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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2,406.06371 | mHuBERT-147: A Compact Multilingual HuBERT Model | ['Marcely Zanon Boito', 'Vivek Iyer', 'Nikolaos Lagos', 'Laurent Besacier', 'Ioan Calapodescu'] | ['cs.CL', 'cs.SD', 'eess.AS'] | We present mHuBERT-147, the first general-purpose massively multilingual
HuBERT speech representation model trained on 90K hours of clean, open-license
data. To scale up the multi-iteration HuBERT approach, we use faiss-based
clustering, achieving 5.2x faster label assignment than the original method. We
also apply a n... | 2024-06-10T15:32:42Z | Extended version of the Interspeech 2024 paper of same name | null | null | null | null | null | null | null | null | null |
2,406.06419 | Foundation Inference Models for Markov Jump Processes | ['David Berghaus', 'Kostadin Cvejoski', 'Patrick Seifner', 'Cesar Ojeda', 'Ramses J. Sanchez'] | ['cs.LG', 'stat.ML'] | Markov jump processes are continuous-time stochastic processes which describe
dynamical systems evolving in discrete state spaces. These processes find wide
application in the natural sciences and machine learning, but their inference
is known to be far from trivial. In this work we introduce a methodology for
zero-sho... | 2024-06-10T16:12:00Z | null | null | null | Foundation Inference Models for Markov Jump Processes | ['David Berghaus', 'K. Cvejoski', 'Patrick Seifner', 'C. Ojeda', 'Ramsés J. Sánchez'] | 2,024 | Neural Information Processing Systems | 1 | 49 | ['Computer Science', 'Mathematics'] |
2,406.06424 | Margin-aware Preference Optimization for Aligning Diffusion Models
without Reference | ['Jiwoo Hong', 'Sayak Paul', 'Noah Lee', 'Kashif Rasul', 'James Thorne', 'Jongheon Jeong'] | ['cs.CV'] | Modern alignment techniques based on human preferences, such as RLHF and DPO,
typically employ divergence regularization relative to the reference model to
ensure training stability. However, this often limits the flexibility of models
during alignment, especially when there is a clear distributional discrepancy
betwee... | 2024-06-10T16:14:45Z | Preprint | null | null | Margin-aware Preference Optimization for Aligning Diffusion Models without Reference | ['Jiwoo Hong', 'Sayak Paul', 'Noah Lee', 'Kashif Rasul', 'James Thorne', 'Jongheon Jeong'] | 2,024 | arXiv.org | 18 | 95 | ['Computer Science'] |
2,406.06484 | Parallelizing Linear Transformers with the Delta Rule over Sequence
Length | ['Songlin Yang', 'Bailin Wang', 'Yu Zhang', 'Yikang Shen', 'Yoon Kim'] | ['cs.LG', 'cs.CL'] | Transformers with linear attention (i.e., linear transformers) and
state-space models have recently been suggested as a viable linear-time
alternative to transformers with softmax attention. However, these models still
underperform transformers especially on tasks that require in-context
retrieval. While more expressiv... | 2024-06-10T17:24:42Z | Final camera ready | null | null | Parallelizing Linear Transformers with the Delta Rule over Sequence Length | ['Songlin Yang', 'Bailin Wang', 'Yu Zhang', 'Yikang Shen', 'Yoon Kim'] | 2,024 | Neural Information Processing Systems | 89 | 135 | ['Computer Science'] |
2,406.06496 | Direct Preference Optimization for Suppressing Hallucinated Prior Exams
in Radiology Report Generation | ['Oishi Banerjee', 'Hong-Yu Zhou', 'Subathra Adithan', 'Stephen Kwak', 'Kay Wu', 'Pranav Rajpurkar'] | ['cs.LG', 'cs.CL', 'cs.CV'] | Recent advances in generative vision-language models (VLMs) have exciting
potential implications for AI in radiology, yet VLMs are also known to produce
hallucinations, nonsensical text, and other unwanted behaviors that can waste
clinicians' time and cause patient harm. Drawing on recent work on direct
preference opti... | 2024-06-10T17:31:36Z | Added acknowledgemnts | null | null | Direct Preference Optimization for Suppressing Hallucinated Prior Exams in Radiology Report Generation | ['Oishi Banerjee', 'Hong-Yu Zhou', 'Subathra Adithan', 'Stephen Kwak', 'Kay Wu', 'P. Rajpurkar'] | 2,024 | arXiv.org | 3 | 29 | ['Computer Science'] |
