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2,506.24119
SPIRAL: Self-Play on Zero-Sum Games Incentivizes Reasoning via Multi-Agent Multi-Turn Reinforcement Learning
['Bo Liu', 'Leon Guertler', 'Simon Yu', 'Zichen Liu', 'Penghui Qi', 'Daniel Balcells', 'Mickel Liu', 'Cheston Tan', 'Weiyan Shi', 'Min Lin', 'Wee Sun Lee', 'Natasha Jaques']
['cs.AI', 'cs.CL', 'cs.LG']
Recent advances in reinforcement learning have shown that language models can develop sophisticated reasoning through training on tasks with verifiable rewards, but these approaches depend on human-curated problem-answer pairs and domain-specific reward engineering. We introduce SPIRAL, a self-play framework where mode...
2025-06-30T17:58:13Z
Work in Progress
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2,507.00432
Does Math Reasoning Improve General LLM Capabilities? Understanding Transferability of LLM Reasoning
['Maggie Huan', 'Yuetai Li', 'Tuney Zheng', 'Xiaoyu Xu', 'Seungone Kim', 'Minxin Du', 'Radha Poovendran', 'Graham Neubig', 'Xiang Yue']
['cs.AI', 'cs.CL']
Math reasoning has become the poster child of progress in large language models (LLMs), with new models rapidly surpassing human-level performance on benchmarks like MATH and AIME. But as math leaderboards improve week by week, it is worth asking: do these gains reflect broader problem-solving ability or just narrow ov...
2025-07-01T05:23:05Z
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2,507.00505
LLaVA-SP: Enhancing Visual Representation with Visual Spatial Tokens for MLLMs
['Haoran Lou', 'Chunxiao Fan', 'Ziyan Liu', 'Yuexin Wu', 'Xinliang Wang']
['cs.CV']
The architecture of multimodal large language models (MLLMs) commonly connects a vision encoder, often based on CLIP-ViT, to a large language model. While CLIP-ViT works well for capturing global image features, it struggles to model local relationships between adjacent patches, leading to weaker visual representation,...
2025-07-01T07:20:11Z
Accepted to ICCV 2025
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2,507.00833
HumanoidGen: Data Generation for Bimanual Dexterous Manipulation via LLM Reasoning
['Zhi Jing', 'Siyuan Yang', 'Jicong Ao', 'Ting Xiao', 'Yugang Jiang', 'Chenjia Bai']
['cs.RO', 'cs.AI']
For robotic manipulation, existing robotics datasets and simulation benchmarks predominantly cater to robot-arm platforms. However, for humanoid robots equipped with dual arms and dexterous hands, simulation tasks and high-quality demonstrations are notably lacking. Bimanual dexterous manipulation is inherently more co...
2025-07-01T15:04:38Z
Project Page: https://openhumanoidgen.github.io
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2,507.00971
Reasoning as an Adaptive Defense for Safety
['Taeyoun Kim', 'Fahim Tajwar', 'Aditi Raghunathan', 'Aviral Kumar']
['cs.LG', 'cs.AI']
Reasoning methods that adaptively allocate test-time compute have advanced LLM performance on easy to verify domains such as math and code. In this work, we study how to utilize this approach to train models that exhibit a degree of robustness to safety vulnerabilities, and show that doing so can provide benefits. We b...
2025-07-01T17:20:04Z
42 pages, 11 Figures, 7 Tables
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2,507.00994
Should We Still Pretrain Encoders with Masked Language Modeling?
['Hippolyte Gisserot-Boukhlef', 'Nicolas Boizard', 'Manuel Faysse', 'Duarte M. Alves', 'Emmanuel Malherbe', 'André F. T. Martins', 'Céline Hudelot', 'Pierre Colombo']
['cs.CL']
Learning high-quality text representations is fundamental to a wide range of NLP tasks. While encoder pretraining has traditionally relied on Masked Language Modeling (MLM), recent evidence suggests that decoder models pretrained with Causal Language Modeling (CLM) can be effectively repurposed as encoders, often surpa...
2025-07-01T17:45:48Z
23 pages, 10 figures, 17 tables
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2,507.01006
GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning
['GLM-V Team', ':', 'Wenyi Hong', 'Wenmeng Yu', 'Xiaotao Gu', 'Guo Wang', 'Guobing Gan', 'Haomiao Tang', 'Jiale Cheng', 'Ji Qi', 'Junhui Ji', 'Lihang Pan', 'Shuaiqi Duan', 'Weihan Wang', 'Yan Wang', 'Yean Cheng', 'Zehai He', 'Zhe Su', 'Zhen Yang', 'Ziyang Pan', 'Aohan Zeng', 'Baoxu Wang', 'Boyan Shi', 'Changyu Pang', '...
['cs.CV', 'cs.AI', 'cs.LG']
We present GLM-4.1V-Thinking, a vision-language model (VLM) designed to advance general-purpose multimodal understanding and reasoning. In this report, we share our key findings in the development of the reasoning-centric training framework. We first develop a capable vision foundation model with significant potential ...
