arxiv_id float64 1.5k 2.51k | title stringlengths 9 178 ⌀ | authors stringlengths 2 22.8k | categories stringlengths 4 146 | summary stringlengths 103 1.92k ⌀ | published stringdate 2015-02-06 10:44:00 2025-07-10 17:59:58 ⌀ | comments stringlengths 2 417 ⌀ | journal_ref stringclasses 321
values | doi stringclasses 398
values | ss_title stringlengths 8 159 ⌀ | ss_authors stringlengths 11 8.38k ⌀ | ss_year float64 2.02k 2.03k ⌀ | ss_venue stringclasses 281
values | ss_citationCount float64 0 134k ⌀ | ss_referenceCount float64 0 429 ⌀ | ss_fieldsOfStudy stringclasses 47
values |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2,506.13796 | ClimateChat: Designing Data and Methods for Instruction Tuning LLMs to
Answer Climate Change Queries | ['Zhou Chen', 'Xiao Wang', 'Yuanhong Liao', 'Ming Lin', 'Yuqi Bai'] | ['cs.CL', 'cs.AI'] | As the issue of global climate change becomes increasingly severe, the demand
for research in climate science continues to grow. Natural language processing
technologies, represented by Large Language Models (LLMs), have been widely
applied to climate change-specific research, providing essential information
support fo... | 2025-06-12T08:43:38Z | ICLR 2025 camera ready, 13 pages, 4 figures, 4 tables | null | null | ClimateChat: Designing Data and Methods for Instruction Tuning LLMs to Answer Climate Change Queries | ['Zhou Chen', 'Xiao Wang', 'Yuanhong Liao', 'Ming Lin', 'Yuqi Bai'] | 2,025 | arXiv.org | 1 | 25 | ['Computer Science'] |
2,506.14111 | Essential-Web v1.0: 24T tokens of organized web data | ['Essential AI', ':', 'Andrew Hojel', 'Michael Pust', 'Tim Romanski', 'Yash Vanjani', 'Ritvik Kapila', 'Mohit Parmar', 'Adarsh Chaluvaraju', 'Alok Tripathy', 'Anil Thomas', 'Ashish Tanwer', 'Darsh J Shah', 'Ishaan Shah', 'Karl Stratos', 'Khoi Nguyen', 'Kurt Smith', 'Michael Callahan', 'Peter Rushton', 'Philip Monk', 'P... | ['cs.CL', 'cs.AI', 'cs.LG'] | Data plays the most prominent role in how language models acquire skills and
knowledge. The lack of massive, well-organized pre-training datasets results in
costly and inaccessible data pipelines. We present Essential-Web v1.0, a
24-trillion-token dataset in which every document is annotated with a
twelve-category taxo... | 2025-06-17T02:03:36Z | include MegaMath-Web-Pro | null | null | null | null | null | null | null | null | null |
2,506.14175 | GRAM: A Generative Foundation Reward Model for Reward Generalization | ['Chenglong Wang', 'Yang Gan', 'Yifu Huo', 'Yongyu Mu', 'Qiaozhi He', 'Murun Yang', 'Bei Li', 'Tong Xiao', 'Chunliang Zhang', 'Tongran Liu', 'Jingbo Zhu'] | ['cs.CL', 'cs.AI'] | In aligning large language models (LLMs), reward models have played an
important role, but are standardly trained as discriminative models and rely
only on labeled human preference data. In this paper, we explore methods that
train reward models using both unlabeled and labeled data. Building on the
generative models i... | 2025-06-17T04:34:27Z | Accepted by ICML 2025 | null | null | GRAM: A Generative Foundation Reward Model for Reward Generalization | ['Chenglong Wang', 'Yang Gan', 'Yifu Huo', 'Yongyu Mu', 'Qiaozhi He', 'Murun Yang', 'Bei Li', 'Tong Xiao', 'Chunliang Zhang', 'Tongran Liu', 'Jingbo Zhu'] | 2,025 | arXiv.org | 0 | 53 | ['Computer Science'] |
2,506.14512 | SIRI-Bench: Challenging VLMs' Spatial Intelligence through Complex
Reasoning Tasks | ['Zijian Song', 'Xiaoxin Lin', 'Qiuming Huang', 'Guangrun Wang', 'Liang Lin'] | ['cs.CV'] | Large Language Models (LLMs) are experiencing rapid advancements in complex
reasoning, exhibiting remarkable generalization in mathematics and programming.
In contrast, while spatial intelligence is fundamental for Vision-Language
Models (VLMs) in real-world interaction, the systematic evaluation of their
complex reaso... | 2025-06-17T13:40:00Z | 16 pages, 9 figures | null | null | null | null | null | null | null | null | null |
2,506.14606 | Guaranteed Guess: A Language Modeling Approach for CISC-to-RISC
Transpilation with Testing Guarantees | ['Ahmed Heakl', 'Sarim Hashmi', 'Chaimaa Abi', 'Celine Lee', 'Abdulrahman Mahmoud'] | ['cs.CL', 'cs.AR', 'cs.LG', 'cs.PL', 'cs.SE'] | The hardware ecosystem is rapidly evolving, with increasing interest in
translating low-level programs across different instruction set architectures
(ISAs) in a quick, flexible, and correct way to enhance the portability and
longevity of existing code. A particularly challenging class of this
transpilation problem is ... | 2025-06-17T15:06:54Z | Project page: https://ahmedheakl.github.io/Guaranteed-Guess/ | null | null | Guaranteed Guess: A Language Modeling Approach for CISC-to-RISC Transpilation with Testing Guarantees | ['Ahmed Heakl', 'Sarim Hashmi', 'Chaimaa Abi', 'Celine Lee', 'Abdulrahman Mahmoud'] | 2,025 | arXiv.org | 0 | 56 | ['Computer Science'] |
2,506.14731 | Ring-lite: Scalable Reasoning via C3PO-Stabilized Reinforcement Learning
for LLMs | ['Ling Team', 'Bin Hu', 'Cai Chen', 'Deng Zhao', 'Ding Liu', 'Dingnan Jin', 'Feng Zhu', 'Hao Dai', 'Hongzhi Luan', 'Jia Guo', 'Jiaming Liu', 'Jiewei Wu', 'Jun Mei', 'Jun Zhou', 'Junbo Zhao', 'Junwu Xiong', 'Kaihong Zhang', 'Kuan Xu', 'Lei Liang', 'Liang Jiang', 'Liangcheng Fu', 'Longfei Zheng', 'Qiang Gao', 'Qing Cui',... | ['cs.CL', 'cs.AI'] | We present Ring-lite, a Mixture-of-Experts (MoE)-based large language model
optimized via reinforcement learning (RL) to achieve efficient and robust
reasoning capabilities. Built upon the publicly available Ling-lite model, a
16.8 billion parameter model with 2.75 billion activated parameters, our
approach matches the... | 2025-06-17T17:12:34Z | Technical Report | null | null | null | null | null | null | null | null | null |
2,506.14794 | Assembly of Experts: Linear-time construction of the Chimera LLM
variants with emergent and adaptable behaviors | ['Henrik Klagges', 'Robert Dahlke', 'Fabian Klemm', 'Benjamin Merkel', 'Daniel Klingmann', 'David A. Reiss', 'Dan Zecha'] | ['cs.LG', 'cs.AI', 'cs.CL'] | Requiring $10^{13}$-$10^{15}$ FLOPs to calculate one 8 bit weight in an LLM
during pretraining is extremely expensive and seems inefficient. To better
leverage the huge investments made into pretrained models, we develop the new
"Assembly-of-Experts" (AoE) construction method to create capable child
variants of existin... | 2025-05-31T18:23:19Z | null | null | null | Assembly of Experts: Linear-time construction of the Chimera LLM variants with emergent and adaptable behaviors | ['Henrik Klagges', 'Robert Dahlke', 'Fabian Klemm', 'Benjamin Merkel', 'Daniel Klingmann', 'David A. Reiss', 'Dan Zecha'] | 2,025 | arXiv.org | 0 | 41 | ['Computer Science'] |
2,506.14842 | PictSure: Pretraining Embeddings Matters for In-Context Learning Image
Classifiers | ['Lukas Schiesser', 'Cornelius Wolff', 'Sophie Haas', 'Simon Pukrop'] | ['cs.CV', 'cs.AI'] | Building image classification models remains cumbersome in data-scarce
domains, where collecting large labeled datasets is impractical. In-context
learning (ICL) has emerged as a promising paradigm for few-shot image
classification (FSIC), enabling models to generalize across domains without
gradient-based adaptation. ... | 2025-06-16T08:57:03Z | 15 pages, 10 figures | null | null | null | null | null | null | null | null | null |
2,506.14965 | Revisiting Reinforcement Learning for LLM Reasoning from A Cross-Domain