2,406.06512 | Merlin: A Vision Language Foundation Model for 3D Computed Tomography | ['Louis Blankemeier', 'Joseph Paul Cohen', 'Ashwin Kumar', 'Dave Van Veen', 'Syed Jamal Safdar Gardezi', 'Magdalini Paschali', 'Zhihong Chen', 'Jean-Benoit Delbrouck', 'Eduardo Reis', 'Cesar Truyts', 'Christian Bluethgen', 'Malte Engmann Kjeldskov Jensen', 'Sophie Ostmeier', 'Maya Varma', 'Jeya Maria Jose Valanarasu', ... | ['cs.CV', 'cs.AI'] | Over 85 million computed tomography (CT) scans are performed annually in the
US, of which approximately one quarter focus on the abdomen. Given the current
radiologist shortage, there is a large impetus to use artificial intelligence
to alleviate the burden of interpreting these complex imaging studies. Prior
state-of-... | 2024-06-10T17:53:01Z | 18 pages, 7 figures | null | null | Merlin: A Vision Language Foundation Model for 3D Computed Tomography | ['Louis Blankemeier', 'Joseph Paul Cohen', 'Ashwin Kumar', 'Dave Van Veen', 'Syed Jamal Safdar Gardezi', 'Magdalini Paschali', 'Zhihong Chen', 'Jean-Benoit Delbrouck', 'E. Reis', 'C. Truyts', 'Christian Bluethgen', 'Malte E. K. Jensen', 'Sophie Ostmeier', 'Maya Varma', 'Jeya Maria Jose Valanarasu', 'Zhongnan Fang', 'Ze... | 2,024 | Research Square | 41 | 94 | ['Computer Science', 'Medicine'] |
2,406.06525 | Autoregressive Model Beats Diffusion: Llama for Scalable Image
Generation | ['Peize Sun', 'Yi Jiang', 'Shoufa Chen', 'Shilong Zhang', 'Bingyue Peng', 'Ping Luo', 'Zehuan Yuan'] | ['cs.CV'] | We introduce LlamaGen, a new family of image generation models that apply
original ``next-token prediction'' paradigm of large language models to visual
generation domain. It is an affirmative answer to whether vanilla
autoregressive models, e.g., Llama, without inductive biases on visual signals
can achieve state-of-t... | 2024-06-10T17:59:52Z | Codes and models: \url{https://github.com/FoundationVision/LlamaGen} | null | null | Autoregressive Model Beats Diffusion: Llama for Scalable Image Generation | ['Peize Sun', 'Yi Jiang', 'Shoufa Chen', 'Shilong Zhang', 'Bingyue Peng', 'Ping Luo', 'Zehuan Yuan'] | 2,024 | arXiv.org | 301 | 98 | ['Computer Science'] |
2,406.06526 | Generative Gaussian Splatting for Unbounded 3D City Generation | ['Haozhe Xie', 'Zhaoxi Chen', 'Fangzhou Hong', 'Ziwei Liu'] | ['cs.CV'] | 3D city generation with NeRF-based methods shows promising generation results
but is computationally inefficient. Recently 3D Gaussian Splatting (3D-GS) has
emerged as a highly efficient alternative for object-level 3D generation.
However, adapting 3D-GS from finite-scale 3D objects and humans to
infinite-scale 3D citi... | 2024-06-10T17:59:55Z | CVPR 2025. Project Page: https://haozhexie.com/project/gaussian-city | null | null | Generative Gaussian Splatting for Unbounded 3D City Generation | ['Haozhe Xie', 'Zhaoxi Chen', 'Fangzhou Hong', 'Ziwei Liu'] | 2,024 | Computer Vision and Pattern Recognition | 12 | 66 | ['Computer Science'] |
2,406.06561 | Brainstorming Brings Power to Large Language Models of Knowledge
Reasoning | ['Zining Qin', 'Chenhao Wang', 'Huiling Qin', 'Weijia Jia'] | ['cs.CL', 'cs.AI'] | Large Language Models (LLMs) have demonstrated amazing capabilities in
language generation, text comprehension, and knowledge reasoning. While a
single powerful model can already handle multiple tasks, relying on a single
perspective can lead to biased and unstable results. Recent studies have
further improved the mode... | 2024-06-02T14:47:14Z | null | null | null | null | null | null | null | null | null | null |
2,406.06563 | Skywork-MoE: A Deep Dive into Training Techniques for Mixture-of-Experts
Language Models | ['Tianwen Wei', 'Bo Zhu', 'Liang Zhao', 'Cheng Cheng', 'Biye Li', 'Weiwei Lü', 'Peng Cheng', 'Jianhao Zhang', 'Xiaoyu Zhang', 'Liang Zeng', 'Xiaokun Wang', 'Yutuan Ma', 'Rui Hu', 'Shuicheng Yan', 'Han Fang', 'Yahui Zhou'] | ['cs.CL', 'cs.AI'] | In this technical report, we introduce the training methodologies implemented
in the development of Skywork-MoE, a high-performance mixture-of-experts (MoE)
large language model (LLM) with 146 billion parameters and 16 experts. It is
initialized from the pre-existing dense checkpoints of our Skywork-13B model.