2025-07-01T17:55:04Z
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2,507.01255
AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation
['Xiao Liu', 'Jiawei Zhang']
['cs.CV']
The rapid advancement of AI-generated video models has created a pressing need for robust and interpretable evaluation frameworks. Existing metrics are limited to producing numerical scores without explanatory comments, resulting in low interpretability and human evaluation alignment. To address those challenges, we in...
2025-07-02T00:20:06Z
Working in Progress
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2,507.01352
Skywork-Reward-V2: Scaling Preference Data Curation via Human-AI Synergy
['Chris Yuhao Liu', 'Liang Zeng', 'Yuzhen Xiao', 'Jujie He', 'Jiacai Liu', 'Chaojie Wang', 'Rui Yan', 'Wei Shen', 'Fuxiang Zhang', 'Jiacheng Xu', 'Yang Liu', 'Yahui Zhou']
['cs.CL', 'cs.AI', 'cs.LG']
Despite the critical role of reward models (RMs) in reinforcement learning from human feedback (RLHF), current state-of-the-art open RMs perform poorly on most existing evaluation benchmarks, failing to capture the spectrum of nuanced and sophisticated human preferences. Even approaches that incorporate advanced traini...
2025-07-02T04:40:29Z
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2,507.01472
Optimizing Methane Detection On Board Satellites: Speed, Accuracy, and Low-Power Solutions for Resource-Constrained Hardware
['Jonáš Herec', 'Vít Růžička', 'Rado Pitoňák']
['cs.CV', 'cs.LG', 'cs.PF']
Methane is a potent greenhouse gas, and detecting its leaks early via hyperspectral satellite imagery can help mitigate climate change. Meanwhile, many existing missions operate in manual tasking regimes only, thus missing potential events of interest. To overcome slow downlink rates cost-effectively, onboard detection...
2025-07-02T08:34:34Z
This is a preprint of a paper accepted for the EDHPC 2025 Conference
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2,507.01634
Depth Anything at Any Condition
['Boyuan Sun', 'Modi Jin', 'Bowen Yin', 'Qibin Hou']
['cs.CV', 'cs.AI']
We present Depth Anything at Any Condition (DepthAnything-AC), a foundation monocular depth estimation (MDE) model capable of handling diverse environmental conditions. Previous foundation MDE models achieve impressive performance across general scenes but not perform well in complex open-world environments that involv...
2025-07-02T12:05:57Z
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2,507.01643
SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement
['Weijie Yin', 'Dingkang Yang', 'Hongyuan Dong', 'Zijian Kang', 'Jiacong Wang', 'Xiao Liang', 'Chao Feng', 'Jiao Ran']
['cs.CV']
Vision Transformers (ViTs) are essential as foundation backbones in establishing the visual comprehension capabilities of Multimodal Large Language Models (MLLMs). Although most ViTs achieve impressive performance through image-text pair-based contrastive learning or self-supervised mechanisms, they struggle to engage ...
2025-07-02T12:17:23Z
We release SAILViT, a series of versatile vision foundation models
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2,507.01738
DeRIS: Decoupling Perception and Cognition for Enhanced Referring Image Segmentation through Loopback Synergy
['Ming Dai', 'Wenxuan Cheng', 'Jiang-jiang Liu', 'Sen Yang', 'Wenxiao Cai', 'Yanpeng Sun', 'Wankou Yang']
['cs.CV']
Referring Image Segmentation (RIS) is a challenging task that aims to segment objects in an image based on natural language expressions. While prior studies have predominantly concentrated on improving vision-language interactions and achieving fine-grained localization, a systematic analysis of the fundamental bottlen...
2025-07-02T14:14:35Z
ICCV 2025
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2,507.01931
Adaptability of ASR Models on Low-Resource Language: A Comparative Study of Whisper and Wav2Vec-BERT on Bangla
['Md Sazzadul Islam Ridoy', 'Sumi Akter', 'Md. Aminur Rahman']
['cs.CL', 'cs.AI', 'cs.SD', 'eess.AS']
In recent years, neural models trained on large multilingual text and speech datasets have shown great potential for supporting low-resource languages. This study investigates the performances of two state-of-the-art Automatic Speech Recognition (ASR) models, OpenAI's Whisper (Small & Large-V2) and Facebook's Wav2Vec-B...
2025-07-02T17:44:54Z
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2,507.01949
Kwai Keye-VL Technical Report
['Kwai Keye Team', 'Biao Yang', 'Bin Wen', 'Changyi Liu', 'Chenglong Chu', 'Chengru Song', 'Chongling Rao', 'Chuan Yi', 'Da Li', 'Dunju Zang', 'Fan Yang', 'Guorui Zhou', 'Hao Peng', 'Haojie Ding', 'Jiaming Huang', 'Jiangxia Cao', 'Jiankang Chen', 'Jingyun Hua', 'Jin Ouyang', 'Kaibing Chen', 'Kaiyu Jiang', 'Kaiyu Tang',...