Perspective | ['Zhoujun Cheng', 'Shibo Hao', 'Tianyang Liu', 'Fan Zhou', 'Yutao Xie', 'Feng Yao', 'Yuexin Bian', 'Yonghao Zhuang', 'Nilabjo Dey', 'Yuheng Zha', 'Yi Gu', 'Kun Zhou', 'Yuqi Wang', 'Yuan Li', 'Richard Fan', 'Jianshu She', 'Chengqian Gao', 'Abulhair Saparov', 'Haonan Li', 'Taylor W. Killian', 'Mikhail Yurochkin', 'Zhengz... | ['cs.LG', 'cs.AI', 'cs.CL'] | Reinforcement learning (RL) has emerged as a promising approach to improve
large language model (LLM) reasoning, yet most open efforts focus narrowly on
math and code, limiting our understanding of its broader applicability to
general reasoning. A key challenge lies in the lack of reliable, scalable RL
reward signals a... | 2025-06-17T20:24:00Z | 38 pages, 9 figures. Under review | null | null | null | null | null | null | null | null | null |
2,506.15068 | Semantically-Aware Rewards for Open-Ended R1 Training in Free-Form
Generation | ['Zongxia Li', 'Yapei Chang', 'Yuhang Zhou', 'Xiyang Wu', 'Zichao Liang', 'Yoo Yeon Sung', 'Jordan Lee Boyd-Graber'] | ['cs.CL', 'cs.LG'] | Evaluating open-ended long-form generation is challenging because it is hard
to define what clearly separates good from bad outputs. Existing methods often
miss key aspects like coherence, style, or relevance, or are biased by
pretraining data, making open-ended long-form evaluation an underexplored
problem. To address... | 2025-06-18T02:16:53Z | null | null | null | null | null | null | null | null | null | null |
2,506.15154 | SonicVerse: Multi-Task Learning for Music Feature-Informed Captioning | ['Anuradha Chopra', 'Abhinaba Roy', 'Dorien Herremans'] | ['cs.SD', 'cs.AI', 'cs.CL', 'cs.MM', 'eess.AS', '68T10 (Primary), 68T50 (Secondary)', 'H.5.5; H.5.1; I.2.7'] | Detailed captions that accurately reflect the characteristics of a music
piece can enrich music databases and drive forward research in music AI. This
paper introduces a multi-task music captioning model, SonicVerse, that
integrates caption generation with auxiliary music feature detection tasks such
as key detection, ... | 2025-06-18T05:51:36Z | 14 pages, 2 figures, Accepted to AIMC 2025 | Proceedings of the 6th Conference on AI Music Creativity (AIMC
2025), Brussels, Belgium, September 10th - 12th, 2025 | null | SonicVerse: Multi-Task Learning for Music Feature-Informed Captioning | ['Anuradha Chopra', 'Abhinaba Roy', 'Dorien Herremans'] | 2,025 | arXiv.org | 0 | 30 | ['Computer Science', 'Engineering'] |
2,506.15266 | Thunder-DeID: Accurate and Efficient De-identification Framework for
Korean Court Judgments | ['Sungeun Hahm', 'Heejin Kim', 'Gyuseong Lee', 'Hyunji Park', 'Jaejin Lee'] | ['cs.CL'] | To ensure a balance between open access to justice and personal data
protection, the South Korean judiciary mandates the de-identification of court
judgments before they can be publicly disclosed. However, the current
de-identification process is inadequate for handling court judgments at scale
while adhering to strict... | 2025-06-18T08:41:28Z | null | null | null | null | null | null | null | null | null | null |
2,506.15442 | Hunyuan3D 2.1: From Images to High-Fidelity 3D Assets with
Production-Ready PBR Material | ['Team Hunyuan3D', 'Shuhui Yang', 'Mingxin Yang', 'Yifei Feng', 'Xin Huang', 'Sheng Zhang', 'Zebin He', 'Di Luo', 'Haolin Liu', 'Yunfei Zhao', 'Qingxiang Lin', 'Zeqiang Lai', 'Xianghui Yang', 'Huiwen Shi', 'Zibo Zhao', 'Bowen Zhang', 'Hongyu Yan', 'Lifu Wang', 'Sicong Liu', 'Jihong Zhang', 'Meng Chen', 'Liang Dong', 'Y... | ['cs.CV', 'cs.AI'] | 3D AI-generated content (AIGC) is a passionate field that has significantly
accelerated the creation of 3D models in gaming, film, and design. Despite the
development of several groundbreaking models that have revolutionized 3D
generation, the field remains largely accessible only to researchers,
developers, and design... | 2025-06-18T13:14:46Z | Github link: https://github.com/Tencent-Hunyuan/Hunyuan3D-2.1 | null | null | null | null | null | null | null | null | null |
2,506.15498 | SPARE: Single-Pass Annotation with Reference-Guided Evaluation for
Automatic Process Supervision and Reward Modelling | ['Md Imbesat Hassan Rizvi', 'Xiaodan Zhu', 'Iryna Gurevych'] | ['cs.CL', 'cs.AI', 'cs.LG'] | Process or step-wise supervision has played a crucial role in advancing
complex multi-step reasoning capabilities of Large Language Models (LLMs).
However, efficient, high-quality automated process annotation remains a
significant challenge. To address this, we introduce Single-Pass Annotation
with Reference-Guided Eva... | 2025-06-18T14:37:59Z | 8 pages main content, 4 figures, 4 tables | null | null | null | null | null | null | null | null | null |
2,506.15564 | Show-o2: Improved Native Unified Multimodal Models | ['Jinheng Xie', 'Zhenheng Yang', 'Mike Zheng Shou'] | ['cs.CV'] | This paper presents improved native unified multimodal models, \emph{i.e.,}
Show-o2, that leverage autoregressive modeling and flow matching. Built upon a
3D causal variational autoencoder space, unified visual representations are
constructed through a dual-path of spatial (-temporal) fusion, enabling
scalability acros... | 2025-06-18T15:39:15Z | Technical report. (v2: update references and tables) | null | null | Show-o2: Improved Native Unified Multimodal Models | ['Jinheng Xie', 'Zhenheng Yang', 'Mike Zheng Shou'] | 2,025 | arXiv.org | 0 | 120 | ['Computer Science'] |
2,506.15635 | FindingDory: A Benchmark to Evaluate Memory in Embodied Agents | ['Karmesh Yadav', 'Yusuf Ali', 'Gunshi Gupta', 'Yarin Gal', 'Zsolt Kira'] | ['cs.CV', 'cs.RO'] | Large vision-language models have recently demonstrated impressive
performance in planning and control tasks, driving interest in their
application to real-world robotics. However, deploying these models for
reasoning in embodied contexts is limited by their ability to incorporate
long-term experience collected across ... | 2025-06-18T17:06:28Z | Our dataset and code will be made available at:
https://findingdory-benchmark.github.io/ | null | null | null | null | null | null | null | null | null |
2,506.15721 | Bohdi: Heterogeneous LLM Fusion with Automatic Data Exploration | ['Junqi Gao', 'Zhichang Guo', 'Dazhi Zhang', 'Dong Li', 'Runze Liu', 'Pengfei Li', 'Kai Tian', 'Biqing Qi'] | ['cs.LG'] | Heterogeneous Large Language Model (LLM) fusion integrates the strengths of
multiple source LLMs with different architectures into a target LLM with low
computational overhead. While promising, existing methods suffer from two major
limitations: 1) reliance on real data from limited domain for knowledge fusion,
prevent... | 2025-06-04T17:01:38Z | null | null | null | Bohdi: Heterogeneous LLM Fusion with Automatic Data Exploration | ['Junqi Gao', 'Zhichang Guo', 'Dazhi Zhang', 'Dong Li', 'Runze Liu', 'Pengfei Li', 'Kai Tian', 'Biqing Qi'] | 2,025 | arXiv.org | 0 | 39 | ['Computer Science'] |
2,506.15742 | FLUX.1 Kontext: Flow Matching for In-Context Image Generation and
Editing in Latent Space | ['Black Forest Labs', 'Stephen Batifol', 'Andreas Blattmann', 'Frederic Boesel', 'Saksham Consul', 'Cyril Diagne', 'Tim Dockhorn', 'Jack English', 'Zion English', 'Patrick Esser', 'Sumith Kulal', 'Kyle Lacey', 'Yam Levi', 'Cheng Li', 'Dominik Lorenz', 'Jonas Müller', 'Dustin Podell', 'Robin Rombach', 'Harry Saini', 'Ax... | ['cs.GR'] | We present evaluation results for FLUX.1 Kontext, a generative flow matching
model that unifies image generation and editing. The model generates novel
output views by incorporating semantic context from text and image inputs.
