleytner', 'Ilya Shchuckin', 'Valeriy Berezovskiy', 'Daniil Smirnov', 'Dmitry Kozlov', 'Sergei Averkiev', 'Lukyanenko Ivan', 'Aleksandr Proshunin', 'Ainur Israfilova', 'Ivan Baskov', 'Artem Chervyakov', 'Emil Shakirov', 'Mikhail Kolesov', 'Daria Khomich... | ['cs.CL', 'cs.AI'] | Generative large language models (LLMs) have become crucial for modern NLP
research and applications across various languages. However, the development of
foundational models specifically tailored to the Russian language has been
limited, primarily due to the significant computational resources required.
This paper int... | 2025-06-11T06:46:49Z | ACL-2025 System Demo | null | null | null | null | null | null | null | null | null |
2,506.09482 | Marrying Autoregressive Transformer and Diffusion with Multi-Reference
Autoregression | ['Dingcheng Zhen', 'Qian Qiao', 'Tan Yu', 'Kangxi Wu', 'Ziwei Zhang', 'Siyuan Liu', 'Shunshun Yin', 'Ming Tao'] | ['cs.CV'] | We introduce TransDiff, the first image generation model that marries
Autoregressive (AR) Transformer with diffusion models. In this joint modeling
framework, TransDiff encodes labels and images into high-level semantic
features and employs a diffusion model to estimate the distribution of image
samples. On the ImageNe... | 2025-06-11T07:50:31Z | null | null | null | null | null | null | null | null | null | null |
2,506.09513 | ReasonMed: A 370K Multi-Agent Generated Dataset for Advancing Medical
Reasoning | ['Yu Sun', 'Xingyu Qian', 'Weiwen Xu', 'Hao Zhang', 'Chenghao Xiao', 'Long Li', 'Yu Rong', 'Wenbing Huang', 'Qifeng Bai', 'Tingyang Xu'] | ['cs.CL', 'cs.AI', 'cs.MA'] | Though reasoning-based large language models (LLMs) have excelled in
mathematics and programming, their capabilities in knowledge-intensive medical
question answering remain underexplored. To address this, we introduce
ReasonMed, the largest medical reasoning dataset, comprising 370k high-quality
examples distilled fro... | 2025-06-11T08:36:55Z | 24 pages, 6 figures, 7 tables | null | null | null | null | null | null | null | null | null |
2,506.0956 | Towards Open Foundation Language Model and Corpus for Macedonian: A
Low-Resource Language | ['Stefan Krsteski', 'Matea Tashkovska', 'Borjan Sazdov', 'Hristijan Gjoreski', 'Branislav Gerazov'] | ['cs.CL'] | The increase in technological adoption worldwide comes with demands for novel
tools to be used by the general population. Large Language Models (LLMs)
provide a great opportunity in this respect, but their capabilities remain
limited for low-resource languages, restricting applications in countries where
such languages... | 2025-06-11T09:46:58Z | Camera-ready version accepted at SlavNLP-2025@ACL | null | null | null | null | null | null | null | null | null |
2,506.09645 | Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph
Question Answering | ['Tianjun Yao', 'Haoxuan Li', 'Zhiqiang Shen', 'Pan Li', 'Tongliang Liu', 'Kun Zhang'] | ['cs.CL', 'cs.IR', 'cs.LG', 'I.2.6'] | Large Language Models (LLMs) have shown strong inductive reasoning ability
across various domains, but their reliability is hindered by the outdated
knowledge and hallucinations. Retrieval-Augmented Generation mitigates these
issues by grounding LLMs with external knowledge; however, most existing RAG
pipelines rely on... | 2025-06-11T12:03:52Z | 32 pages, 28 figures | null | null | Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering | ['Tianjun Yao', 'Haoxuan Li', 'Zhiqiang Shen', 'Pan Li', 'Tongliang Liu', 'Kun Zhang'] | 2,025 | arXiv.org | 0 | 66 | ['Computer Science'] |
2,506.09736 | Vision Matters: Simple Visual Perturbations Can Boost Multimodal Math
Reasoning | ['Yuting Li', 'Lai Wei', 'Kaipeng Zheng', 'Jingyuan Huang', 'Linghe Kong', 'Lichao Sun', 'Weiran Huang'] | ['cs.CV', 'cs.AI'] | Despite the rapid progress of multimodal large language models (MLLMs), they
have largely overlooked the importance of visual processing. In a simple yet
revealing experiment, we interestingly find that language-only models, when
provided with image captions, can achieve comparable or even better performance
than MLLMs... | 2025-06-11T13:39:46Z | Technical Report | null | null | null | null | null | null | null | null | null |
2,506.0982 | CoRT: Code-integrated Reasoning within Thinking | ['Chengpeng Li', 'Zhengyang Tang', 'Ziniu Li', 'Mingfeng Xue', 'Keqin Bao', 'Tian Ding', 'Ruoyu Sun', 'Benyou Wang', 'Xiang Wang', 'Junyang Lin', 'Dayiheng Liu'] | ['cs.CL', 'cs.AI', 'cs.LG'] | Large Reasoning Models (LRMs) like o1 and DeepSeek-R1 have shown remarkable
progress in natural language reasoning with long chain-of-thought (CoT), yet
they remain inefficient or inaccurate when handling complex mathematical
operations. Addressing these limitations through computational tools (e.g.,
computation librar... | 2025-06-11T14:59:02Z | work in progress | null | null | null | null | null | null | null | null | null |
2,506.0993 | From Intention to Execution: Probing the Generalization Boundaries of
Vision-Language-Action Models | ['Irving Fang', 'Juexiao Zhang', 'Shengbang Tong', 'Chen Feng'] | ['cs.RO', 'cs.CV'] | One promise that Vision-Language-Action (VLA) models hold over traditional
imitation learning for robotics is to leverage the broad generalization
capabilities of large Vision-Language Models (VLMs) to produce versatile,
"generalist" robot policies. However, current evaluations of VLAs remain
insufficient. Traditional ... | 2025-06-11T16:52:18Z | Under review | null | null | From Intention to Execution: Probing the Generalization Boundaries of Vision-Language-Action Models | ['Irving Fang', 'Juexiao Zhang', 'Shengbang Tong', 'Chen Feng'] | 2,025 | arXiv.org | 1 | 38 | ['Computer Science'] |
2,506.09942 | VerIF: Verification Engineering for Reinforcement Learning in
Instruction Following | ['Hao Peng', 'Yunjia Qi', 'Xiaozhi Wang', 'Bin Xu', 'Lei Hou', 'Juanzi Li'] | ['cs.CL', 'cs.AI'] | Reinforcement learning with verifiable rewards (RLVR) has become a key