['cs.CV']
While Multimodal Large Language Models (MLLMs) demonstrate remarkable capabilities on static images, they often fall short in comprehending dynamic, information-dense short-form videos, a dominant medium in today's digital landscape. To bridge this gap, we introduce \textbf{Kwai Keye-VL}, an 8-billion-parameter multimo...
2025-07-02T17:57:28Z
Technical Report: https://github.com/Kwai-Keye/Keye
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2,507.01951
Test-Time Scaling with Reflective Generative Model
['Zixiao Wang', 'Yuxin Wang', 'Xiaorui Wang', 'Mengting Xing', 'Jie Gao', 'Jianjun Xu', 'Guangcan Liu', 'Chenhui Jin', 'Zhuo Wang', 'Shengzhuo Zhang', 'Hongtao Xie']
['cs.LG', 'cs.CL']
We introduce our first reflective generative model MetaStone-S1, which obtains OpenAI o3-mini's performance via the new Reflective Generative Form. The new form focuses on high-quality reasoning trajectory selection and contains two novelties: 1) A unified interface for policy and process reward model: we share the bac...
2025-07-02T17:58:01Z
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2,507.01991
FinAI-BERT: A Transformer-Based Model for Sentence-Level Detection of AI Disclosures in Financial Reports
['Muhammad Bilal Zafar']
['q-fin.CP', 'cs.CL', 'econ.GN', 'q-fin.EC', 'q-fin.GN']
The proliferation of artificial intelligence (AI) in financial services has prompted growing demand for tools that can systematically detect AI-related disclosures in corporate filings. While prior approaches often rely on keyword expansion or document-level classification, they fall short in granularity, interpretabil...
2025-06-29T09:33:29Z
The FinAI-BERT model can be directly loaded via Hugging Face Transformers (https://huggingface.co/bilalzafar/FinAI-BERT) for sentence-level AI disclosure classification
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2,507.02025
IntFold: A Controllable Foundation Model for General and Specialized Biomolecular Structure Prediction
['The IntFold Team', 'Leon Qiao', 'Wayne Bai', 'He Yan', 'Gary Liu', 'Nova Xi', 'Xiang Zhang', 'Siqi Sun']
['q-bio.BM']
We introduce IntFold, a controllable foundation model for general and specialized biomolecular structure prediction. Utilizing a high-performance custom attention kernel, IntFold achieves accuracy comparable to the state-of-the-art AlphaFold 3 on a comprehensive benchmark of diverse biomolecular structures, while also ...
2025-07-02T16:09:47Z
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2,507.02029
RoboBrain 2.0 Technical Report
['BAAI RoboBrain Team', 'Mingyu Cao', 'Huajie Tan', 'Yuheng Ji', 'Minglan Lin', 'Zhiyu Li', 'Zhou Cao', 'Pengwei Wang', 'Enshen Zhou', 'Yi Han', 'Yingbo Tang', 'Xiangqi Xu', 'Wei Guo', 'Yaoxu Lyu', 'Yijie Xu', 'Jiayu Shi', 'Mengfei Du', 'Cheng Chi', 'Mengdi Zhao', 'Xiaoshuai Hao', 'Junkai Zhao', 'Xiaojie Zhang', 'Shany...
['cs.RO']
We introduce RoboBrain 2.0, our latest generation of embodied vision-language foundation models, designed to unify perception, reasoning, and planning for complex embodied tasks in physical environments. It comes in two variants: a lightweight 7B model and a full-scale 32B model, featuring a heterogeneous architecture ...
2025-07-02T17:05:33Z
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2,507.02259
MemAgent: Reshaping Long-Context LLM with Multi-Conv RL-based Memory Agent
['Hongli Yu', 'Tinghong Chen', 'Jiangtao Feng', 'Jiangjie Chen', 'Weinan Dai', 'Qiying Yu', 'Ya-Qin Zhang', 'Wei-Ying Ma', 'Jingjing Liu', 'Mingxuan Wang', 'Hao Zhou']
['cs.CL', 'cs.AI', 'cs.LG']
Despite improvements by length extrapolation, efficient attention and memory modules, handling infinitely long documents with linear complexity without performance degradation during extrapolation remains the ultimate challenge in long-text processing. We directly optimize for long-text tasks in an end-to-end fashion a...
2025-07-03T03:11:50Z
Project Page: https://memagent-sialab.github.io/
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2,507.02735
Meta SecAlign: A Secure Foundation LLM Against Prompt Injection Attacks
['Sizhe Chen', 'Arman Zharmagambetov', 'David Wagner', 'Chuan Guo']
['cs.CR', 'cs.AI']
Prompt injection attacks pose a significant security threat to LLM-integrated applications. Model-level defenses have shown strong effectiveness, but are currently deployed into commercial-grade models in a closed-source manner. We believe open-source models are needed by the AI security community, where co-development...