Using a simple sequence concatenation approach, FLUX.1 Kontext handles both
local editing and... | 2025-06-17T20:18:23Z | null | null | null | null | null | null | null | null | null | null |
2,506.16073 | TD3Net: A Temporal Densely Connected Multi-Dilated Convolutional Network
for Lipreading | ['Byung Hoon Lee', 'Wooseok Shin', 'Sung Won Han'] | ['cs.CV', 'I.4.8; I.5.4; I.2.10'] | The word-level lipreading approach typically employs a two-stage framework
with separate frontend and backend architectures to model dynamic lip
movements. Each component has been extensively studied, and in the backend
architecture, temporal convolutional networks (TCNs) have been widely adopted
in state-of-the-art me... | 2025-06-19T06:55:03Z | 15 pages, 6 figures | null | null | TD3Net: A Temporal Densely Connected Multi-Dilated Convolutional Network for Lipreading | ['B. Lee', 'Wooseok Shin', 'Sung Won Han'] | 2,025 | arXiv.org | 0 | 54 | ['Computer Science'] |
2,506.16141 | GRPO-CARE: Consistency-Aware Reinforcement Learning for Multimodal
Reasoning | ['Yi Chen', 'Yuying Ge', 'Rui Wang', 'Yixiao Ge', 'Junhao Cheng', 'Ying Shan', 'Xihui Liu'] | ['cs.CV', 'cs.AI', 'cs.CL', 'cs.LG'] | Recent reinforcement learning approaches, such as outcome-supervised GRPO,
have advanced Chain-of-Thought reasoning in large language models (LLMs), yet
their adaptation to multimodal LLMs (MLLMs) is unexplored. To address the lack
of rigorous evaluation for MLLM post-training methods, we introduce
SEED-Bench-R1, a ben... | 2025-06-19T08:49:13Z | Code released at: https://github.com/TencentARC/GRPO-CARE | null | null | GRPO-CARE: Consistency-Aware Reinforcement Learning for Multimodal Reasoning | ['Yi Chen', 'Yuying Ge', 'Rui Wang', 'Yixiao Ge', 'Jun Cheng', 'Ying Shan', 'Xihui Liu'] | 2,025 | arXiv.org | 0 | 45 | ['Computer Science'] |
2,506.16233 | Can AI Dream of Unseen Galaxies? Conditional Diffusion Model for Galaxy
Morphology Augmentation | ['Chenrui Ma', 'Zechang Sun', 'Tao Jing', 'Zheng Cai', 'Yuan-Sen Ting', 'Song Huang', 'Mingyu Li'] | ['astro-ph.GA', 'cs.LG'] | Observational astronomy relies on visual feature identification to detect
critical astrophysical phenomena. While machine learning (ML) increasingly
automates this process, models often struggle with generalization in
large-scale surveys due to the limited representativeness of labeled datasets
-- whether from simulati... | 2025-06-19T11:44:09Z | We have submitted to AAS journals. See another independent work for
further reference -- Category-based Galaxy Image Generation via Diffusion
Models (Fan, Tang et al.). Comments are welcome | null | null | Can AI Dream of Unseen Galaxies? Conditional Diffusion Model for Galaxy Morphology Augmentation | ['Chenrui Ma', 'Zechang Sun', 'Tao Jing', 'Zheng Cai', 'Yuan-Sen Ting', 'Song Huang', 'Mingyu Li'] | 2,025 | arXiv.org | 0 | 7 | ['Physics', 'Computer Science'] |
2,506.1631 | Optimizing Multilingual Text-To-Speech with Accents & Emotions | ['Pranav Pawar', 'Akshansh Dwivedi', 'Jenish Boricha', 'Himanshu Gohil', 'Aditya Dubey'] | ['cs.LG', 'cs.HC', 'cs.SD', 'eess.AS'] | State-of-the-art text-to-speech (TTS) systems realize high naturalness in
monolingual environments, synthesizing speech with correct multilingual accents
(especially for Indic languages) and context-relevant emotions still poses
difficulty owing to cultural nuance discrepancies in current frameworks. This
paper introdu... | 2025-06-19T13:35:05Z | 12 pages, 8 figures | null | null | null | null | null | null | null | null | null |
2,506.16322 | PL-Guard: Benchmarking Language Model Safety for Polish | ['Aleksandra Krasnodębska', 'Karolina Seweryn', 'Szymon Łukasik', 'Wojciech Kusa'] | ['cs.CL', 'I.2.7'] | Despite increasing efforts to ensure the safety of large language models
(LLMs), most existing safety assessments and moderation tools remain heavily
biased toward English and other high-resource languages, leaving majority of
global languages underexamined. To address this gap, we introduce a manually
annotated benchm... | 2025-06-19T13:56:41Z | Accepted to the 10th Workshop on Slavic Natural Language Processing | null | null | null | null | null | null | null | null | null |
2,506.165 | SparseLoRA: Accelerating LLM Fine-Tuning with Contextual Sparsity | ['Samir Khaki', 'Xiuyu Li', 'Junxian Guo', 'Ligeng Zhu', 'Chenfeng Xu', 'Konstantinos N. Plataniotis', 'Amir Yazdanbakhsh', 'Kurt Keutzer', 'Song Han', 'Zhijian Liu'] | ['cs.LG'] | Fine-tuning LLMs is both computationally and memory-intensive. While
parameter-efficient fine-tuning methods, such as QLoRA and DoRA, reduce the
number of trainable parameters and lower memory usage, they do not decrease
computational cost. In some cases, they may even slow down fine-tuning. In this
paper, we introduce... | 2025-06-19T17:53:34Z | ICML 2025. The first three authors contributed equally to this work.
Project page: https://z-lab.ai/projects/sparselora | null | null | null | null | null | null | null | null | null |
2,506.16655 | Arch-Router: Aligning LLM Routing with Human Preferences | ['Co Tran', 'Salman Paracha', 'Adil Hafeez', 'Shuguang Chen'] | ['cs.CL'] | With the rapid proliferation of large language models (LLMs) -- each
optimized for different strengths, style, or latency/cost profile -- routing
has become an essential technique to operationalize the use of different
models. However, existing LLM routing approaches are limited in two key ways:
they evaluate performan... | 2025-06-19T23:57:41Z | null | null | null | null | null | null | null | null | null | null |
2,506.16962 | Enhancing Step-by-Step and Verifiable Medical Reasoning in MLLMs | ['Haoran Sun', 'Yankai Jiang', 'Wenjie Lou', 'Yujie Zhang', 'Wenjie Li', 'Lilong Wang', 'Mianxin Liu', 'Lei Liu', 'Xiaosong Wang'] | ['cs.CV', 'cs.AI', 'cs.CL'] | Multimodal large language models (MLLMs) have begun to demonstrate robust
reasoning capabilities on general tasks, yet their application in the medical
domain remains in its early stages. Constructing chain-of-thought (CoT)
training data is essential for bolstering the reasoning abilities of medical
MLLMs. However, exi... | 2025-06-20T12:51:19Z | null | null | null | null | null | null | null | null | null | null |
2,506.1708 | Tower+: Bridging Generality and Translation Specialization in
Multilingual LLMs | ['Ricardo Rei', 'Nuno M. Guerreiro', 'José Pombal', 'João Alves', 'Pedro Teixeirinha', 'Amin Farajian', 'André F. T. Martins'] | ['cs.CL', 'cs.AI'] | Fine-tuning pretrained LLMs has been shown to be an effective strategy for
reaching state-of-the-art performance on specific tasks like machine
translation. However, this process of adaptation often implies sacrificing
general-purpose capabilities, such as conversational reasoning and
instruction-following, hampering t... | 2025-06-20T15:30:06Z | null | null | null | Tower+: Bridging Generality and Translation Specialization in Multilingual LLMs | ['Ricardo Rei', 'Nuno M. Guerreiro', 'José P. Pombal', 'João Alves', 'Pedro Teixeirinha', 'Amin Farajian', "Andr'e F. T. Martins"] | 2,025 | arXiv.org | 0 | 37 | ['Computer Science'] |
2,506.1709 | Better Language Model Inversion by Compactly Representing Next-Token
Distributions | ['Murtaza Nazir', 'Matthew Finlayson', 'John X. Morris', 'Xiang Ren', 'Swabha Swayamdipta'] | ['cs.CL'] | Language model inversion seeks to recover hidden prompts using only language
model outputs. This capability has implications for security and accountability
in language model deployments, such as leaking private information from an
API-protected language model's system message. We propose a new method --
prompt inversi... | 2025-06-20T15:53:51Z | null | null | null | null | null | null | null | null | null | null |
2,506.17206 | DreamCube: 3D Panorama Generation via Multi-plane Synchronization | ['Yukun Huang', 'Yanning Zhou', 'Jianan Wang', 'Kaiyi Huang', 'Xihui Liu'] | ['cs.GR', 'cs.CV', 'cs.LG'] | 3D panorama synthesis is a promising yet challenging task that demands
high-quality and diverse visual appearance and geometry of the generated
omnidirectional content. Existing methods leverage rich image priors from
pre-trained 2D foundation models to circumvent the scarcity of 3D panoramic
data, but the incompatibil... | 2025-06-20T17:55:06Z | Project page: https://yukun-huang.github.io/DreamCube/ | null | null | null | null | null | null | null | null | null |
2,506.17238 | Training a Scientific Reasoning Model for Chemistry | ['Siddharth M. Narayanan', 'James D. Braza', 'Ryan-Rhys Griffiths', 'Albert Bou', 'Geemi Wellawatte', 'Mayk Caldas Ramos', 'Ludovico Mitchener', 'Samuel G. Rodriques', 'Andrew D. White'] | ['cs.LG'] | Reasoning models are large language models that emit a long chain-of-thought
before answering, providing both higher accuracy and explicit reasoning for
their response. A major question has been whether language model reasoning
generalizes beyond mathematics, programming, and logic, where most previous
work has focused... | 2025-06-04T17:57:18Z | null | null | null | null | null | null | null | null | null | null |
2,506.17497 | From Generality to Mastery: Composer-Style Symbolic Music Generation via
Large-Scale Pre-training | ['Mingyang Yao', 'Ke Chen'] | ['cs.SD', 'cs.AI', 'cs.LG', 'eess.AS'] | Despite progress in controllable symbolic music generation, data scarcity
remains a challenge for certain control modalities. Composer-style music
generation is a prime example, as only a few pieces per composer are available,
limiting the modeling of both styles and fundamental music elements (e.g.,
melody, chord, rhy... | 2025-06-20T22:20:59Z | Proceedings of the 6th Conference on AI Music Creativity, AIMC 2025 | null | null | null | null | null | null | null | null | null |
2,506.17561 | VLA-OS: Structuring and Dissecting Planning Representations and
Paradigms in Vision-Language-Action Models | ['Chongkai Gao', 'Zixuan Liu', 'Zhenghao Chi', 'Junshan Huang', 'Xin Fei', 'Yiwen Hou', 'Yuxuan Zhang', 'Yudi Lin', 'Zhirui Fang', 'Zeyu Jiang', 'Lin Shao'] | ['cs.CV', 'cs.AI', 'cs.RO'] | Recent studies on Vision-Language-Action (VLA) models have shifted from the
end-to-end action-generation paradigm toward a pipeline involving task planning
followed by action generation, demonstrating improved performance on various
complex, long-horizon manipulation tasks. However, existing approaches vary
significant... | 2025-06-21T03:07:48Z | null | null | null | null | null | null | null | null | null | null |
2,506.17612 | JarvisArt: Liberating Human Artistic Creativity via an Intelligent Photo
Retouching Agent | ['Yunlong Lin', 'Zixu Lin', 'Kunjie Lin', 'Jinbin Bai', 'Panwang Pan', 'Chenxin Li', 'Haoyu Chen', 'Zhongdao Wang', 'Xinghao Ding', 'Wenbo Li', 'Shuicheng Yan'] | ['cs.CV'] | Photo retouching has become integral to contemporary visual storytelling,
enabling users to capture aesthetics and express creativity. While professional
tools such as Adobe Lightroom offer powerful capabilities, they demand
substantial expertise and manual effort. In contrast, existing AI-based
solutions provide autom... | 2025-06-21T06:36:00Z | 40 pages, 26 figures | null | null | null | null | null | null | null | null | null |
2,506.17671 | TPTT: Transforming Pretrained Transformer into Titans | ['Fabien Furfaro'] | ['cs.CL', 'cs.AI', 'cs.LG'] | Recent advances in large language models (LLMs) have led to remarkable
progress in natural language processing, but their computational and memory
demands remain a significant challenge, particularly for long-context
inference. We introduce TPTT (Transforming Pretrained Transformer into Titans),
a novel framework for e... | 2025-06-21T10:06:07Z | 6 pages, 1 figure | null | null | null | null | null | null | null | null | null |
2,506.17818 | CultureMERT: Continual Pre-Training for Cross-Cultural Music
Representation Learning | ['Angelos-Nikolaos Kanatas', 'Charilaos Papaioannou', 'Alexandros Potamianos'] | ['cs.SD', 'cs.AI', 'cs.LG', 'eess.AS'] | Recent advances in music foundation models have improved audio representation
learning, yet their effectiveness across diverse musical traditions remains
limited. We introduce CultureMERT-95M, a multi-culturally adapted foundation
model developed to enhance cross-cultural music representation learning and
understanding... | 2025-06-21T21:16:39Z | 10 pages, 4 figures, accepted to the 26th International Society for
Music Information Retrieval conference (ISMIR 2025), to be held in Daejeon,
South Korea | null | null | null | null | null | null | null | null | null |
2,506.18035 | Splitformer: An improved early-exit architecture for automatic speech
recognition on edge devices | ['Maxence Lasbordes', 'Daniele Falavigna', 'Alessio Brutti'] | ['cs.CL', 'cs.SD', 'eess.AS', '68T50 (Primary)', 'I.2.7; I.5.4'] | The ability to dynamically adjust the computational load of neural models
during inference in a resource aware manner is crucial for on-device processing
scenarios, characterised by limited and time-varying computational resources.