technique for enhancing large language models (LLMs), with verification
engineering playing a central role. However, best practices for RL in
instruction following remain underexplored. In this work, we explore the
verification challenge in RL for i... | 2025-06-11T17:10:36Z | 16 pages, 8 figures | null | null | null | null | null | null | null | null | null |
2,506.09965 | Reinforcing Spatial Reasoning in Vision-Language Models with Interwoven
Thinking and Visual Drawing | ['Junfei Wu', 'Jian Guan', 'Kaituo Feng', 'Qiang Liu', 'Shu Wu', 'Liang Wang', 'Wei Wu', 'Tieniu Tan'] | ['cs.CV', 'cs.AI'] | As textual reasoning with large language models (LLMs) has advanced
significantly, there has been growing interest in enhancing the multimodal
reasoning capabilities of large vision-language models (LVLMs). However,
existing methods primarily approach multimodal reasoning in a straightforward,
text-centric manner, wher... | 2025-06-11T17:41:50Z | null | null | null | null | null | null | null | null | null | null |
2,506.0998 | Efficient Part-level 3D Object Generation via Dual Volume Packing | ['Jiaxiang Tang', 'Ruijie Lu', 'Zhaoshuo Li', 'Zekun Hao', 'Xuan Li', 'Fangyin Wei', 'Shuran Song', 'Gang Zeng', 'Ming-Yu Liu', 'Tsung-Yi Lin'] | ['cs.CV'] | Recent progress in 3D object generation has greatly improved both the quality
and efficiency. However, most existing methods generate a single mesh with all
parts fused together, which limits the ability to edit or manipulate individual
parts. A key challenge is that different objects may have a varying number of
parts... | 2025-06-11T17:55:03Z | Code: https://github.com/NVlabs/PartPacker Project Page:
https://research.nvidia.com/labs/dir/partpacker/ | null | null | null | null | null | null | null | null | null |
2,506.09991 | Multiverse: Your Language Models Secretly Decide How to Parallelize and
Merge Generation | ['Xinyu Yang', 'Yuwei An', 'Hongyi Liu', 'Tianqi Chen', 'Beidi Chen'] | ['cs.LG'] | Autoregressive Large Language Models (AR-LLMs) frequently exhibit implicit
parallelism in sequential generation. Inspired by this, we introduce
Multiverse, a new generative model that enables natively parallel generation.
Multiverse internalizes a MapReduce paradigm, generating automatically through
three stages: (i) a... | 2025-06-11T17:59:23Z | null | null | null | null | null | null | null | null | null | null |
2,506.10357 | Optimus-3: Towards Generalist Multimodal Minecraft Agents with Scalable
Task Experts | ['Zaijing Li', 'Yuquan Xie', 'Rui Shao', 'Gongwei Chen', 'Weili Guan', 'Dongmei Jiang', 'Liqiang Nie'] | ['cs.AI'] | Recently, agents based on multimodal large language models (MLLMs) have
achieved remarkable progress across various domains. However, building a
generalist agent with capabilities such as perception, planning, action,
grounding, and reflection in open-world environments like Minecraft remains
challenges: insufficient d... | 2025-06-12T05:29:40Z | 24 pages, 10 figures | null | null | null | null | null | null | null | null | null |
2,506.10452 | Towards Robust Multimodal Emotion Recognition under Missing Modalities
and Distribution Shifts | ['Guowei Zhong', 'Ruohong Huan', 'Mingzhen Wu', 'Ronghua Liang', 'Peng Chen'] | ['cs.CV', 'cs.CL', 'cs.LG', 'cs.MM'] | Recent advancements in Multimodal Emotion Recognition (MER) face challenges
in addressing both modality missing and Out-Of-Distribution (OOD) data
simultaneously. Existing methods often rely on specific models or introduce
excessive parameters, which limits their practicality. To address these issues,
we propose a nove... | 2025-06-12T07:58:17Z | Submitted to TAC. The code is available at
https://github.com/gw-zhong/CIDer | null | null | Towards Robust Multimodal Emotion Recognition under Missing Modalities and Distribution Shifts | ['Guowei Zhong', 'Ruohong Huan', 'Mingzhen Wu', 'Ronghua Liang', 'Peng Chen'] | 2,025 | arXiv.org | 0 | 41 | ['Computer Science'] |
2,506.10601 | Semantic-decoupled Spatial Partition Guided Point-supervised Oriented
Object Detection | ['Xinyuan Liu', 'Hang Xu', 'Yike Ma', 'Yucheng Zhang', 'Feng Dai'] | ['cs.CV'] | Recent remote sensing tech advancements drive imagery growth, making oriented
object detection rapid development, yet hindered by labor-intensive annotation
for high-density scenes. Oriented object detection with point supervision
offers a cost-effective solution for densely packed scenes in remote sensing,
yet existin... | 2025-06-12T11:44:34Z | null | null | null | null | null | null | null | null | null | null |
2,506.10707 | ConTextTab: A Semantics-Aware Tabular In-Context Learner | ['Marco Spinaci', 'Marek Polewczyk', 'Maximilian Schambach', 'Sam Thelin'] | ['cs.LG', 'cs.AI'] | Tabular in-context learning (ICL) has recently achieved state-of-the-art
(SOTA) performance on several tabular prediction tasks. Previously restricted
to classification problems on small tables, recent advances such as TabPFN and
TabICL have extended its use to larger datasets. While being architecturally
efficient and... | 2025-06-12T13:57:29Z | null | null | null | ConTextTab: A Semantics-Aware Tabular In-Context Learner | ['Marco Spinaci', 'Marek Polewczyk', 'Maximilian Schambach', 'Sam Thelin'] | 2,025 | arXiv.org | 0 | 38 | ['Computer Science'] |
2,506.10741 | PosterCraft: Rethinking High-Quality Aesthetic Poster Generation in a
Unified Framework | ['SiXiang Chen', 'Jianyu Lai', 'Jialin Gao', 'Tian Ye', 'Haoyu Chen', 'Hengyu Shi', 'Shitong Shao', 'Yunlong Lin', 'Song Fei', 'Zhaohu Xing', 'Yeying Jin', 'Junfeng Luo', 'Xiaoming Wei', 'Lei Zhu'] | ['cs.CV'] | Generating aesthetic posters is more challenging than simple design images:
it requires not only precise text rendering but also the seamless integration
of abstract artistic content, striking layouts, and overall stylistic harmony.