2025-07-03T15:47:13Z
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2,507.02768
DeSTA2.5-Audio: Toward General-Purpose Large Audio Language Model with Self-Generated Cross-Modal Alignment
['Ke-Han Lu', 'Zhehuai Chen', 'Szu-Wei Fu', 'Chao-Han Huck Yang', 'Sung-Feng Huang', 'Chih-Kai Yang', 'Chee-En Yu', 'Chun-Wei Chen', 'Wei-Chih Chen', 'Chien-yu Huang', 'Yi-Cheng Lin', 'Yu-Xiang Lin', 'Chi-An Fu', 'Chun-Yi Kuan', 'Wenze Ren', 'Xuanjun Chen', 'Wei-Ping Huang', 'En-Pei Hu', 'Tzu-Quan Lin', 'Yuan-Kuei Wu',...
['eess.AS', 'cs.CL', 'cs.SD']
We introduce DeSTA2.5-Audio, a general-purpose Large Audio Language Model (LALM) designed for robust auditory perception and instruction-following, without requiring task-specific audio instruction-tuning. Recent LALMs typically augment Large Language Models (LLMs) with auditory capabilities by training on large-scale,...
2025-07-03T16:28:25Z
Model and code available at: https://github.com/kehanlu/DeSTA2.5-Audio
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2,507.02813
LangScene-X: Reconstruct Generalizable 3D Language-Embedded Scenes with TriMap Video Diffusion
['Fangfu Liu', 'Hao Li', 'Jiawei Chi', 'Hanyang Wang', 'Minghui Yang', 'Fudong Wang', 'Yueqi Duan']
['cs.CV']
Recovering 3D structures with open-vocabulary scene understanding from 2D images is a fundamental but daunting task. Recent developments have achieved this by performing per-scene optimization with embedded language information. However, they heavily rely on the calibrated dense-view reconstruction paradigm, thereby su...
2025-07-03T17:21:23Z
Project page: https://liuff19.github.io/LangScene-X
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2,507.02851
MOTIF: Modular Thinking via Reinforcement Fine-tuning in LLMs
['Purbesh Mitra', 'Sennur Ulukus']
['cs.CL', 'cs.AI', 'cs.IT', 'cs.LG', 'cs.SY', 'eess.SY', 'math.IT']
Recent advancements in the reasoning capabilities of large language models (LLMs) show that employing group relative policy optimization (GRPO) algorithm for reinforcement learning (RL) training allows the models to use more thinking/reasoning tokens for generating better responses. However, LLMs can generate only a fi...
2025-07-03T17:55:43Z
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2,507.03033
Preserving Privacy, Increasing Accessibility, and Reducing Cost: An On-Device Artificial Intelligence Model for Medical Transcription and Note Generation
['Johnson Thomas', 'Ayush Mudgal', 'Wendao Liu', 'Nisten Tahiraj', 'Zeeshaan Mohammed', 'Dhruv Diddi']
['cs.CL', 'cs.AI']
Background: Clinical documentation represents a significant burden for healthcare providers, with physicians spending up to 2 hours daily on administrative tasks. Recent advances in large language models (LLMs) offer promising solutions, but privacy concerns and computational requirements limit their adoption in health...
2025-07-03T01:51:49Z
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2,507.03112
RLVER: Reinforcement Learning with Verifiable Emotion Rewards for Empathetic Agents
['Peisong Wang', 'Ruotian Ma', 'Bang Zhang', 'Xingyu Chen', 'Zhiwei He', 'Kang Luo', 'Qingsong Lv', 'Qingxuan Jiang', 'Zheng Xie', 'Shanyi Wang', 'Yuan Li', 'Fanghua Ye', 'Jian Li', 'Yifan Yang', 'Zhaopeng Tu', 'Xiaolong Li']
['cs.CL', 'cs.AI', 'cs.CY']
Large language models (LLMs) excel at logical and algorithmic reasoning, yet their emotional intelligence (EQ) still lags far behind their cognitive prowess. While reinforcement learning from verifiable rewards (RLVR) has advanced in other domains, its application to dialogue-especially for emotional intelligence-remai...
2025-07-03T18:33:18Z
Code: https://github.com/Tencent/DigitalHuman/tree/main/RLVER
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2,507.03152
Expert-level validation of AI-generated medical text with scalable language models
['Asad Aali', 'Vasiliki Bikia', 'Maya Varma', 'Nicole Chiou', 'Sophie Ostmeier', 'Arnav Singhvi', 'Magdalini Paschali', 'Ashwin Kumar', 'Andrew Johnston', 'Karimar Amador-Martinez', 'Eduardo Juan Perez Guerrero', 'Paola Naovi Cruz Rivera', 'Sergios Gatidis', 'Christian Bluethgen', 'Eduardo Pontes Reis', 'Eddy D. Zandee...