Early-exit architectures represent an elegant and effective solution, since
they can pro... | 2025-06-22T13:34:18Z | 5 pages, 3 Postscript figures | null | null | null | null | null | null | null | null | null |
2,506.18088 | RoboTwin 2.0: A Scalable Data Generator and Benchmark with Strong Domain
Randomization for Robust Bimanual Robotic Manipulation | ['Tianxing Chen', 'Zanxin Chen', 'Baijun Chen', 'Zijian Cai', 'Yibin Liu', 'Qiwei Liang', 'Zixuan Li', 'Xianliang Lin', 'Yiheng Ge', 'Zhenyu Gu', 'Weiliang Deng', 'Yubin Guo', 'Tian Nian', 'Xuanbing Xie', 'Qiangyu Chen', 'Kailun Su', 'Tianling Xu', 'Guodong Liu', 'Mengkang Hu', 'Huan-ang Gao', 'Kaixuan Wang', 'Zhixuan ... | ['cs.RO', 'cs.AI', 'cs.CL', 'cs.CV', 'cs.MA'] | Simulation-based data synthesis has emerged as a powerful paradigm for
enhancing real-world robotic manipulation. However, existing synthetic datasets
remain insufficient for robust bimanual manipulation due to two challenges: (1)
the lack of an efficient, scalable data generation method for novel tasks, and
(2) oversi... | 2025-06-22T16:26:53Z | Project Page: https://robotwin-platform.github.io/ | null | null | null | null | null | null | null | null | null |
2,506.18095 | ShareGPT-4o-Image: Aligning Multimodal Models with GPT-4o-Level Image
Generation | ['Junying Chen', 'Zhenyang Cai', 'Pengcheng Chen', 'Shunian Chen', 'Ke Ji', 'Xidong Wang', 'Yunjin Yang', 'Benyou Wang'] | ['cs.CV', 'cs.AI', 'cs.LG'] | Recent advances in multimodal generative models have unlocked photorealistic,
instruction-aligned image generation, yet leading systems like GPT-4o-Image
remain proprietary and inaccessible. To democratize these capabilities, we
present ShareGPT-4o-Image, the first dataset comprising 45K text-to-image and
46K text-and-... | 2025-06-22T16:51:09Z | null | null | null | null | null | null | null | null | null | null |
2,506.18203 | Shrinking the Generation-Verification Gap with Weak Verifiers | ['Jon Saad-Falcon', 'E. Kelly Buchanan', 'Mayee F. Chen', 'Tzu-Heng Huang', 'Brendan McLaughlin', 'Tanvir Bhathal', 'Shang Zhu', 'Ben Athiwaratkun', 'Frederic Sala', 'Scott Linderman', 'Azalia Mirhoseini', 'Christopher Ré'] | ['cs.CR', 'cs.CL'] | Verifiers can improve language model capabilities by scoring and ranking
responses from generated candidates. Currently, high-quality verifiers are
either unscalable (e.g., humans) or limited in utility (e.g., tools like Lean).
While LM judges and reward models have become broadly useful as general-purpose
verifiers, a... | 2025-06-22T23:38:15Z | null | null | null | null | null | null | null | null | null | null |
2,506.18245 | Smart-LLaMA-DPO: Reinforced Large Language Model for Explainable Smart
Contract Vulnerability Detection | ['Lei Yu', 'Zhirong Huang', 'Hang Yuan', 'Shiqi Cheng', 'Li Yang', 'Fengjun Zhang', 'Chenjie Shen', 'Jiajia Ma', 'Jingyuan Zhang', 'Junyi Lu', 'Chun Zuo'] | ['cs.CR', 'cs.AI', 'cs.SE'] | Smart contract vulnerability detection remains a major challenge in
blockchain security. Existing vulnerability detection methods face two main
issues: (1) Existing datasets lack comprehensive coverage and high-quality
explanations for preference learning. (2) Large language models (LLMs) often
struggle with accurately... | 2025-06-23T02:24:07Z | Accepted to ISSTA 2025 | null | null | null | null | null | null | null | null | null |
2,506.18254 | RLPR: Extrapolating RLVR to General Domains without Verifiers | ['Tianyu Yu', 'Bo Ji', 'Shouli Wang', 'Shu Yao', 'Zefan Wang', 'Ganqu Cui', 'Lifan Yuan', 'Ning Ding', 'Yuan Yao', 'Zhiyuan Liu', 'Maosong Sun', 'Tat-Seng Chua'] | ['cs.LG', 'cs.AI', 'cs.CL'] | Reinforcement Learning with Verifiable Rewards (RLVR) demonstrates promising
potential in advancing the reasoning capabilities of LLMs. However, its success
remains largely confined to mathematical and code domains. This primary
limitation stems from the heavy reliance on domain-specific verifiers, which
results in pro... | 2025-06-23T02:56:36Z | Project Website: https://github.com/openbmb/RLPR | null | null | null | null | null | null | null | null | null |
2,506.1833 | Confucius3-Math: A Lightweight High-Performance Reasoning LLM for
Chinese K-12 Mathematics Learning | ['Lixin Wu', 'Na Cai', 'Qiao Cheng', 'Jiachen Wang', 'Yitao Duan'] | ['cs.LG', 'cs.AI', 'cs.CL'] | We introduce Confucius3-Math, an open-source large language model with 14B
parameters that (1) runs efficiently on a single consumer-grade GPU; (2)
achieves SOTA performances on a range of mathematical reasoning tasks,
outperforming many models with significantly larger sizes. In particular, as
part of our mission to e... | 2025-06-23T06:23:53Z | null | null | null | null | null | null | null | null | null | null |
2,506.18349 | SlimMoE: Structured Compression of Large MoE Models via Expert Slimming
and Distillation | ['Zichong Li', 'Chen Liang', 'Zixuan Zhang', 'Ilgee Hong', 'Young Jin Kim', 'Weizhu Chen', 'Tuo Zhao'] | ['cs.LG', 'cs.CL'] | The Mixture of Experts (MoE) architecture has emerged as a powerful paradigm
for scaling large language models (LLMs) while maintaining inference
efficiency. However, their enormous memory requirements make them prohibitively
expensive to fine-tune or deploy in resource-constrained environments. To
address this challen... | 2025-06-23T07:15:59Z | null | null | null | null | null | null | null | null | null | null |
2,506.18582 | Parallel Continuous Chain-of-Thought with Jacobi Iteration | ['Haoyi Wu', 'Zhihao Teng', 'Kewei Tu'] | ['cs.CL'] | Continuous chain-of-thought has been shown to be effective in saving
reasoning tokens for large language models. By reasoning with continuous latent
thought tokens, continuous CoT is able to perform implicit reasoning in a
compact manner. However, the sequential dependencies between latent thought
tokens spoil parallel... | 2025-06-23T12:35:41Z | under review | null | null | null | null | null | null | null | null | null |
2,506.18623 | Efficient and Generalizable Speaker Diarization via Structured Pruning
of Self-Supervised Models | ['Jiangyu Han', 'Petr Pálka', 'Marc Delcroix', 'Federico Landini', 'Johan Rohdin', 'Jan Cernocký', 'Lukáš Burget'] | ['eess.AS'] | Self-supervised learning (SSL) models such as WavLM have brought substantial
improvements to speaker diarization by providing rich contextual
representations. However, the high computational and memory costs of these
models hinder their deployment in real-time and resource-constrained scenarios.