To address this, we propose PosterCraft, a unified framework that abandons
prior modula... | 2025-06-12T14:28:12Z | null | null | null | null | null | null | null | null | null | null |
2,506.10892 | The Diffusion Duality | ['Subham Sekhar Sahoo', 'Justin Deschenaux', 'Aaron Gokaslan', 'Guanghan Wang', 'Justin Chiu', 'Volodymyr Kuleshov'] | ['cs.LG', 'cs.AI', 'cs.CL'] | Uniform-state discrete diffusion models hold the promise of fast text
generation due to their inherent ability to self-correct. However, they are
typically outperformed by autoregressive models and masked diffusion models. In
this work, we narrow this performance gap by leveraging a key insight:
Uniform-state diffusion... | 2025-06-12T16:55:35Z | ICML 2025. We provide the code at: https://github.com/s-sahoo/duo | null | null | null | null | null | null | null | null | null |
2,506.10896 | BioClinical ModernBERT: A State-of-the-Art Long-Context Encoder for
Biomedical and Clinical NLP | ['Thomas Sounack', 'Joshua Davis', 'Brigitte Durieux', 'Antoine Chaffin', 'Tom J. Pollard', 'Eric Lehman', 'Alistair E. W. Johnson', 'Matthew McDermott', 'Tristan Naumann', 'Charlotta Lindvall'] | ['cs.CL', 'cs.AI'] | Encoder-based transformer models are central to biomedical and clinical
Natural Language Processing (NLP), as their bidirectional self-attention makes
them well-suited for efficiently extracting structured information from
unstructured text through discriminative tasks. However, encoders have seen
slower development co... | 2025-06-12T17:01:11Z | null | null | null | null | null | null | null | null | null | null |
2,506.1091 | Magistral | ['Mistral-AI', ':', 'Abhinav Rastogi', 'Albert Q. Jiang', 'Andy Lo', 'Gabrielle Berrada', 'Guillaume Lample', 'Jason Rute', 'Joep Barmentlo', 'Karmesh Yadav', 'Kartik Khandelwal', 'Khyathi Raghavi Chandu', 'Léonard Blier', 'Lucile Saulnier', 'Matthieu Dinot', 'Maxime Darrin', 'Neha Gupta', 'Roman Soletskyi', 'Sagar Vaz... | ['cs.CL'] | We introduce Magistral, Mistral's first reasoning model and our own scalable
reinforcement learning (RL) pipeline. Instead of relying on existing
implementations and RL traces distilled from prior models, we follow a ground
up approach, relying solely on our own models and infrastructure. Notably, we
demonstrate a stac... | 2025-06-12T17:22:37Z | null | null | null | null | null | null | null | null | null | null |
2,506.10941 | VINCIE: Unlocking In-context Image Editing from Video | ['Leigang Qu', 'Feng Cheng', 'Ziyan Yang', 'Qi Zhao', 'Shanchuan Lin', 'Yichun Shi', 'Yicong Li', 'Wenjie Wang', 'Tat-Seng Chua', 'Lu Jiang'] | ['cs.CV', 'cs.AI', 'cs.CL', 'cs.LG', 'cs.MM'] | In-context image editing aims to modify images based on a contextual sequence
comprising text and previously generated images. Existing methods typically
depend on task-specific pipelines and expert models (e.g., segmentation and
inpainting) to curate training data. In this work, we explore whether an
in-context image ... | 2025-06-12T17:46:54Z | Project page: https://vincie2025.github.io/ | null | null | null | null | null | null | null | null | null |
2,506.1096 | ChineseHarm-Bench: A Chinese Harmful Content Detection Benchmark | ['Kangwei Liu', 'Siyuan Cheng', 'Bozhong Tian', 'Xiaozhuan Liang', 'Yuyang Yin', 'Meng Han', 'Ningyu Zhang', 'Bryan Hooi', 'Xi Chen', 'Shumin Deng'] | ['cs.CL', 'cs.AI', 'cs.CR', 'cs.IR', 'cs.LG'] | Large language models (LLMs) have been increasingly applied to automated
harmful content detection tasks, assisting moderators in identifying policy
violations and improving the overall efficiency and accuracy of content review.