['cs.CL', 'cs.AI', 'cs.LG']
With the growing use of language models (LMs) in clinical environments, there is an immediate need to evaluate the accuracy and safety of LM-generated medical text. Currently, such evaluation relies solely on manual physician review. However, detecting errors in LM-generated text is challenging because 1) manual review...
2025-07-03T20:19:18Z
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2,507.03482
OMAR-RQ: Open Music Audio Representation Model Trained with Multi-Feature Masked Token Prediction
['Pablo Alonso-Jiménez', 'Pedro Ramoneda', 'R. Oguz Araz', 'Andrea Poltronieri', 'Dmitry Bogdanov']
['cs.SD', 'eess.AS']
Developing open-source foundation models is essential for advancing research in music audio understanding and ensuring access to powerful, multipurpose representations for music information retrieval. We present OMAR-RQ, a model trained with self-supervision via masked token classification methodologies using a large-s...
2025-07-04T11:19:47Z
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2,507.03607
VLAI: A RoBERTa-Based Model for Automated Vulnerability Severity Classification
['Cédric Bonhomme', 'Alexandre Dulaunoy']
['cs.CR']
This paper presents VLAI, a transformer-based model that predicts software vulnerability severity levels directly from text descriptions. Built on RoBERTa, VLAI is fine-tuned on over 600,000 real-world vulnerabilities and achieves over 82% accuracy in predicting severity categories, enabling faster and more consistent ...
2025-07-04T14:28:14Z
This paper is a preprint for the 25V4C-TC: 2025 Vulnerability Forecasting Technical Colloquia. Darwin College Cambridge, UK, September 25-26, 2025
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2,507.03738
Flow-Anchored Consistency Models
['Yansong Peng', 'Kai Zhu', 'Yu Liu', 'Pingyu Wu', 'Hebei Li', 'Xiaoyan Sun', 'Feng Wu']
['cs.CV']
Continuous-time Consistency Models (CMs) promise efficient few-step generation but face significant challenges with training instability. We argue this instability stems from a fundamental conflict: by training a network to learn only a shortcut across a probability flow, the model loses its grasp on the instantaneous ...
2025-07-04T17:56:51Z
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2,507.04569
Nile-Chat: Egyptian Language Models for Arabic and Latin Scripts
['Guokan Shang', 'Hadi Abdine', 'Ahmad Chamma', 'Amr Mohamed', 'Mohamed Anwar', 'Abdelaziz Bounhar', 'Omar El Herraoui', 'Preslav Nakov', 'Michalis Vazirgiannis', 'Eric Xing']
['cs.CL', 'cs.AI', 'cs.LG']
We introduce Nile-Chat-4B, 3x4B-A6B, and 12B, a collection of LLMs for Egyptian dialect, uniquely designed to understand and generate texts written in both Arabic and Latin scripts. Specifically, with Nile-Chat-3x4B-A6B, we introduce a novel language adaptation approach by leveraging the Branch-Train-MiX strategy to me...
2025-07-06T22:53:41Z
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2,507.0459
VLM2Vec-V2: Advancing Multimodal Embedding for Videos, Images, and Visual Documents
['Rui Meng', 'Ziyan Jiang', 'Ye Liu', 'Mingyi Su', 'Xinyi Yang', 'Yuepeng Fu', 'Can Qin', 'Zeyuan Chen', 'Ran Xu', 'Caiming Xiong', 'Yingbo Zhou', 'Wenhu Chen', 'Semih Yavuz']
['cs.CV', 'cs.CL']
Multimodal embedding models have been crucial in enabling various downstream tasks such as semantic similarity, information retrieval, and clustering over different modalities. However, existing multimodal embeddings like VLM2Vec, E5-V, GME are predominantly focused on natural images, with limited support for other vis...
2025-07-07T00:51:57Z
Technical Report
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2,507.04612
Retain or Reframe? A Computational Framework for the Analysis of Framing in News Articles and Reader Comments
['Matteo Guida', 'Yulia Otmakhova', 'Eduard Hovy', 'Lea Frermann']
['cs.CL']
When a news article describes immigration as an "economic burden" or a "humanitarian crisis," it selectively emphasizes certain aspects of the issue. Although \textit{framing} shapes how the public interprets such issues, audiences do not absorb frames passively but actively reorganize the presented information. While ...
2025-07-07T02:05:56Z
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2,507.04635
MODA: MOdular Duplex Attention for Multimodal Perception, Cognition, and Emotion Understanding
['Zhicheng Zhang', 'Wuyou Xia', 'Chenxi Zhao', 'Zhou Yan', 'Xiaoqiang Liu', 'Yongjie Zhu', 'Wenyu Qin', 'Pengfei Wan', 'Di Zhang', 'Jufeng Yang']
['cs.CV']
Multimodal large language models (MLLMs) recently showed strong capacity in integrating data among multiple modalities, empowered by a generalizable attention architecture. Advanced methods predominantly focus on language-centric tuning while less exploring multimodal tokens mixed through attention, posing challenges i...