In this work, we presen... | 2025-06-23T13:29:51Z | 11 pages, 6 figures | null | null | null | null | null | null | null | null | null |
2,506.18701 | Matrix-Game: Interactive World Foundation Model | ['Yifan Zhang', 'Chunli Peng', 'Boyang Wang', 'Puyi Wang', 'Qingcheng Zhu', 'Fei Kang', 'Biao Jiang', 'Zedong Gao', 'Eric Li', 'Yang Liu', 'Yahui Zhou'] | ['cs.CV', 'cs.AI'] | We introduce Matrix-Game, an interactive world foundation model for
controllable game world generation. Matrix-Game is trained using a two-stage
pipeline that first performs large-scale unlabeled pretraining for environment
understanding, followed by action-labeled training for interactive video
generation. To support ... | 2025-06-23T14:40:49Z | Technical Report | null | null | null | null | null | null | null | null | null |
2,506.18841 | LongWriter-Zero: Mastering Ultra-Long Text Generation via Reinforcement
Learning | ['Yuhao Wu', 'Yushi Bai', 'Zhiqiang Hu', 'Roy Ka-Wei Lee', 'Juanzi Li'] | ['cs.CL', 'cs.AI', 'cs.LG'] | Ultra-long generation by large language models (LLMs) is a widely demanded
scenario, yet it remains a significant challenge due to their maximum
generation length limit and overall quality degradation as sequence length
increases. Previous approaches, exemplified by LongWriter, typically rely on
''teaching'', which inv... | 2025-06-23T16:59:02Z | null | null | null | null | null | null | null | null | null | null |
2,506.18843 | USAD: Universal Speech and Audio Representation via Distillation | ['Heng-Jui Chang', 'Saurabhchand Bhati', 'James Glass', 'Alexander H. Liu'] | ['cs.SD', 'cs.CL', 'eess.AS'] | Self-supervised learning (SSL) has revolutionized audio representations, yet
models often remain domain-specific, focusing on either speech or non-speech
tasks. In this work, we present Universal Speech and Audio Distillation (USAD),
a unified approach to audio representation learning that integrates diverse
audio type... | 2025-06-23T17:02:00Z | Preprint | null | null | null | null | null | null | null | null | null |
2,506.18866 | OmniAvatar: Efficient Audio-Driven Avatar Video Generation with Adaptive
Body Animation | ['Qijun Gan', 'Ruizi Yang', 'Jianke Zhu', 'Shaofei Xue', 'Steven Hoi'] | ['cs.CV', 'cs.AI', 'cs.MM'] | Significant progress has been made in audio-driven human animation, while
most existing methods focus mainly on facial movements, limiting their ability
to create full-body animations with natural synchronization and fluidity. They
also struggle with precise prompt control for fine-grained generation. To
tackle these c... | 2025-06-23T17:33:03Z | Project page: https://omni-avatar.github.io/ | null | null | null | null | null | null | null | null | null |
2,506.18871 | OmniGen2: Exploration to Advanced Multimodal Generation | ['Chenyuan Wu', 'Pengfei Zheng', 'Ruiran Yan', 'Shitao Xiao', 'Xin Luo', 'Yueze Wang', 'Wanli Li', 'Xiyan Jiang', 'Yexin Liu', 'Junjie Zhou', 'Ze Liu', 'Ziyi Xia', 'Chaofan Li', 'Haoge Deng', 'Jiahao Wang', 'Kun Luo', 'Bo Zhang', 'Defu Lian', 'Xinlong Wang', 'Zhongyuan Wang', 'Tiejun Huang', 'Zheng Liu'] | ['cs.CV', 'cs.AI', 'cs.CL'] | In this work, we introduce OmniGen2, a versatile and open-source generative
model designed to provide a unified solution for diverse generation tasks,
including text-to-image, image editing, and in-context generation. Unlike
OmniGen v1, OmniGen2 features two distinct decoding pathways for text and image
modalities, uti... | 2025-06-23T17:38:54Z | null | null | null | null | null | null | null | null | null | null |
2,506.18896 | ReasonFlux-PRM: Trajectory-Aware PRMs for Long Chain-of-Thought
Reasoning in LLMs | ['Jiaru Zou', 'Ling Yang', 'Jingwen Gu', 'Jiahao Qiu', 'Ke Shen', 'Jingrui He', 'Mengdi Wang'] | ['cs.CL'] | Process Reward Models (PRMs) have recently emerged as a powerful framework
for supervising intermediate reasoning steps in large language models (LLMs).
Previous PRMs are primarily trained on model final output responses and
struggle to evaluate intermediate thinking trajectories robustly, especially in
the emerging se... | 2025-06-23T17:59:02Z | Codes and Models: https://github.com/Gen-Verse/ReasonFlux | null | null | null | null | null | null | null | null | null |
2,506.18898 | Vision as a Dialect: Unifying Visual Understanding and Generation via
Text-Aligned Representations | ['Jiaming Han', 'Hao Chen', 'Yang Zhao', 'Hanyu Wang', 'Qi Zhao', 'Ziyan Yang', 'Hao He', 'Xiangyu Yue', 'Lu Jiang'] | ['cs.CV', 'cs.AI', 'cs.CL', 'cs.MM'] | This paper presents a multimodal framework that attempts to unify visual
understanding and generation within a shared discrete semantic representation.
At its core is the Text-Aligned Tokenizer (TA-Tok), which converts images into
discrete tokens using a text-aligned codebook projected from a large language
model's (LL... | 2025-06-23T17:59:14Z | Project page: https://tar.csuhan.com | null | null | null | null | null | null | null | null | null |
2,506.18902 | jina-embeddings-v4: Universal Embeddings for Multimodal Multilingual
Retrieval | ['Michael Günther', 'Saba Sturua', 'Mohammad Kalim Akram', 'Isabelle Mohr', 'Andrei Ungureanu', 'Bo Wang', 'Sedigheh Eslami', 'Scott Martens', 'Maximilian Werk', 'Nan Wang', 'Han Xiao'] | ['cs.AI', 'cs.CL', 'cs.IR', '68T50', 'I.2.7'] | We introduce jina-embeddings-v4, a 3.8 billion parameter multimodal embedding
model that unifies text and image representations through a novel architecture
supporting both single-vector and multi-vector embeddings in the late
interaction style. The model incorporates task-specific Low-Rank Adaptation
(LoRA) adapters t... | 2025-06-23T17:59:55Z | 22 pages, 1-10 main, 14-22 experimental results, benchmark tables | null | null | null | null | null | null | null | null | null |
2,506.18903 | VMem: Consistent Interactive Video Scene Generation with Surfel-Indexed
View Memory | ['Runjia Li', 'Philip Torr', 'Andrea Vedaldi', 'Tomas Jakab'] | ['cs.CV'] | We propose a novel memory mechanism to build video generators that can
explore environments interactively. Similar results have previously been
achieved by out-painting 2D views of the scene while incrementally
reconstructing its 3D geometry, which quickly accumulates errors, or by video
generators with a short context... | 2025-06-23T17:59:56Z | Project page: https://v-mem.github.io | null | null | null | null | null | null | null | null | null |
2,506.18904 | TC-Light: Temporally Coherent Generative Rendering for Realistic World
Transfer | ['Yang Liu', 'Chuanchen Luo', 'Zimo Tang', 'Yingyan Li', 'Yuran Yang', 'Yuanyong Ning', 'Lue Fan', 'Zhaoxiang Zhang', 'Junran Peng'] | ['cs.CV'] | Illumination and texture editing are critical dimensions for world-to-world
transfer, which is valuable for applications including sim2real and real2real
visual data scaling up for embodied AI. Existing techniques generatively
re-render the input video to realize the transfer, such as video relighting
models and condit... | 2025-06-23T17:59:58Z | Project Page: https://dekuliutesla.github.io/tclight/ Code:
https://github.com/Linketic/TC-Light | null | null | null | null | null | null | null | null | null |
2,506.19103 | Inverse-and-Edit: Effective and Fast Image Editing by Cycle Consistency
Models | ['Ilia Beletskii', 'Andrey Kuznetsov', 'Aibek Alanov'] | ['cs.CV'] | Recent advances in image editing with diffusion models have achieved
impressive results, offering fine-grained control over the generation process.
However, these methods are computationally intensive because of their iterative
nature. While distilled diffusion models enable faster inference, their editing
capabilities... | 2025-06-23T20:34:43Z | The code of our method is available on GitHub at
https://github.com/ControlGenAI/Inverse-and-Edit | null | null | null | null | null | null | null | null | null |
2,506.1929 | Skywork-SWE: Unveiling Data Scaling Laws for Software Engineering in
LLMs | ['Liang Zeng', 'Yongcong Li', 'Yuzhen Xiao', 'Changshi Li', 'Chris Yuhao Liu', 'Rui Yan', 'Tianwen Wei', 'Jujie He', 'Xuchen Song', 'Yang Liu', 'Yahui Zhou'] | ['cs.AI', 'cs.CL'] | Software engineering (SWE) has recently emerged as a crucial testbed for
next-generation LLM agents, demanding inherent capabilities in two critical
dimensions: sustained iterative problem-solving (e.g., >50 interaction rounds)
and long-context dependency resolution (e.g., >32k tokens). However, the data
curation proce... | 2025-06-24T03:53:36Z | null | null | null | null | null | null | null | null | null | null |
2,506.19585 | SMARTIES: Spectrum-Aware Multi-Sensor Auto-Encoder for Remote Sensing
Images | ['Gencer Sumbul', 'Chang Xu', 'Emanuele Dalsasso', 'Devis Tuia'] | ['cs.CV'] | From optical sensors to microwave radars, leveraging the complementary
strengths of remote sensing (RS) sensors is crucial for achieving dense
spatio-temporal monitoring of our planet. In contrast, recent deep learning
models, whether task-specific or foundational, are often specific to single
sensors or to fixed combi... | 2025-06-24T12:51:39Z | null | null | null | null | null | null | null | null | null | null |
2,506.19697 | Outlier-Safe Pre-Training for Robust 4-Bit Quantization of Large
Language Models | ['Jungwoo Park', 'Taewhoo Lee', 'Chanwoong Yoon', 'Hyeon Hwang', 'Jaewoo Kang'] | ['cs.LG', 'cs.AI', 'cs.CL'] | Extreme activation outliers in Large Language Models (LLMs) critically
degrade quantization performance, hindering efficient on-device deployment.