However, existing resources for harmful content detection are predominantly
focused on Engl... | 2025-06-12T17:57:05Z | Work in progress | null | null | null | null | null | null | null | null | null |
2,506.11029 | Output Scaling: YingLong-Delayed Chain of Thought in a Large Pretrained
Time Series Forecasting Model | ['Xue Wang', 'Tian Zhou', 'Jinyang Gao', 'Bolin Ding', 'Jingren Zhou'] | ['cs.LG', 'cs.AI'] | We present a joint forecasting framework for time series prediction that
contrasts with traditional direct or recursive methods. This framework achieves
state-of-the-art performance for our designed foundation model, YingLong, and
reveals a novel scaling effect: longer outputs significantly enhance model
accuracy due t... | 2025-05-20T14:31:06Z | null | null | null | Output Scaling: YingLong-Delayed Chain of Thought in a Large Pretrained Time Series Forecasting Model | ['Xue Wang', 'Tian Zhou', 'Jinyang Gao', 'Bolin Ding', 'Jingren Zhou'] | 2,025 | arXiv.org | 0 | 58 | ['Computer Science'] |
2,506.11115 | Incorporating Domain Knowledge into Materials Tokenization | ['Yerim Oh', 'Jun-Hyung Park', 'Junho Kim', 'SungHo Kim', 'SangKeun Lee'] | ['cs.CL', 'cs.AI'] | While language models are increasingly utilized in materials science, typical
models rely on frequency-centric tokenization methods originally developed for
natural language processing. However, these methods frequently produce
excessive fragmentation and semantic loss, failing to maintain the structural
and semantic i... | 2025-06-09T04:59:13Z | null | null | null | null | null | null | null | null | null | null |
2,506.1113 | A Self-Refining Framework for Enhancing ASR Using TTS-Synthesized Data | ['Cheng-Kang Chou', 'Chan-Jan Hsu', 'Ho-Lam Chung', 'Liang-Hsuan Tseng', 'Hsi-Chun Cheng', 'Yu-Kuan Fu', 'Kuan Po Huang', 'Hung-Yi Lee'] | ['cs.CL', 'cs.AI', 'cs.SD', 'eess.AS'] | We propose a self-refining framework that enhances ASR performance with only
unlabeled datasets. The process starts with an existing ASR model generating
pseudo-labels on unannotated speech, which are then used to train a
high-fidelity text-to-speech (TTS) system. Then, synthesized speech text pairs
are bootstrapped in... | 2025-06-10T17:30:32Z | null | null | null | null | null | null | null | null | null | null |
2,506.11305 | Don't Pay Attention | ['Mohammad Hammoud', 'Devang Acharya'] | ['cs.CL', 'cs.AI'] | The Transformer has become the de facto standard for large language models
and a wide range of downstream tasks across various domains. Despite its
numerous advantages like inherent training parallelism, the Transformer still
faces key challenges due to its inability to effectively process sequences
beyond a fixed cont... | 2025-06-12T21:11:06Z | null | null | null | null | null | null | null | null | null | null |
2,506.1135 | GLAP: General contrastive audio-text pretraining across domains and
languages | ['Heinrich Dinkel', 'Zhiyong Yan', 'Tianzi Wang', 'Yongqing Wang', 'Xingwei Sun', 'Yadong Niu', 'Jizhong Liu', 'Gang Li', 'Junbo Zhang', 'Jian Luan'] | ['cs.SD', 'cs.CL', 'eess.AS'] | Contrastive Language Audio Pretraining (CLAP) is a widely-used method to
bridge the gap between audio and text domains. Current CLAP methods enable
sound and music retrieval in English, ignoring multilingual spoken content. To
address this, we introduce general language audio pretraining (GLAP), which
expands CLAP with... | 2025-06-12T22:54:31Z | null | null | null | GLAP: General contrastive audio-text pretraining across domains and languages | ['Heinrich Dinkel', 'Zhiyong Yan', 'Tianzi Wang', 'Yongqing Wang', 'Xingwei Sun', 'Yadong Niu', 'Jizhong Liu', 'Gang Li', 'Junbo Zhang', 'Jian Luan'] | 2,025 | arXiv.org | 0 | 33 | ['Computer Science', 'Engineering'] |
2,506.11474 | Med-PRM: Medical Reasoning Models with Stepwise, Guideline-verified
Process Rewards | ['Jaehoon Yun', 'Jiwoong Sohn', 'Jungwoo Park', 'Hyunjae Kim', 'Xiangru Tang', 'Yanjun Shao', 'Yonghoe Koo', 'Minhyeok Ko', 'Qingyu Chen', 'Mark Gerstein', 'Michael Moor', 'Jaewoo Kang'] | ['cs.CL'] | Large language models have shown promise in clinical decision making, but
current approaches struggle to localize and correct errors at specific steps of
the reasoning process. This limitation is critical in medicine, where
identifying and addressing reasoning errors is essential for accurate diagnosis
and effective pa... | 2025-06-13T05:36:30Z | null | null | null | null | null | null | null | null | null | null |
2,506.11515 | Manager: Aggregating Insights from Unimodal Experts in Two-Tower VLMs
and MLLMs | ['Xiao Xu', 'Libo Qin', 'Wanxiang Che', 'Min-Yen Kan'] | ['cs.CV', 'cs.CL', 'cs.LG'] | Two-Tower Vision--Language Models (VLMs) have demonstrated strong performance
across various downstream VL tasks. While BridgeTower further enhances
performance by building bridges between encoders, it \textit{(i)} suffers from
ineffective layer-by-layer utilization of unimodal representations,
\textit{(ii)} restricts ... | 2025-06-13T07:16:41Z | Accepted by IEEE Transactions on Circuits and Systems for Video
Technology (TCSVT). June 2025. DOI:
https://doi.org/10.1109/TCSVT.2025.3578266 | null | 10.1109/TCSVT.2025.3578266 | Manager: Aggregating Insights from Unimodal Experts in Two-Tower VLMs and MLLMs | ['Xiao Xu', 'Libo Qin', 'Wanxiang Che', 'Min-Yen Kan'] | 2,025 | IEEE transactions on circuits and systems for video technology (Print) | 0 | 143 | ['Computer Science'] |