2025-07-07T03:37:42Z
ICML 2025 (Spotlight, Top 2.6%)
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2,507.04886
Emergent Semantics Beyond Token Embeddings: Transformer LMs with Frozen Visual Unicode Representations
['A. Bochkov']
['cs.CL', 'cs.AI']
Understanding the locus of semantic representation in large language models (LLMs) is crucial for interpretability and architectural innovation. The dominant paradigm posits that trainable input embeddings serve as foundational "meaning vectors." This paper challenges that view. We construct Transformer models where th...
2025-07-07T11:17:32Z
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2,507.05197
Pre-Trained Policy Discriminators are General Reward Models
['Shihan Dou', 'Shichun Liu', 'Yuming Yang', 'Yicheng Zou', 'Yunhua Zhou', 'Shuhao Xing', 'Chenhao Huang', 'Qiming Ge', 'Demin Song', 'Haijun Lv', 'Songyang Gao', 'Chengqi Lv', 'Enyu Zhou', 'Honglin Guo', 'Zhiheng Xi', 'Wenwei Zhang', 'Qipeng Guo', 'Qi Zhang', 'Xipeng Qiu', 'Xuanjing Huang', 'Tao Gui', 'Kai Chen']
['cs.CL', 'cs.LG']
We offer a novel perspective on reward modeling by formulating it as a policy discriminator, which quantifies the difference between two policies to generate a reward signal, guiding the training policy towards a target policy with desired behaviors. Based on this conceptual insight, we propose a scalable pre-training ...
2025-07-07T16:56:31Z
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2,507.05201
MedGemma Technical Report
['Andrew Sellergren', 'Sahar Kazemzadeh', 'Tiam Jaroensri', 'Atilla Kiraly', 'Madeleine Traverse', 'Timo Kohlberger', 'Shawn Xu', 'Fayaz Jamil', 'Cían Hughes', 'Charles Lau', 'Justin Chen', 'Fereshteh Mahvar', 'Liron Yatziv', 'Tiffany Chen', 'Bram Sterling', 'Stefanie Anna Baby', 'Susanna Maria Baby', 'Jeremy Lai', 'Sa...
['cs.AI', 'cs.CL', 'cs.CV']
Artificial intelligence (AI) has significant potential in healthcare applications, but its training and deployment faces challenges due to healthcare's diverse data, complex tasks, and the need to preserve privacy. Foundation models that perform well on medical tasks and require less task-specific tuning data are criti...
2025-07-07T17:01:44Z
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2,507.0524
StreamVLN: Streaming Vision-and-Language Navigation via SlowFast Context Modeling
['Meng Wei', 'Chenyang Wan', 'Xiqian Yu', 'Tai Wang', 'Yuqiang Yang', 'Xiaohan Mao', 'Chenming Zhu', 'Wenzhe Cai', 'Hanqing Wang', 'Yilun Chen', 'Xihui Liu', 'Jiangmiao Pang']
['cs.RO', 'cs.CV']
Vision-and-Language Navigation (VLN) in real-world settings requires agents to process continuous visual streams and generate actions with low latency grounded in language instructions. While Video-based Large Language Models (Video-LLMs) have driven recent progress, current VLN methods based on Video-LLM often face tr...
2025-07-07T17:49:41Z
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2,507.05513
Llama Nemoretriever Colembed: Top-Performing Text-Image Retrieval Model
['Mengyao Xu', 'Gabriel Moreira', 'Ronay Ak', 'Radek Osmulski', 'Yauhen Babakhin', 'Zhiding Yu', 'Benedikt Schifferer', 'Even Oldridge']
['cs.CV', 'cs.AI']
Motivated by the growing demand for retrieval systems that operate across modalities, we introduce llama-nemoretriever-colembed, a unified text-image retrieval model that delivers state-of-the-art performance across multiple benchmarks. We release two model variants, 1B and 3B. The 3B model achieves state of the art pe...
2025-07-07T22:20:04Z
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2,507.05517
Empowering Healthcare Practitioners with Language Models: Structuring Speech Transcripts in Two Real-World Clinical Applications
['Jean-Philippe Corbeil', 'Asma Ben Abacha', 'George Michalopoulos', 'Phillip Swazinna', 'Miguel Del-Agua', 'Jerome Tremblay', 'Akila Jeeson Daniel', 'Cari Bader', 'Yu-Cheng Cho', 'Pooja Krishnan', 'Nathan Bodenstab', 'Thomas Lin', 'Wenxuan Teng', 'Francois Beaulieu', 'Paul Vozila']
['cs.CL', 'cs.AI']
Large language models (LLMs) such as GPT-4o and o1 have demonstrated strong performance on clinical natural language processing (NLP) tasks across multiple medical benchmarks. Nonetheless, two high-impact NLP tasks - structured tabular reporting from nurse dictations and medical order extraction from doctor-patient con...