While channel-wise operations and adaptive gradient scaling are recognized
causes, practical mitigation remains challenging. We introduce Outlier-Safe
Pre-Training (OSP), a ... | 2025-06-24T15:03:57Z | null | null | null | null | null | null | null | null | null | null |
2,506.19708 | Uncovering Conceptual Blindspots in Generative Image Models Using Sparse
Autoencoders | ['Matyas Bohacek', 'Thomas Fel', 'Maneesh Agrawala', 'Ekdeep Singh Lubana'] | ['cs.GR', 'cs.AI', 'cs.CV'] | Despite their impressive performance, generative image models trained on
large-scale datasets frequently fail to produce images with seemingly simple
concepts -- e.g., human hands or objects appearing in groups of four -- that
are reasonably expected to appear in the training data. These failure modes
have largely been... | 2025-06-24T15:15:15Z | null | null | null | null | null | null | null | null | null | null |
2,506.19753 | Arabic Dialect Classification using RNNs, Transformers, and Large
Language Models: A Comparative Analysis | ['Omar A. Essameldin', 'Ali O. Elbeih', 'Wael H. Gomaa', 'Wael F. Elsersy'] | ['cs.CL', 'cs.AI'] | The Arabic language is among the most popular languages in the world with a
huge variety of dialects spoken in 22 countries. In this study, we address the
problem of classifying 18 Arabic dialects of the QADI dataset of Arabic tweets.
RNN models, Transformer models, and large language models (LLMs) via prompt
engineeri... | 2025-06-24T16:06:58Z | Email Typo Update | null | null | null | null | null | null | null | null | null |
2,506.19767 | SRFT: A Single-Stage Method with Supervised and Reinforcement
Fine-Tuning for Reasoning | ['Yuqian Fu', 'Tinghong Chen', 'Jiajun Chai', 'Xihuai Wang', 'Songjun Tu', 'Guojun Yin', 'Wei Lin', 'Qichao Zhang', 'Yuanheng Zhu', 'Dongbin Zhao'] | ['cs.CL', 'cs.AI', 'cs.LG'] | Large language models (LLMs) have achieved remarkable progress in reasoning
tasks, yet the optimal integration of Supervised Fine-Tuning (SFT) and
Reinforcement Learning (RL) remains a fundamental challenge. Through
comprehensive analysis of token distributions, learning dynamics, and
integration mechanisms from entrop... | 2025-06-24T16:31:37Z | null | null | null | null | null | null | null | null | null | null |
2,506.19807 | KnowRL: Exploring Knowledgeable Reinforcement Learning for Factuality | ['Baochang Ren', 'Shuofei Qiao', 'Wenhao Yu', 'Huajun Chen', 'Ningyu Zhang'] | ['cs.AI', 'cs.CL', 'cs.CV', 'cs.LG', 'cs.MA'] | Large Language Models (LLMs), particularly slow-thinking models, often
exhibit severe hallucination, outputting incorrect content due to an inability
to accurately recognize knowledge boundaries during reasoning. While
Reinforcement Learning (RL) can enhance complex reasoning abilities, its
outcome-oriented reward mech... | 2025-06-24T17:17:17Z | Work in progress | null | null | null | null | null | null | null | null | null |
2,506.1985 | Unified Vision-Language-Action Model | ['Yuqi Wang', 'Xinghang Li', 'Wenxuan Wang', 'Junbo Zhang', 'Yingyan Li', 'Yuntao Chen', 'Xinlong Wang', 'Zhaoxiang Zhang'] | ['cs.CV', 'cs.RO'] | Vision-language-action models (VLAs) have garnered significant attention for
their potential in advancing robotic manipulation. However, previous approaches
predominantly rely on the general comprehension capabilities of vision-language
models (VLMs) to generate action signals, often overlooking the rich temporal
and c... | 2025-06-24T17:59:57Z | technical report | null | null | null | null | null | null | null | null | null |
2,506.20151 | EAR: Erasing Concepts from Unified Autoregressive Models | ['Haipeng Fan', 'Shiyuan Zhang', 'Baohunesitu', 'Zihang Guo', 'Huaiwen Zhang'] | ['cs.CV', 'cs.AI'] | Autoregressive (AR) models have achieved unified and strong performance
across both visual understanding and image generation tasks. However, removing
undesired concepts from AR models while maintaining overall generation quality
remains an open challenge. In this paper, we propose Erasure Autoregressive
Model (EAR), a... | 2025-06-25T06:15:07Z | 11 pages, 7 figures, 1 tables | null | null | null | null | null | null | null | null | null |
2,506.20279 | From Ideal to Real: Unified and Data-Efficient Dense Prediction for
Real-World Scenarios | ['Changliang Xia', 'Chengyou Jia', 'Zhuohang Dang', 'Minnan Luo'] | ['cs.CV'] | Dense prediction tasks hold significant importance of computer vision, aiming
to learn pixel-wise annotated label for an input image. Despite advances in
this field, existing methods primarily focus on idealized conditions, with
limited generalization to real-world scenarios and facing the challenging
scarcity of real-... | 2025-06-25T09:40:50Z | null | null | null | null | null | null | null | null | null | null |
2,506.20326 | From Codicology to Code: A Comparative Study of Transformer and
YOLO-based Detectors for Layout Analysis in Historical Documents | ['Sergio Torres Aguilar'] | ['cs.CV', 'cs.CL', 'cs.DB'] | Robust Document Layout Analysis (DLA) is critical for the automated
processing and understanding of historical documents with complex page
organizations. This paper benchmarks five state-of-the-art object detection
architectures on three annotated datasets representing a spectrum of
codicological complexity: The e-NDP,... | 2025-06-25T11:14:04Z | null | null | null | null | null | null | null | null | null | null |
2,506.2048 | GPTailor: Large Language Model Pruning Through Layer Cutting and
Stitching | ['Guinan Su', 'Li Shen', 'Lu Yin', 'Shiwei Liu', 'Yanwu Yang', 'Jonas Geiping'] | ['cs.CL'] | Large language models (LLMs) have shown remarkable capabilities in language
understanding and generation. However, such impressive capability typically
comes with a substantial model size, which presents significant challenges in
deployment and inference. While structured pruning of model parameters offers a
promising ... | 2025-06-25T14:24:59Z | null | null | null | null | null | null | null | null | null | null |
2,506.20512 | OctoThinker: Mid-training Incentivizes Reinforcement Learning Scaling | ['Zengzhi Wang', 'Fan Zhou', 'Xuefeng Li', 'Pengfei Liu'] | ['cs.CL', 'cs.AI', 'cs.LG'] | Different base language model families, such as Llama and Qwen, exhibit
divergent behaviors during post-training with reinforcement learning (RL),
especially on reasoning-intensive tasks. What makes a base language model
suitable for reinforcement learning? Gaining deeper insight into this question
is essential for dev... | 2025-06-25T14:58:13Z | 26 pages; The first three authors contribute to this work equally | null | null | null | null | null | null | null | null | null |
2,506.20639 | DiffuCoder: Understanding and Improving Masked Diffusion Models for Code
Generation | ['Shansan Gong', 'Ruixiang Zhang', 'Huangjie Zheng', 'Jiatao Gu', 'Navdeep Jaitly', 'Lingpeng Kong', 'Yizhe Zhang'] | ['cs.CL'] | Diffusion large language models (dLLMs) are compelling alternatives to
autoregressive (AR) models because their denoising models operate over the
entire sequence. The global planning and iterative refinement features of dLLMs
are particularly useful for code generation. However, current training and
inference mechanism... | 2025-06-25T17:35:47Z | minor update | null | null | null | null | null | null | null | null | null |
2,506.20741 | OTSurv: A Novel Multiple Instance Learning Framework for Survival
Prediction with Heterogeneity-aware Optimal Transport | ['Qin Ren', 'Yifan Wang', 'Ruogu Fang', 'Haibin Ling', 'Chenyu You'] | ['cs.CV'] | Survival prediction using whole slide images (WSIs) can be formulated as a
multiple instance learning (MIL) problem. However, existing MIL methods often
fail to explicitly capture pathological heterogeneity within WSIs, both
globally -- through long-tailed morphological distributions, and locally
through -- tile-level ... | 2025-06-25T18:09:42Z | Accepted by International Conference on Medical Image Computing and
Computer-Assisted Intervention (MICCAI 2025) | null | null | null | null | null | null | null | null | null |
2,506.20923 | KaLM-Embedding-V2: Superior Training Techniques and Data Inspire A
Versatile Embedding Model | ['Xinping Zhao', 'Xinshuo Hu', 'Zifei Shan', 'Shouzheng Huang', 'Yao Zhou', 'Zetian Sun', 'Zhenyu Liu', 'Dongfang Li', 'Xinyuan Wei', 'Qian Chen', 'Youcheng Pan', 'Yang Xiang', 'Meishan Zhang', 'Haofen Wang', 'Jun Yu', 'Baotian Hu', 'Min Zhang'] | ['cs.CL'] | In this paper, we propose KaLM-Embedding-V2, a versatile and compact
embedding model, which achieves impressive performance in general-purpose text
embedding tasks by leveraging superior training techniques and data. Our key
innovations include: (1) To better align the architecture with representation
learning, we remo... | 2025-06-26T01:09:44Z | Technical Report; 26 pages 12 tables 1 figure. arXiv admin note:
substantial text overlap with arXiv:2501.01028 | null | null | null | null | null | null | null | null | null |
2,506.2109 | Post-training for Deepfake Speech Detection | ['Wanying Ge', 'Xin Wang', 'Xuechen Liu', 'Junichi Yamagishi'] | ['eess.AS'] | We introduce a post-training approach that adapts self-supervised learning
(SSL) models for deepfake speech detection by bridging the gap between general
pre-training and domain-specific fine-tuning. We present AntiDeepfake models, a
series of post-trained models developed using a large-scale multilingual speech
datase... | 2025-06-26T08:34:19Z | null | null | null | null | null | null | null | null | null | null |
2,506.21103 | Learning to Skip the Middle Layers of Transformers | ['Tim Lawson', 'Laurence Aitchison'] | ['cs.LG', 'cs.CL'] | Conditional computation is a popular strategy to make Transformers more
efficient. Existing methods often target individual modules (e.g.,
mixture-of-experts layers) or skip layers independently of one another.