2,506.11543 | FIMA-Q: Post-Training Quantization for Vision Transformers by Fisher
Information Matrix Approximation | ['Zhuguanyu Wu', 'Shihe Wang', 'Jiayi Zhang', 'Jiaxin Chen', 'Yunhong Wang'] | ['cs.CV', 'cs.AI', 'cs.LG'] | Post-training quantization (PTQ) has stood out as a cost-effective and
promising model compression paradigm in recent years, as it avoids
computationally intensive model retraining. Nevertheless, current PTQ methods
for Vision Transformers (ViTs) still suffer from significant accuracy
degradation, especially under low-... | 2025-06-13T07:57:38Z | CVPR 2025 Highlight | null | null | null | null | null | null | null | null | null |
2,506.11702 | Configurable Preference Tuning with Rubric-Guided Synthetic Data | ['Víctor Gallego'] | ['cs.CL', 'cs.AI'] | Models of human feedback for AI alignment, such as those underpinning Direct
Preference Optimization (DPO), often bake in a singular, static set of
preferences, limiting adaptability. This paper challenges the assumption of
monolithic preferences by introducing Configurable Preference Tuning (CPT), a
novel framework fo... | 2025-06-13T12:17:38Z | Accepted to ICML 2025 Workshop on Models of Human Feedback for AI
Alignment | null | null | null | null | null | null | null | null | null |
2,506.11903 | GeistBERT: Breathing Life into German NLP | ['Raphael Scheible-Schmitt', 'Johann Frei'] | ['cs.CL'] | Advances in transformer-based language models have highlighted the benefits
of language-specific pre-training on high-quality corpora. In this context,
German NLP stands to gain from updated architectures and modern datasets
tailored to the linguistic characteristics of the German language. GeistBERT
seeks to improve G... | 2025-06-13T15:53:17Z | null | null | null | null | null | null | null | null | null | null |
2,506.11991 | VGR: Visual Grounded Reasoning | ['Jiacong Wang', 'Zijian Kang', 'Haochen Wang', 'Haiyong Jiang', 'Jiawen Li', 'Bohong Wu', 'Ya Wang', 'Jiao Ran', 'Xiao Liang', 'Chao Feng', 'Jun Xiao'] | ['cs.CV', 'cs.AI', 'cs.CL'] | In the field of multimodal chain-of-thought (CoT) reasoning, existing
approaches predominantly rely on reasoning on pure language space, which
inherently suffers from language bias and is largely confined to math or
science domains. This narrow focus limits their ability to handle complex
visual reasoning tasks that de... | 2025-06-13T17:47:43Z | 9 pages, 4 figures | null | null | null | null | null | null | null | null | null |
2,506.12119 | Can Mixture-of-Experts Surpass Dense LLMs Under Strictly Equal
Resources? | ['Houyi Li', 'Ka Man Lo', 'Ziqi Wang', 'Zili Wang', 'Wenzhen Zheng', 'Shuigeng Zhou', 'Xiangyu Zhang', 'Daxin Jiang'] | ['cs.CL', 'cs.AI'] | Mixture-of-Experts (MoE) language models dramatically expand model capacity
and achieve remarkable performance without increasing per-token compute.
However, can MoEs surpass dense architectures under strictly equal resource
constraints - that is, when the total parameter count, training compute, and
data budget are id... | 2025-06-13T17:59:05Z | null | null | null | Can Mixture-of-Experts Surpass Dense LLMs Under Strictly Equal Resources? | ['Houyi Li', 'Ka Man Lo', 'Ziqi Wang', 'Zili Wang', 'Wenzheng Zheng', 'Shuigeng Zhou', 'Xiangyu Zhang', 'Daxin Jiang'] | 2,025 | arXiv.org | 0 | 63 | ['Computer Science'] |
2,506.12242 | Large Language Models for History, Philosophy, and Sociology of Science:
Interpretive Uses, Methodological Challenges, and Critical Perspectives | ['Arno Simons', 'Michael Zichert', 'Adrian Wüthrich'] | ['cs.CL', 'cs.AI', 'cs.CY', 'A.1; I.2.1; I.2.7; J.4; J.5'] | This paper explores the use of large language models (LLMs) as research tools
in the history, philosophy, and sociology of science (HPSS). LLMs are
remarkably effective at processing unstructured text and inferring meaning from
context, offering new affordances that challenge long-standing divides between
computational... | 2025-06-13T21:44:13Z | 27 pages, 2 tables | null | null | Large Language Models for History, Philosophy, and Sociology of Science: Interpretive Uses, Methodological Challenges, and Critical Perspectives | ['Arno Simons', 'Michael Zichert', 'Adrian Wüthrich'] | 2,025 | arXiv.org | 0 | 79 | ['Computer Science'] |
2,506.12364 | MM-R5: MultiModal Reasoning-Enhanced ReRanker via Reinforcement Learning
for Document Retrieval | ['Mingjun Xu', 'Jinhan Dong', 'Jue Hou', 'Zehui Wang', 'Sihang Li', 'Zhifeng Gao', 'Renxin Zhong', 'Hengxing Cai'] | ['cs.AI', 'cs.CL', 'cs.CV'] | Multimodal document retrieval systems enable information access across text,
images, and layouts, benefiting various domains like document-based question
answering, report analysis, and interactive content summarization. Rerankers
improve retrieval precision by reordering retrieved candidates. However,
current multimod... | 2025-06-14T05:55:00Z | null | null | null | MM-R5: MultiModal Reasoning-Enhanced ReRanker via Reinforcement Learning for Document Retrieval | ['Mingjun Xu', 'Jinhan Dong', 'Jue Hou', 'Zehui Wang', 'Sihang Li', 'Zhifeng Gao', 'Renxin Zhong', 'Hengxing Cai'] | 2,025 | arXiv.org | 0 | 47 | ['Computer Science'] |
2,506.12473 | TagRouter: Learning Route to LLMs through Tags for Open-Domain Text
Generation Tasks | ['Zhou Chen', 'Zhiqiang Wei', 'Yuqi Bai', 'Xue Xiong', 'Jianmin Wu'] | ['cs.CL'] | Model routing allocates queries to the suitable model, improving system