2025-07-07T22:29:29Z
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2,507.06167
Skywork-R1V3 Technical Report
['Wei Shen', 'Jiangbo Pei', 'Yi Peng', 'Xuchen Song', 'Yang Liu', 'Jian Peng', 'Haofeng Sun', 'Yunzhuo Hao', 'Peiyu Wang', 'Jianhao Zhang', 'Yahui Zhou']
['cs.CL', 'cs.CV']
We introduce Skywork-R1V3, an advanced, open-source vision-language model (VLM) that pioneers a new approach to visual reasoning. Its key innovation lies in effectively transferring reasoning skills from text-only Large Language Models (LLMs) to visual tasks. The strong performance of Skywork-R1V3 primarily stems from ...
2025-07-08T16:47:16Z
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2,507.06181
CriticLean: Critic-Guided Reinforcement Learning for Mathematical Formalization
['Zhongyuan Peng', 'Yifan Yao', 'Kaijing Ma', 'Shuyue Guo', 'Yizhe Li', 'Yichi Zhang', 'Chenchen Zhang', 'Yifan Zhang', 'Zhouliang Yu', 'Luming Li', 'Minghao Liu', 'Yihang Xia', 'Jiawei Shen', 'Yuchen Wu', 'Yixin Cao', 'Zhaoxiang Zhang', 'Wenhao Huang', 'Jiaheng Liu', 'Ge Zhang']
['cs.CL']
Translating natural language mathematical statements into formal, executable code is a fundamental challenge in automated theorem proving. While prior work has focused on generation and compilation success, little attention has been paid to the critic phase-the evaluation of whether generated formalizations truly captu...
2025-07-08T17:03:39Z
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2,507.0623
Feed-Forward SceneDINO for Unsupervised Semantic Scene Completion
['Aleksandar Jevtić', 'Christoph Reich', 'Felix Wimbauer', 'Oliver Hahn', 'Christian Rupprecht', 'Stefan Roth', 'Daniel Cremers']
['cs.CV']
Semantic scene completion (SSC) aims to infer both the 3D geometry and semantics of a scene from single images. In contrast to prior work on SSC that heavily relies on expensive ground-truth annotations, we approach SSC in an unsupervised setting. Our novel method, SceneDINO, adapts techniques from self-supervised repr...
2025-07-08T17:59:50Z
To appear at ICCV 2025. Christoph Reich and Aleksandar Jevti\'c - both authors contributed equally. Code: https://github.com/tum-vision/scenedino Project page: https://visinf.github.io/scenedino
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2,507.06448
Perception-Aware Policy Optimization for Multimodal Reasoning
['Zhenhailong Wang', 'Xuehang Guo', 'Sofia Stoica', 'Haiyang Xu', 'Hongru Wang', 'Hyeonjeong Ha', 'Xiusi Chen', 'Yangyi Chen', 'Ming Yan', 'Fei Huang', 'Heng Ji']
['cs.CL']
Reinforcement Learning with Verifiable Rewards (RLVR) has proven to be a highly effective strategy for endowing Large Language Models (LLMs) with robust multi-step reasoning abilities. However, its design and optimizations remain tailored to purely textual domains, resulting in suboptimal performance when applied to mu...
2025-07-08T23:22:34Z
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2,507.06607
Decoder-Hybrid-Decoder Architecture for Efficient Reasoning with Long Generation
['Liliang Ren', 'Congcong Chen', 'Haoran Xu', 'Young Jin Kim', 'Adam Atkinson', 'Zheng Zhan', 'Jiankai Sun', 'Baolin Peng', 'Liyuan Liu', 'Shuohang Wang', 'Hao Cheng', 'Jianfeng Gao', 'Weizhu Chen', 'Yelong Shen']
['cs.CL', 'cs.LG']
Recent advances in language modeling have demonstrated the effectiveness of State Space Models (SSMs) for efficient sequence modeling. While hybrid architectures such as Samba and the decoder-decoder architecture, YOCO, have shown promising performance gains over Transformers, prior works have not investigated the effi...
2025-07-09T07:27:00Z
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2,507.07104
Vision-Language-Vision Auto-Encoder: Scalable Knowledge Distillation from Diffusion Models
['Tiezheng Zhang', 'Yitong Li', 'Yu-cheng Chou', 'Jieneng Chen', 'Alan Yuille', 'Chen Wei', 'Junfei Xiao']
['cs.CV']
Building state-of-the-art Vision-Language Models (VLMs) with strong captioning capabilities typically necessitates training on billions of high-quality image-text pairs, requiring millions of GPU hours. This paper introduces the Vision-Language-Vision (VLV) auto-encoder framework, which strategically leverages key pret...