We explo... | 2024-06-03T03:58:41Z | null | null | null | null | null | null | null | null | null | null |
2,406.06592 | Improve Mathematical Reasoning in Language Models by Automated Process
Supervision | ['Liangchen Luo', 'Yinxiao Liu', 'Rosanne Liu', 'Samrat Phatale', 'Meiqi Guo', 'Harsh Lara', 'Yunxuan Li', 'Lei Shu', 'Yun Zhu', 'Lei Meng', 'Jiao Sun', 'Abhinav Rastogi'] | ['cs.CL', 'cs.LG'] | Complex multi-step reasoning tasks, such as solving mathematical problems or
generating code, remain a significant hurdle for even the most advanced large
language models (LLMs). Verifying LLM outputs with an Outcome Reward Model
(ORM) is a standard inference-time technique aimed at enhancing the reasoning
performance ... | 2024-06-05T19:25:40Z | 17 pages, 5 figures, 2 table | null | null | Improve Mathematical Reasoning in Language Models by Automated Process Supervision | ['Liangchen Luo', 'Yinxiao Liu', 'Rosanne Liu', 'Samrat Phatale', 'Harsh Lara', 'Yunxuan Li', 'Lei Shu', 'Yun Zhu', 'Lei Meng', 'Jiao Sun', 'Abhinav Rastogi'] | 2,024 | arXiv.org | 193 | 27 | ['Computer Science'] |
2,406.06612 | SEE-2-SOUND: Zero-Shot Spatial Environment-to-Spatial Sound | ['Rishit Dagli', 'Shivesh Prakash', 'Robert Wu', 'Houman Khosravani'] | ['cs.CV', 'cs.LG', 'cs.SD', 'eess.AS'] | Generating combined visual and auditory sensory experiences is critical for
the consumption of immersive content. Recent advances in neural generative
models have enabled the creation of high-resolution content across multiple
modalities such as images, text, speech, and videos. Despite these successes,
there remains a... | 2024-06-06T22:55:01Z | Project Page: https://see2sound.github.io/ | null | null | null | null | null | null | null | null | null |
2,406.06623 | Spectrum: Targeted Training on Signal to Noise Ratio | ['Eric Hartford', 'Lucas Atkins', 'Fernando Fernandes Neto', 'David Golchinfar'] | ['cs.LG', 'stat.ML'] | Efficiently post-training large language models remains a challenging task
due to the vast computational resources required. We present Spectrum, a method
that accelerates LLM training by selectively targeting layer modules based on
their signal-to-noise ratio (SNR), and freezing the remaining modules. Our
approach, wh... | 2024-06-07T21:20:57Z | null | null | null | null | null | null | null | null | null | null |
2,406.0689 | Motion Consistency Model: Accelerating Video Diffusion with Disentangled
Motion-Appearance Distillation | ['Yuanhao Zhai', 'Kevin Lin', 'Zhengyuan Yang', 'Linjie Li', 'Jianfeng Wang', 'Chung-Ching Lin', 'David Doermann', 'Junsong Yuan', 'Lijuan Wang'] | ['cs.CV'] | Image diffusion distillation achieves high-fidelity generation with very few
sampling steps. However, applying these techniques directly to video diffusion
often results in unsatisfactory frame quality due to the limited visual quality
in public video datasets. This affects the performance of both teacher and
student v... | 2024-06-11T02:09:46Z | NeurIPS 2024; project page: https://yhzhai.github.io/mcm/ | null | null | Motion Consistency Model: Accelerating Video Diffusion with Disentangled Motion-Appearance Distillation | ['Yuanhao Zhai', 'K. Lin', 'Zhengyuan Yang', 'Linjie Li', 'Jianfeng Wang', 'Chung-Ching Lin', 'David S. Doermann', 'Junsong Yuan', 'Lijuan Wang'] | 2,024 | Neural Information Processing Systems | 13 | 72 | ['Computer Science'] |
2,406.06973 | RWKV-CLIP: A Robust Vision-Language Representation Learner | ['Tiancheng Gu', 'Kaicheng Yang', 'Xiang An', 'Ziyong Feng', 'Dongnan Liu', 'Weidong Cai', 'Jiankang Deng'] | ['cs.CV'] | Contrastive Language-Image Pre-training (CLIP) has significantly improved