performance while reducing costs. However, existing routing methods face
practical limitations that hinder scalability in large-scale applications and
struggle to keep up with the rapid growth of the large language model (LLM)
ecosystem. To tackle ... | 2025-06-14T12:17:47Z | ACL 2025, 26 pages, 13 figures, 14 tables | null | null | null | null | null | null | null | null | null |
2,506.12479 | AI Flow: Perspectives, Scenarios, and Approaches | ['Hongjun An', 'Wenhan Hu', 'Sida Huang', 'Siqi Huang', 'Ruanjun Li', 'Yuanzhi Liang', 'Jiawei Shao', 'Yiliang Song', 'Zihan Wang', 'Cheng Yuan', 'Chi Zhang', 'Hongyuan Zhang', 'Wenhao Zhuang', 'Xuelong Li'] | ['cs.AI', 'cs.CL', 'cs.CV', 'cs.DC', 'eess.SP'] | Pioneered by the foundational information theory by Claude Shannon and the
visionary framework of machine intelligence by Alan Turing, the convergent
evolution of information and communication technologies (IT/CT) has created an
unbroken wave of connectivity and computation. This synergy has sparked a
technological rev... | 2025-06-14T12:43:07Z | Authors are with Institute of Artificial Intelligence (TeleAI), China
Telecom, China. Author names are listed alphabetically by surname. This work
was conducted at TeleAI, facilitated by Dr. Jiawei Shao (e-mail:
shaojw2@chinatelecom.cn) under the leadership of Prof. Xuelong Li. The
corresponding author is Prof.... | null | null | null | null | null | null | null | null | null |
2,506.12704 | Flexible Realignment of Language Models | ['Wenhong Zhu', 'Ruobing Xie', 'Weinan Zhang', 'Rui Wang'] | ['cs.CL', 'cs.AI'] | Realignment becomes necessary when a language model (LM) fails to meet
expected performance. We propose a flexible realignment framework that supports
quantitative control of alignment degree during training and inference. This
framework incorporates Training-time Realignment (TrRa), which efficiently
realigns the refe... | 2025-06-15T03:26:59Z | null | null | null | null | null | null | null | null | null | null |
2,506.12776 | Native Visual Understanding: Resolving Resolution Dilemmas in
Vision-Language Models | ['Junbo Niu', 'Yuanhong Zheng', 'Ziyang Miao', 'Hejun Dong', 'Chunjiang Ge', 'Hao Liang', 'Ma Lu', 'Bohan Zeng', 'Qiahao Zheng', 'Conghui He', 'Wentao Zhang'] | ['cs.CV'] | Vision-Language Models (VLMs) face significant challenges when dealing with
the diverse resolutions and aspect ratios of real-world images, as most
existing models rely on fixed, low-resolution inputs. While recent studies have
explored integrating native resolution visual encoding to improve model
performance, such ef... | 2025-06-15T08:58:09Z | null | null | null | Native Visual Understanding: Resolving Resolution Dilemmas in Vision-Language Models | ['Junbo Niu', 'Yuanhong Zheng', 'Ziyang Miao', 'Hejun Dong', 'Chunjiang Ge', 'Hao Liang', 'Ma Lu', 'Bohan Zeng', 'Qiahao Zheng', 'Conghui He', 'Wentao Zhang'] | 2,025 | arXiv.org | 0 | 62 | ['Computer Science'] |
2,506.1286 | QFFT, Question-Free Fine-Tuning for Adaptive Reasoning | ['Wanlong Liu', 'Junxiao Xu', 'Fei Yu', 'Yukang Lin', 'Ke Ji', 'Wenyu Chen', 'Yan Xu', 'Yasheng Wang', 'Lifeng Shang', 'Benyou Wang'] | ['cs.CL'] | Recent advancements in Long Chain-of-Thought (CoT) reasoning models have
improved performance on complex tasks, but they suffer from overthinking, which
generates redundant reasoning steps, especially for simple questions. This
paper revisits the reasoning patterns of Long and Short CoT models, observing
that the Short... | 2025-06-15T14:21:28Z | 23 pages | null | null | QFFT, Question-Free Fine-Tuning for Adaptive Reasoning | ['Wanlong Liu', 'Junxiao Xu', 'Fei Yu', 'Yukang Lin', 'Ke Ji', 'Wenyu Chen', 'Yan Xu', 'Yasheng Wang', 'Lifeng Shang', 'Benyou Wang'] | 2,025 | arXiv.org | 0 | 48 | ['Computer Science'] |
2,506.13006 | Antibody Foundational Model : Ab-RoBERTa | ['Eunna Huh', 'Hyeonsu Lee', 'Hyunjin Shin'] | ['cs.LG', '68T50 (Primary) 68U15 (Secondary)'] | With the growing prominence of antibody-based therapeutics, antibody
engineering has gained increasing attention as a critical area of research and
development. Recent progress in transformer-based protein large language models
(LLMs) has demonstrated promising applications in protein sequence design and
structural pre... | 2025-06-16T00:22:07Z | 14 page, 3 figures, 5 tables | null | null | null | null | null | null | null | null | null |
2,506.13044 | Just Go Parallel: Improving the Multilingual Capabilities of Large
Language Models | ['Muhammad Reza Qorib', 'Junyi Li', 'Hwee Tou Ng'] | ['cs.CL', 'cs.AI'] | Large language models (LLMs) have demonstrated impressive translation
capabilities even without being explicitly trained on parallel data. This
remarkable property has led some to believe that parallel data is no longer
necessary for building multilingual language models. While some attribute this
to the emergent abili... | 2025-06-16T02:21:15Z | ACL 2025 | null | null | null | null | null | null | null | null | null |
2,506.13053 | ZipVoice: Fast and High-Quality Zero-Shot Text-to-Speech with Flow
Matching | ['Han Zhu', 'Wei Kang', 'Zengwei Yao', 'Liyong Guo', 'Fangjun Kuang', 'Zhaoqing Li', 'Weiji Zhuang', 'Long Lin', 'Daniel Povey'] | ['eess.AS', 'cs.SD'] | Existing large-scale zero-shot text-to-speech (TTS) models deliver high
speech quality but suffer from slow inference speeds due to massive parameters.