2025-07-09T17:59:04Z
Project Page: https://lambert-x.github.io/Vision-Language-Vision/
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2,507.07129
Growing Transformers: Modular Composition and Layer-wise Expansion on a Frozen Substrate
['A. Bochkov']
['cs.LG', 'cs.CL']
The prevailing paradigm for scaling large language models (LLMs) involves monolithic, end-to-end training, a resource-intensive process that lacks flexibility. This paper explores an alternative, constructive approach to model development, built upon the foundation of non-trainable, deterministic input embeddings. In p...
2025-07-08T20:01:15Z
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2,507.07186
Planted in Pretraining, Swayed by Finetuning: A Case Study on the Origins of Cognitive Biases in LLMs
['Itay Itzhak', 'Yonatan Belinkov', 'Gabriel Stanovsky']
['cs.CL', 'cs.AI', 'cs.LG']
Large language models (LLMs) exhibit cognitive biases -- systematic tendencies of irrational decision-making, similar to those seen in humans. Prior work has found that these biases vary across models and can be amplified by instruction tuning. However, it remains unclear if these differences in biases stem from pretra...
2025-07-09T18:01:14Z
CoLM 2025
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2,507.0723
Colors See Colors Ignore: Clothes Changing ReID with Color Disentanglement
['Priyank Pathak', 'Yogesh S. Rawat']
['cs.CV']
Clothes-Changing Re-Identification (CC-ReID) aims to recognize individuals across different locations and times, irrespective of clothing. Existing methods often rely on additional models or annotations to learn robust, clothing-invariant features, making them resource-intensive. In contrast, we explore the use of colo...
2025-07-09T19:05:46Z
ICCV'25 paper
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2,507.07248
Medical Red Teaming Protocol of Language Models: On the Importance of User Perspectives in Healthcare Settings
['Jean-Philippe Corbeil', 'Minseon Kim', 'Alessandro Sordoni', 'Francois Beaulieu', 'Paul Vozila']
['cs.CL']
As the performance of large language models (LLMs) continues to advance, their adoption is expanding across a wide range of domains, including the medical field. The integration of LLMs into medical applications raises critical safety concerns, particularly due to their use by users with diverse roles, e.g. patients an...
2025-07-09T19:38:58Z
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2,507.07439
Towards Interpretable Time Series Foundation Models
['Matthieu Boileau', 'Philippe Helluy', 'Jeremy Pawlus', 'Svitlana Vyetrenko']
['cs.CL', 'cs.AI']
In this paper, we investigate the distillation of time series reasoning capabilities into small, instruction-tuned language models as a step toward building interpretable time series foundation models. Leveraging a synthetic dataset of mean-reverting time series with systematically varied trends and noise levels, we ge...
2025-07-10T05:29:34Z
International Conference on Machine Leaning (ICML) 2025 Workshop on Foundation Models for Structured Data
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2,507.07562
The Synergy Dilemma of Long-CoT SFT and RL: Investigating Post-Training Techniques for Reasoning VLMs
['Jierun Chen', 'Tiezheng Yu', 'Haoli Bai', 'Lewei Yao', 'Jiannan Wu', 'Kaican Li', 'Fei Mi', 'Chaofan Tao', 'Lei Zhu', 'Manyi Zhang', 'Xiaohui Li', 'Lu Hou', 'Lifeng Shang', 'Qun Liu']
['cs.CL']
Large vision-language models (VLMs) increasingly adopt post-training techniques such as long chain-of-thought (CoT) supervised fine-tuning (SFT) and reinforcement learning (RL) to elicit sophisticated reasoning. While these methods exhibit synergy in language-only models, their joint effectiveness in VLMs remains uncer...
2025-07-10T09:05:49Z
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2,507.07831
Rethinking Query-based Transformer for Continual Image Segmentation
['Yuchen Zhu', 'Cheng Shi', 'Dingyou Wang', 'Jiajin Tang', 'Zhengxuan Wei', 'Yu Wu', 'Guanbin Li', 'Sibei Yang']
['cs.CV']
Class-incremental/Continual image segmentation (CIS) aims to train an image segmenter in stages, where the set of available categories differs at each stage. To leverage the built-in objectness of query-based transformers, which mitigates catastrophic forgetting of mask proposals, current methods often decouple mask ge...
2025-07-10T15:03:10Z
This work is accepted by CVPR 2025
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2,507.07999
Traceable Evidence Enhanced Visual Grounded Reasoning: Evaluation and Methodology
['Haochen Wang', 'Xiangtai Li', 'Zilong Huang', 'Anran Wang', 'Jiacong Wang', 'Tao Zhang', 'Jiani Zheng', 'Sule Bai', 'Zijian Kang', 'Jiashi Feng', 'Zhuochen Wang', 'Zhaoxiang Zhang']
['cs.CV', 'cs.AI', 'cs.CL']
Models like OpenAI-o3 pioneer visual grounded reasoning by dynamically referencing visual regions, just like human "thinking with images". However, no benchmark exists to evaluate these capabilities holistically. To bridge this gap, we propose TreeBench (Traceable Evidence Evaluation Benchmark), a diagnostic benchmark ...
2025-07-10T17:59:58Z
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