However, interpretability research has demonstrated that the middle layers of
Transformers exhibit greater re... | 2025-06-26T09:01:19Z | 11 pages, 2 figures | null | null | null | null | null | null | null | null | null |
2,506.21277 | HumanOmniV2: From Understanding to Omni-Modal Reasoning with Context | ['Qize Yang', 'Shimin Yao', 'Weixuan Chen', 'Shenghao Fu', 'Detao Bai', 'Jiaxing Zhao', 'Boyuan Sun', 'Bowen Yin', 'Xihan Wei', 'Jingren Zhou'] | ['cs.CV', 'cs.CL'] | With the rapid evolution of multimodal large language models, the capacity to
deeply understand and interpret human intentions has emerged as a critical
capability, which demands detailed and thoughtful reasoning. In recent studies,
Reinforcement Learning (RL) has demonstrated potential in enhancing the
reasoning capab... | 2025-06-26T14:01:03Z | null | null | null | null | null | null | null | null | null | null |
2,506.21356 | ShotBench: Expert-Level Cinematic Understanding in Vision-Language
Models | ['Hongbo Liu', 'Jingwen He', 'Yi Jin', 'Dian Zheng', 'Yuhao Dong', 'Fan Zhang', 'Ziqi Huang', 'Yinan He', 'Yangguang Li', 'Weichao Chen', 'Yu Qiao', 'Wanli Ouyang', 'Shengjie Zhao', 'Ziwei Liu'] | ['cs.CV'] | Cinematography, the fundamental visual language of film, is essential for
conveying narrative, emotion, and aesthetic quality. While recent
Vision-Language Models (VLMs) demonstrate strong general visual understanding,
their proficiency in comprehending the nuanced cinematic grammar embedded
within individual shots rem... | 2025-06-26T15:09:21Z | null | null | null | null | null | null | null | null | null | null |
2,506.21416 | XVerse: Consistent Multi-Subject Control of Identity and Semantic
Attributes via DiT Modulation | ['Bowen Chen', 'Mengyi Zhao', 'Haomiao Sun', 'Li Chen', 'Xu Wang', 'Kang Du', 'Xinglong Wu'] | ['cs.CV'] | Achieving fine-grained control over subject identity and semantic attributes
(pose, style, lighting) in text-to-image generation, particularly for multiple
subjects, often undermines the editability and coherence of Diffusion
Transformers (DiTs). Many approaches introduce artifacts or suffer from
attribute entanglement... | 2025-06-26T16:04:16Z | Project Page: https://bytedance.github.io/XVerse Github Link:
https://github.com/bytedance/XVerse | null | null | null | null | null | null | null | null | null |
2,506.21448 | ThinkSound: Chain-of-Thought Reasoning in Multimodal Large Language
Models for Audio Generation and Editing | ['Huadai Liu', 'Jialei Wang', 'Kaicheng Luo', 'Wen Wang', 'Qian Chen', 'Zhou Zhao', 'Wei Xue'] | ['eess.AS', 'cs.CV', 'cs.SD'] | While end-to-end video-to-audio generation has greatly improved, producing
high-fidelity audio that authentically captures the nuances of visual content
remains challenging. Like professionals in the creative industries, such
generation requires sophisticated reasoning about items such as visual
dynamics, acoustic envi... | 2025-06-26T16:32:06Z | null | null | null | null | null | null | null | null | null | null |
2,506.21458 | Spatial Mental Modeling from Limited Views | ['Baiqiao Yin', 'Qineng Wang', 'Pingyue Zhang', 'Jianshu Zhang', 'Kangrui Wang', 'Zihan Wang', 'Jieyu Zhang', 'Keshigeyan Chandrasegaran', 'Han Liu', 'Ranjay Krishna', 'Saining Xie', 'Manling Li', 'Jiajun Wu', 'Li Fei-Fei'] | ['cs.AI', 'cs.CL', 'cs.CV'] | Can Vision Language Models (VLMs) imagine the full scene from just a few
views, like humans do? Humans form spatial mental models, internal
representations of unseen space, to reason about layout, perspective, and
motion. Our new MindCube benchmark with 21,154 questions across 3,268 images
exposes this critical gap, wh... | 2025-06-26T16:38:19Z | Preprint version | null | null | null | null | null | null | null | null | null |
2,506.21476 | Global and Local Entailment Learning for Natural World Imagery | ['Srikumar Sastry', 'Aayush Dhakal', 'Eric Xing', 'Subash Khanal', 'Nathan Jacobs'] | ['cs.CV'] | Learning the hierarchical structure of data in vision-language models is a
significant challenge. Previous works have attempted to address this challenge
by employing entailment learning. However, these approaches fail to model the
transitive nature of entailment explicitly, which establishes the relationship
between o... | 2025-06-26T17:05:06Z | Accepted at ICCV 2025 | null | null | null | null | null | null | null | null | null |
2,506.21539 | WorldVLA: Towards Autoregressive Action World Model | ['Jun Cen', 'Chaohui Yu', 'Hangjie Yuan', 'Yuming Jiang', 'Siteng Huang', 'Jiayan Guo', 'Xin Li', 'Yibing Song', 'Hao Luo', 'Fan Wang', 'Deli Zhao', 'Hao Chen'] | ['cs.RO', 'cs.AI'] | We present WorldVLA, an autoregressive action world model that unifies action
and image understanding and generation. Our WorldVLA intergrates
Vision-Language-Action (VLA) model and world model in one single framework. The
world model predicts future images by leveraging both action and image
understanding, with the pu... | 2025-06-26T17:55:40Z | Code: https://github.com/alibaba-damo-academy/WorldVLA | null | null | null | null | null | null | null | null | null |
2,506.21594 | Gazal-R1: Achieving State-of-the-Art Medical Reasoning with
Parameter-Efficient Two-Stage Training | ['Ahmed M. Adly', 'Mostafa Samy', 'Amr Fawzy'] | ['cs.CL'] | We present Gazal-R1, a 32-billion-parameter language model that achieves
state-of-the-art performance in medical reasoning while providing transparent,
step-by-step explanations for clinical decision-making. Built upon Qwen3 32B,
our model demonstrates that strategic training can enable mid-sized models to
outperform s... | 2025-06-18T09:44:21Z | null | null | null | null | null | null | null | null | null | null |
2,506.21862 | LLaVA-Scissor: Token Compression with Semantic Connected Components for
Video LLMs | ['Boyuan Sun', 'Jiaxing Zhao', 'Xihan Wei', 'Qibin Hou'] | ['cs.CV', 'cs.AI', 'cs.HC', 'cs.MM'] | In this paper, we present LLaVA-Scissor, a training-free token compression
strategy designed for video multimodal large language models. Previous methods
mostly attempt to compress tokens based on attention scores, but fail to
effectively capture all semantic regions and often lead to token redundancy.