performance in various vision-language tasks by expanding the dataset with
image-text pairs obtained from websites. This paper further explores CLIP from
the perspectives of data and model architecture. To address the prevalence of
noisy data and... | 2024-06-11T06:10:46Z | 14 pages, 10 figures, EMNLP2024 Main | null | null | null | null | null | null | null | null | null |
2,406.06992 | Scaling up masked audio encoder learning for general audio
classification | ['Heinrich Dinkel', 'Zhiyong Yan', 'Yongqing Wang', 'Junbo Zhang', 'Yujun Wang', 'Bin Wang'] | ['cs.SD', 'eess.AS'] | Despite progress in audio classification, a generalization gap remains
between speech and other sound domains, such as environmental sounds and music.
Models trained for speech tasks often fail to perform well on environmental or
musical audio tasks, and vice versa. While self-supervised (SSL) audio
representations off... | 2024-06-11T06:44:54Z | Interspeech 2024 | null | null | null | null | null | null | null | null | null |
2,406.07115 | Advancing Tool-Augmented Large Language Models: Integrating Insights
from Errors in Inference Trees | ['Sijia Chen', 'Yibo Wang', 'Yi-Feng Wu', 'Qing-Guo Chen', 'Zhao Xu', 'Weihua Luo', 'Kaifu Zhang', 'Lijun Zhang'] | ['cs.CL', 'cs.AI', 'cs.LG'] | Tool-augmented large language models (LLMs) leverage tools, often in the form
of APIs, to improve their reasoning capabilities on complex tasks. This enables
them to act as intelligent agents interacting with the real world. The recently
introduced ToolLLaMA model by Qin et al. [2023] utilizes the depth-first
search-ba... | 2024-06-11T10:00:18Z | Accepted by NeurIPS 2024 | null | null | Advancing Tool-Augmented Large Language Models: Integrating Insights from Errors in Inference Trees | ['Sijia Chen', 'Yibo Wang', 'Yi-Feng Wu', 'Qing-Guo Chen', 'Zhao Xu', 'Weihua Luo', 'Kaifu Zhang', 'Lijun Zhang'] | 2,024 | Neural Information Processing Systems | 18 | 52 | ['Computer Science'] |
2,406.07188 | Merging Improves Self-Critique Against Jailbreak Attacks | ['Victor Gallego'] | ['cs.CL', 'cs.AI'] | The robustness of large language models (LLMs) against adversarial
manipulations, such as jailbreak attacks, remains a significant challenge. In
this work, we propose an approach that enhances the self-critique capability of
the LLM and further fine-tunes it over sanitized synthetic data. This is done
with the addition... | 2024-06-11T12:01:09Z | Published at ICML 2024 Workshop on Foundation Models in the Wild | null | null | null | null | null | null | null | null | null |
2,406.07209 | MS-Diffusion: Multi-subject Zero-shot Image Personalization with Layout
Guidance | ['Xierui Wang', 'Siming Fu', 'Qihan Huang', 'Wanggui He', 'Hao Jiang'] | ['cs.CV'] | Recent advancements in text-to-image generation models have dramatically
enhanced the generation of photorealistic images from textual prompts, leading
to an increased interest in personalized text-to-image applications,
particularly in multi-subject scenarios. However, these advances are hindered
by two main challenge... | 2024-06-11T12:32:53Z | null | null | null | MS-Diffusion: Multi-subject Zero-shot Image Personalization with Layout Guidance | ['X. Wang', 'Siming Fu', 'Qihan Huang', 'Wanggui He', 'Hao Jiang'] | 2,024 | International Conference on Learning Representations | 53 | 57 | ['Computer Science'] |
2,406.07289 | Can We Achieve High-quality Direct Speech-to-Speech Translation without
Parallel Speech Data? | ['Qingkai Fang', 'Shaolei Zhang', 'Zhengrui Ma', 'Min Zhang', 'Yang Feng'] | ['cs.CL', 'cs.AI', 'cs.SD', 'eess.AS', 'I.2.7'] | Recently proposed two-pass direct speech-to-speech translation (S2ST) models