To address this issue, this paper introduces ZipVoice, a high-quality
flow-matching-based zero-shot TTS model with a compact model size and fast
inference speed. Key de... | 2025-06-16T02:48:17Z | null | null | null | null | null | null | null | null | null | null |
2,506.13056 | Metis-RISE: RL Incentivizes and SFT Enhances Multimodal Reasoning Model
Learning | ['Haibo Qiu', 'Xiaohan Lan', 'Fanfan Liu', 'Xiaohu Sun', 'Delian Ruan', 'Peng Shi', 'Lin Ma'] | ['cs.AI', 'cs.CV', 'cs.LG'] | Recent advancements in large language models (LLMs) have witnessed a surge in
the development of advanced reasoning paradigms, which are now being integrated
into multimodal large language models (MLLMs). However, existing approaches
often fall short: methods solely employing reinforcement learning (RL) can
struggle wi... | 2025-06-16T02:56:13Z | Project Page: https://github.com/MM-Thinking/Metis-RISE | null | null | null | null | null | null | null | null | null |
2,506.13277 | SeqPE: Transformer with Sequential Position Encoding | ['Huayang Li', 'Yahui Liu', 'Hongyu Sun', 'Deng Cai', 'Leyang Cui', 'Wei Bi', 'Peilin Zhao', 'Taro Watanabe'] | ['cs.LG', 'cs.AI', 'cs.CL', 'cs.CV'] | Since self-attention layers in Transformers are permutation invariant by
design, positional encodings must be explicitly incorporated to enable spatial
understanding. However, fixed-size lookup tables used in traditional learnable
position embeddings (PEs) limit extrapolation capabilities beyond pre-trained
sequence le... | 2025-06-16T09:16:40Z | null | null | null | SeqPE: Transformer with Sequential Position Encoding | ['Huyang Li', 'Yahui Liu', 'Hongyu Sun', 'Deng Cai', 'Leyang Cui', 'Wei Bi', 'Peilin Zhao', 'Taro Watanabe'] | 2,025 | arXiv.org | 0 | 54 | ['Computer Science'] |
2,506.13284 | AceReason-Nemotron 1.1: Advancing Math and Code Reasoning through SFT
and RL Synergy | ['Zihan Liu', 'Zhuolin Yang', 'Yang Chen', 'Chankyu Lee', 'Mohammad Shoeybi', 'Bryan Catanzaro', 'Wei Ping'] | ['cs.CL', 'cs.AI', 'cs.LG'] | In this work, we investigate the synergy between supervised fine-tuning (SFT)
and reinforcement learning (RL) in developing strong reasoning models. We begin
by curating the SFT training data through two scaling strategies: increasing
the number of collected prompts and the number of generated responses per
prompt. Bot... | 2025-06-16T09:27:48Z | The AceReason-Nemotron collection:
https://huggingface.co/collections/nvidia/acereason-682f4e1261dc22f697fd1485 | null | null | AceReason-Nemotron 1.1: Advancing Math and Code Reasoning through SFT and RL Synergy | ['Zihan Liu', 'Zhuoling Yang', 'Yang Chen', 'Chankyu Lee', 'M. Shoeybi', 'Bryan Catanzaro', 'Wei Ping'] | 2,025 | arXiv.org | 0 | 42 | ['Computer Science'] |
2,506.13342 | Verifying the Verifiers: Unveiling Pitfalls and Potentials in Fact
Verifiers | ['Wooseok Seo', 'Seungju Han', 'Jaehun Jung', 'Benjamin Newman', 'Seungwon Lim', 'Seungbeen Lee', 'Ximing Lu', 'Yejin Choi', 'Youngjae Yu'] | ['cs.AI', 'cs.CL', 'cs.LG'] | Fact verification is essential for ensuring the reliability of LLM
applications. In this study, we evaluate 12 pre-trained LLMs and one
specialized fact-verifier, including frontier LLMs and open-weight reasoning
LLMs, using a collection of examples from 14 fact-checking benchmarks. We share
three findings intended to ... | 2025-06-16T10:32:10Z | null | null | null | null | null | null | null | null | null | null |
2,506.13355 | DicFace: Dirichlet-Constrained Variational Codebook Learning for
Temporally Coherent Video Face Restoration | ['Yan Chen', 'Hanlin Shang', 'Ce Liu', 'Yuxuan Chen', 'Hui Li', 'Weihao Yuan', 'Hao Zhu', 'Zilong Dong', 'Siyu Zhu'] | ['cs.CV'] | Video face restoration faces a critical challenge in maintaining temporal
consistency while recovering fine facial details from degraded inputs. This
paper presents a novel approach that extends Vector-Quantized Variational
Autoencoders (VQ-VAEs), pretrained on static high-quality portraits, into a
video restoration fr... | 2025-06-16T10:54:28Z | null | null | null | null | null | null | null | null | null | null |
2,506.13414 | BUT System for the MLC-SLM Challenge | ['Alexander Polok', 'Jiangyu Han', 'Dominik Klement', 'Samuele Cornell', 'Jan Černocký', 'Lukáš Burget'] | ['eess.AS'] | We present a two-speaker automatic speech recognition (ASR) system that
combines DiCoW -- a diarization-conditioned variant of Whisper -- with
DiariZen, a diarization pipeline built on top of Pyannote. We first evaluate
both systems in out-of-domain (OOD) multilingual scenarios without any
fine-tuning. In this scenario... | 2025-06-16T12:28:35Z | null | null | null | null | null | null | null | null | null | null |