Differently, we ... | 2025-06-27T02:29:58Z | 21 pages, 4 figures, 7 tables | null | null | null | null | null | null | null | null | null |
2,506.2276 | Jan-nano Technical Report | ['Alan Dao', 'Dinh Bach Vu'] | ['cs.CL'] | Most language models face a fundamental tradeoff where powerful capabilities
require substantial computational resources. We shatter this constraint with
Jan-nano, a 4B parameter language model that redefines efficiency through
radical specialization: instead of trying to know everything, it masters the
art of finding ... | 2025-06-28T05:44:57Z | null | null | null | null | null | null | null | null | null | null |
2,506.22832 | Listener-Rewarded Thinking in VLMs for Image Preferences | ['Alexander Gambashidze', 'Li Pengyi', 'Matvey Skripkin', 'Andrey Galichin', 'Anton Gusarov', 'Konstantin Sobolev', 'Andrey Kuznetsov', 'Ivan Oseledets'] | ['cs.CV', 'cs.AI'] | Training robust and generalizable reward models for human visual preferences
is essential for aligning text-to-image and text-to-video generative models
with human intent. However, current reward models often fail to generalize, and
supervised fine-tuning leads to memorization, demanding complex annotation
pipelines. W... | 2025-06-28T09:53:17Z | null | null | null | null | null | null | null | null | null | null |
2,506.22919 | Hecto: Modular Sparse Experts for Adaptive and Interpretable Reasoning | ['Sanskar Pandey', 'Ruhaan Chopra', 'Saad Murtaza Bhat', 'Ark Abhyudaya'] | ['cs.AI'] | Mixture-of-Experts (MoE) models enable conditional computation by routing
inputs to specialized experts, but these experts rely on identical inductive
biases, thus limiting representational diversity. This static computation
pathway is inefficient for inputs that require different types of reasoning and
limits speciali... | 2025-06-28T15:03:43Z | null | null | null | null | null | null | null | null | null | null |
2,506.22973 | Confident Splatting: Confidence-Based Compression of 3D Gaussian
Splatting via Learnable Beta Distributions | ['AmirHossein Naghi Razlighi', 'Elaheh Badali Golezani', 'Shohreh Kasaei'] | ['cs.GR', 'cs.CV'] | 3D Gaussian Splatting enables high-quality real-time rendering but often
produces millions of splats, resulting in excessive storage and computational
overhead. We propose a novel lossy compression method based on learnable
confidence scores modeled as Beta distributions. Each splat's confidence is
optimized through re... | 2025-06-28T18:11:30Z | null | null | null | null | null | null | null | null | null | null |
2,506.23009 | MusiXQA: Advancing Visual Music Understanding in Multimodal Large
Language Models | ['Jian Chen', 'Wenye Ma', 'Penghang Liu', 'Wei Wang', 'Tengwei Song', 'Ming Li', 'Chenguang Wang', 'Ruiyi Zhang', 'Changyou Chen'] | ['cs.CV'] | Multimodal Large Language Models (MLLMs) have achieved remarkable visual
reasoning abilities in natural images, text-rich documents, and graphic
designs. However, their ability to interpret music sheets remains
underexplored. To bridge this gap, we introduce MusiXQA, the first
comprehensive dataset for evaluating and a... | 2025-06-28T20:46:47Z | null | null | null | null | null | null | null | null | null | null |
2,506.23044 | Ovis-U1 Technical Report | ['Guo-Hua Wang', 'Shanshan Zhao', 'Xinjie Zhang', 'Liangfu Cao', 'Pengxin Zhan', 'Lunhao Duan', 'Shiyin Lu', 'Minghao Fu', 'Xiaohao Chen', 'Jianshan Zhao', 'Yang Li', 'Qing-Guo Chen'] | ['cs.CV', 'cs.AI'] | In this report, we introduce Ovis-U1, a 3-billion-parameter unified model
that integrates multimodal understanding, text-to-image generation, and image
editing capabilities. Building on the foundation of the Ovis series, Ovis-U1
incorporates a diffusion-based visual decoder paired with a bidirectional token
refiner, en... | 2025-06-29T00:40:17Z | An unified model for multimodal understanding, text-to-image
generation, and image editing. GitHub: https://github.com/AIDC-AI/Ovis-U1 | null | null | null | null | null | null | null | null | null |
2,506.23077 | Dynamic Contrastive Learning for Hierarchical Retrieval: A Case Study of
Distance-Aware Cross-View Geo-Localization | ['Suofei Zhang', 'Xinxin Wang', 'Xiaofu Wu', 'Quan Zhou', 'Haifeng Hu'] | ['cs.CV'] | Existing deep learning-based cross-view geo-localization methods primarily
focus on improving the accuracy of cross-domain image matching, rather than
enabling models to comprehensively capture contextual information around the
target and minimize the cost of localization errors. To support systematic
research into thi... | 2025-06-29T03:57:01Z | null | null | null | null | null | null | null | null | null | null |
2,506.23115 | MoCa: Modality-aware Continual Pre-training Makes Better Bidirectional
Multimodal Embeddings | ['Haonan Chen', 'Hong Liu', 'Yuping Luo', 'Liang Wang', 'Nan Yang', 'Furu Wei', 'Zhicheng Dou'] | ['cs.CV', 'cs.AI', 'cs.CL'] | Multimodal embedding models, built upon causal Vision Language Models (VLMs),
have shown promise in various tasks. However, current approaches face three key
limitations: the use of causal attention in VLM backbones is suboptimal for
embedding tasks; scalability issues due to reliance on high-quality labeled
paired dat... | 2025-06-29T06:41:00Z | Homepage: https://haon-chen.github.io/MoCa/ | null | null | null | null | null | null | null | null | null |
2,506.23151 | MEMFOF: High-Resolution Training for Memory-Efficient Multi-Frame
Optical Flow Estimation | ['Vladislav Bargatin', 'Egor Chistov', 'Alexander Yakovenko', 'Dmitriy Vatolin'] | ['cs.CV', 'cs.AI', 'cs.MM'] | Recent advances in optical flow estimation have prioritized accuracy at the
cost of growing GPU memory consumption, particularly for high-resolution
(FullHD) inputs. We introduce MEMFOF, a memory-efficient multi-frame optical
flow method that identifies a favorable trade-off between multi-frame
estimation and GPU memor... | 2025-06-29T09:01:42Z | Accepted at ICCV 2025 | null | null | null | null | null | null | null | null | null |
2,506.23325 | XY-Tokenizer: Mitigating the Semantic-Acoustic Conflict in Low-Bitrate
Speech Codecs | ['Yitian Gong', 'Luozhijie Jin', 'Ruifan Deng', 'Dong Zhang', 'Xin Zhang', 'Qinyuan Cheng', 'Zhaoye Fei', 'Shimin Li', 'Xipeng Qiu'] | ['cs.SD', 'cs.AI', 'eess.AS'] | Speech codecs serve as bridges between speech signals and large language
models. An ideal codec for speech language models should not only preserve
acoustic information but also capture rich semantic information. However,
existing speech codecs struggle to balance high-quality audio reconstruction
with ease of modeling... | 2025-06-29T16:51:50Z | null | null | null | null | null | null | null | null | null | null |
2,506.23394 | Teaching a Language Model to Speak the Language of Tools | ['Simeon Emanuilov'] | ['cs.IR', 'cs.AI', 'cs.CL', 'I.2.7; I.2.1'] | External tool integration through function-calling is essential for practical
language model applications, yet most multilingual models lack reliable
tool-use capabilities in non-English languages. Even state-of-the-art
multilingual models struggle with determining when to use tools and generating
the structured output... | 2025-06-29T20:47:27Z | null | null | null | null | null | null | null | null | null | null |
2,506.23491 | ZonUI-3B: A Lightweight Vision-Language Model for Cross-Resolution GUI
Grounding | ['ZongHan Hsieh', 'Tzer-Jen Wei', 'ShengJing Yang'] | ['cs.CV', 'cs.AI'] | This paper introduces ZonUI-3B, a lightweight Vision-Language Model (VLM)
specifically designed for Graphical User Interface grounding tasks, achieving
performance competitive with significantly larger models. Unlike large-scale
VLMs (>7B parameters) that are computationally intensive and impractical for
consumer-grade... | 2025-06-30T03:33:02Z | null | null | null | null | null | null | null | null | null | null |
2,506.2367 | Efficient Interleaved Speech Modeling through Knowledge Distillation | ['Mohammadmahdi Nouriborji', 'Morteza Rohanian'] | ['cs.SD', 'cs.CL', 'eess.AS'] | Current speech language models exceed the size and latency constraints of
many deployment environments. We build compact, expressive speech generation
models through layer-aligned distillation, matching hidden states, attention
maps, and softened logits to compress large multimodal transformers by 3x with
minimal loss ... | 2025-06-30T09:47:37Z | null | null | null | null | null | null | null | null | null | null |
2,506.23822 | Interpretable Zero-Shot Learning with Locally-Aligned Vision-Language
Model | ['Shiming Chen', 'Bowen Duan', 'Salman Khan', 'Fahad Shahbaz Khan'] | ['cs.CV'] | Large-scale vision-language models (VLMs), such as CLIP, have achieved
remarkable success in zero-shot learning (ZSL) by leveraging large-scale
visual-text pair datasets. However, these methods often lack interpretability,
as they compute the similarity between an entire query image and the embedded
category words, mak... | 2025-06-30T13:14:46Z | Accepted to ICCV'25 | null | null | null | null | null | null | null | null | null |
2,506.23869 | Scaling Self-Supervised Representation Learning for Symbolic Piano
Performance | ['Louis Bradshaw', 'Honglu Fan', 'Alexander Spangher', 'Stella Biderman', 'Simon Colton'] | ['cs.SD', 'cs.AI', 'cs.LG', 'eess.AS'] | We study the capabilities of generative autoregressive transformer models
trained on large amounts of symbolic solo-piano transcriptions. After first
pretraining on approximately 60,000 hours of music, we use a comparatively
smaller, high-quality subset, to finetune models to produce musical
continuations, perform symb... | 2025-06-30T14:00:14Z | ISMIR (2025) | null | null | null | null | null | null | null | null | null |
2,506.23971 | UMA: A Family of Universal Models for Atoms | ['Brandon M. Wood', 'Misko Dzamba', 'Xiang Fu', 'Meng Gao', 'Muhammed Shuaibi', 'Luis Barroso-Luque', 'Kareem Abdelmaqsoud', 'Vahe Gharakhanyan', 'John R. Kitchin', 'Daniel S. Levine', 'Kyle Michel', 'Anuroop Sriram', 'Taco Cohen', 'Abhishek Das', 'Ammar Rizvi', 'Sushree Jagriti Sahoo', 'Zachary W. Ulissi', 'C. Lawrenc... | ['cs.LG'] | The ability to quickly and accurately compute properties from atomic
simulations is critical for advancing a large number of applications in
chemistry and materials science including drug discovery, energy storage, and
semiconductor manufacturing. To address this need, Meta FAIR presents a family
of Universal Models fo... | 2025-06-30T15:38:13Z | 29 pages, 5 figures | null | null | null | null | null | null | null | null | null |
2,506.24085 | Imagine for Me: Creative Conceptual Blending of Real Images and Text via
Blended Attention | ['Wonwoong Cho', 'Yanxia Zhang', 'Yan-Ying Chen', 'David I. Inouye'] | ['cs.CV', 'cs.AI'] | Blending visual and textual concepts into a new visual concept is a unique
and powerful trait of human beings that can fuel creativity. However, in
practice, cross-modal conceptual blending for humans is prone to cognitive
biases, like design fixation, which leads to local minima in the design space.
In this paper, we ... | 2025-06-30T17:41:25Z | Project website is available at https://imagineforme.github.io/ | null | null | null | null | null | null | null | null | null |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.