decompose the task into speech-to-text translation (S2TT) and text-to-speech
(TTS) within an end-to-end model, yielding promising results. However, the
training of these models still relies on parallel speech data, which is
extremely challengi... | 2024-06-11T14:17:12Z | ACL 2024 main conference. Project Page:
https://ictnlp.github.io/ComSpeech-Site/ | null | null | null | null | null | null | null | null | null |
2,406.07394 | Accessing GPT-4 level Mathematical Olympiad Solutions via Monte Carlo
Tree Self-refine with LLaMa-3 8B | ['Di Zhang', 'Xiaoshui Huang', 'Dongzhan Zhou', 'Yuqiang Li', 'Wanli Ouyang'] | ['cs.AI'] | This paper introduces the MCT Self-Refine (MCTSr) algorithm, an innovative
integration of Large Language Models (LLMs) with Monte Carlo Tree Search
(MCTS), designed to enhance performance in complex mathematical reasoning
tasks. Addressing the challenges of accuracy and reliability in LLMs,
particularly in strategic an... | 2024-06-11T16:01:07Z | null | null | null | null | null | null | null | null | null | null |
2,406.07461 | Noise-robust Speech Separation with Fast Generative Correction | ['Helin Wang', 'Jesus Villalba', 'Laureano Moro-Velazquez', 'Jiarui Hai', 'Thomas Thebaud', 'Najim Dehak'] | ['eess.AS'] | Speech separation, the task of isolating multiple speech sources from a mixed
audio signal, remains challenging in noisy environments. In this paper, we
propose a generative correction method to enhance the output of a
discriminative separator. By leveraging a generative corrector based on a
diffusion model, we refine ... | 2024-06-11T17:08:21Z | Accepted at INTERSPEECH 2024 | null | null | null | null | null | null | null | null | null |
2,406.07476 | VideoLLaMA 2: Advancing Spatial-Temporal Modeling and Audio
Understanding in Video-LLMs | ['Zesen Cheng', 'Sicong Leng', 'Hang Zhang', 'Yifei Xin', 'Xin Li', 'Guanzheng Chen', 'Yongxin Zhu', 'Wenqi Zhang', 'Ziyang Luo', 'Deli Zhao', 'Lidong Bing'] | ['cs.CV', 'cs.CL'] | In this paper, we present the VideoLLaMA 2, a set of Video Large Language
Models (Video-LLMs) designed to enhance spatial-temporal modeling and audio
understanding in video and audio-oriented tasks. Building upon its predecessor,
VideoLLaMA 2 incorporates a tailor-made Spatial-Temporal Convolution (STC)
connector, whic... | 2024-06-11T17:22:23Z | ZC, SL, HZ, YX, and XL contributed equally to this project. Code:
https://github.com/DAMO-NLP-SG/VideoLLaMA2 | null | null | null | null | null | null | null | null | null |
2,406.07505 | THaLLE: Text Hyperlocally Augmented Large Language Extension --
Technical Report | ['KBTG Labs', 'Danupat Khamnuansin', 'Atthakorn Petchsod', 'Anuruth Lertpiya', 'Pornchanan Balee', 'Thanawat Lodkaew', 'Tawunrat Chalothorn', 'Thadpong Pongthawornkamol', 'Monchai Lertsutthiwong'] | ['cs.CL'] | Recent advancements in Large Language Models (LLMs) have revealed new
capabilities and opportunities across the technological landscape. However, the
practicality of very large LLMs is challenged by their high compute cost, which
does not justify the benefits given their limited capability compared to
humans. While sma... | 2024-06-11T17:40:00Z | null | null | null | THaLLE: Text Hyperlocally Augmented Large Language Extension - Technical Report | ['Kbtg Labs', 'Danupat Khamnuansin', 'Atthakorn Petchsod', 'Anuruth Lertpiya', 'Pornchanan Balee', 'Thanawat Lodkaew', 'Tawunrat Chalothorn', 'Thadpong Pongthawornkamol', 'Monchai Lertsutthiwong'] | 2,024 | arXiv.org | 1 | 7 | ['Computer Science'] |
2,406.07522 | Samba: Simple Hybrid State Space Models for Efficient Unlimited Context