2,506.13585 | MiniMax-M1: Scaling Test-Time Compute Efficiently with Lightning
Attention | ['MiniMax', ':', 'Aili Chen', 'Aonian Li', 'Bangwei Gong', 'Binyang Jiang', 'Bo Fei', 'Bo Yang', 'Boji Shan', 'Changqing Yu', 'Chao Wang', 'Cheng Zhu', 'Chengjun Xiao', 'Chengyu Du', 'Chi Zhang', 'Chu Qiao', 'Chunhao Zhang', 'Chunhui Du', 'Congchao Guo', 'Da Chen', 'Deming Ding', 'Dianjun Sun', 'Dong Li', 'Enwei Jiao',... | ['cs.CL', 'cs.LG'] | We introduce MiniMax-M1, the world's first open-weight, large-scale
hybrid-attention reasoning model. MiniMax-M1 is powered by a hybrid
Mixture-of-Experts (MoE) architecture combined with a lightning attention
mechanism. The model is developed based on our previous MiniMax-Text-01 model,
which contains a total of 456 b... | 2025-06-16T15:08:02Z | A technical report from MiniMax. The authors are listed in
alphabetical order. We open-source our MiniMax-M1 at
https://github.com/MiniMax-AI/MiniMax-M1 | null | null | null | null | null | null | null | null | null |
2,506.13642 | Stream-Omni: Simultaneous Multimodal Interactions with Large
Language-Vision-Speech Model | ['Shaolei Zhang', 'Shoutao Guo', 'Qingkai Fang', 'Yan Zhou', 'Yang Feng'] | ['cs.AI', 'cs.CL', 'cs.CV', 'cs.SD', 'eess.AS'] | The emergence of GPT-4o-like large multimodal models (LMMs) has raised the
exploration of integrating text, vision, and speech modalities to support more
flexible multimodal interaction. Existing LMMs typically concatenate
representation of modalities along the sequence dimension and feed them into a
large language mod... | 2025-06-16T16:06:45Z | Code: https://github.com/ictnlp/Stream-Omni , Model:
https://huggingface.co/ICTNLP/stream-omni-8b | null | null | Stream-Omni: Simultaneous Multimodal Interactions with Large Language-Vision-Speech Model | ['Shaolei Zhang', 'Shoutao Guo', 'Qingkai Fang', 'Yan Zhou', 'Yang Feng'] | 2,025 | arXiv.org | 0 | 55 | ['Computer Science', 'Engineering'] |
2,506.13691 | UltraVideo: High-Quality UHD Video Dataset with Comprehensive Captions | ['Zhucun Xue', 'Jiangning Zhang', 'Teng Hu', 'Haoyang He', 'Yinan Chen', 'Yuxuan Cai', 'Yabiao Wang', 'Chengjie Wang', 'Yong Liu', 'Xiangtai Li', 'Dacheng Tao'] | ['cs.CV'] | The quality of the video dataset (image quality, resolution, and fine-grained
caption) greatly influences the performance of the video generation model. The
growing demand for video applications sets higher requirements for high-quality
video generation models. For example, the generation of movie-level Ultra-High
Defi... | 2025-06-16T16:52:52Z | null | null | null | null | null | null | null | null | null | null |
2,506.13705 | TimeMaster: Training Time-Series Multimodal LLMs to Reason via
Reinforcement Learning | ['Junru Zhang', 'Lang Feng', 'Xu Guo', 'Yuhan Wu', 'Yabo Dong', 'Duanqing Xu'] | ['cs.LG', 'cs.AI'] | Time-series reasoning remains a significant challenge in multimodal large
language models (MLLMs) due to the dynamic temporal patterns, ambiguous
semantics, and lack of temporal priors. In this work, we introduce TimeMaster,
a reinforcement learning (RL)-based method that enables time-series MLLMs to
perform structured... | 2025-06-16T17:12:26Z | Preprint | null | null | TimeMaster: Training Time-Series Multimodal LLMs to Reason via Reinforcement Learning | ['Junru Zhang', 'Lang Feng', 'Xu Guo', 'Yuhan Wu', 'Yabo Dong', 'Duanqing Xu'] | 2,025 | arXiv.org | 0 | 59 | ['Computer Science'] |
2,506.13725 | CEED-VLA: Consistency Vision-Language-Action Model with Early-Exit
Decoding | ['Wenxuan Song', 'Jiayi Chen', 'Pengxiang Ding', 'Yuxin Huang', 'Han Zhao', 'Donglin Wang', 'Haoang Li'] | ['cs.RO'] | In recent years, Vision-Language-Action (VLA) models have become a vital
research direction in robotics due to their impressive multimodal understanding
and generalization capabilities. Despite the progress, their practical
deployment is severely constrained by inference speed bottlenecks, particularly
in high-frequenc... | 2025-06-16T17:31:16Z | 16 pages | null | null | null | null | null | null | null | null | null |
2,506.13793 | Med-REFL: Medical Reasoning Enhancement via Self-Corrected Fine-grained
Reflection | ['Zongxian Yang', 'Jiayu Qian', 'Zegao Peng', 'Haoyu Zhang', 'Zhi-An Huang'] | ['cs.AI'] | Large reasoning models have recently made significant strides in mathematical
and code reasoning, yet their success has not transferred smoothly to the
medical domain. While multiple factors contribute to this disparity, a critical
issue is the inadequate focus on the quality of intermediate reflection steps,
which is ... | 2025-06-11T14:58:38Z | null | null | null | null | null | null | null | null | null | null |
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