Language Modeling | ['Liliang Ren', 'Yang Liu', 'Yadong Lu', 'Yelong Shen', 'Chen Liang', 'Weizhu Chen'] | ['cs.CL', 'cs.LG'] | Efficiently modeling sequences with infinite context length has long been a
challenging problem. Previous approaches have either suffered from quadratic
computational complexity or limited extrapolation ability in length
generalization. In this work, we present Samba, a simple hybrid architecture
that layer-wise combin... | 2024-06-11T17:50:51Z | Accepted by ICLR 2025. Camera-ready Version | null | null | null | null | null | null | null | null | null |
2,406.07524 | Simple and Effective Masked Diffusion Language Models | ['Subham Sekhar Sahoo', 'Marianne Arriola', 'Yair Schiff', 'Aaron Gokaslan', 'Edgar Marroquin', 'Justin T Chiu', 'Alexander Rush', 'Volodymyr Kuleshov'] | ['cs.CL', 'cs.AI', 'cs.LG'] | While diffusion models excel at generating high-quality images, prior work
reports a significant performance gap between diffusion and autoregressive (AR)
methods in language modeling. In this work, we show that simple masked discrete
diffusion is more performant than previously thought. We apply an effective
training ... | 2024-06-11T17:51:40Z | NeurIPS 2024. We provide the code at
https://github.com/kuleshov-group/mdlm | null | null | null | null | null | null | null | null | null |
2,406.07543 | Vision Model Pre-training on Interleaved Image-Text Data via Latent
Compression Learning | ['Chenyu Yang', 'Xizhou Zhu', 'Jinguo Zhu', 'Weijie Su', 'Junjie Wang', 'Xuan Dong', 'Wenhai Wang', 'Lewei Lu', 'Bin Li', 'Jie Zhou', 'Yu Qiao', 'Jifeng Dai'] | ['cs.CV'] | Recently, vision model pre-training has evolved from relying on manually
annotated datasets to leveraging large-scale, web-crawled image-text data.
Despite these advances, there is no pre-training method that effectively
exploits the interleaved image-text data, which is very prevalent on the
Internet. Inspired by the ... | 2024-06-11T17:59:35Z | null | null | null | null | null | null | null | null | null | null |
2,406.07547 | Zero-shot Image Editing with Reference Imitation | ['Xi Chen', 'Yutong Feng', 'Mengting Chen', 'Yiyang Wang', 'Shilong Zhang', 'Yu Liu', 'Yujun Shen', 'Hengshuang Zhao'] | ['cs.CV'] | Image editing serves as a practical yet challenging task considering the
diverse demands from users, where one of the hardest parts is to precisely
describe how the edited image should look like. In this work, we present a new
form of editing, termed imitative editing, to help users exercise their
creativity more conve... | 2024-06-11T17:59:51Z | https://xavierchen34.github.io/MimicBrush-Page | null | null | null | null | null | null | null | null | null |
2,406.0755 | An Image is Worth 32 Tokens for Reconstruction and Generation | ['Qihang Yu', 'Mark Weber', 'Xueqing Deng', 'Xiaohui Shen', 'Daniel Cremers', 'Liang-Chieh Chen'] | ['cs.CV'] | Recent advancements in generative models have highlighted the crucial role of
image tokenization in the efficient synthesis of high-resolution images.
Tokenization, which transforms images into latent representations, reduces
computational demands compared to directly processing pixels and enhances the
effectiveness an... | 2024-06-11T17:59:56Z | A compact 1D Image Tokenization method, leading to SOTA generation
performance while being substantially faster. Project page at
https://yucornetto.github.io/projects/titok.html | null | null | null | null | null | null | null | null | null |
2,406.07599 | CTIBench: A Benchmark for Evaluating LLMs in Cyber Threat Intelligence | ['Md Tanvirul Alam', 'Dipkamal Bhusal', 'Le Nguyen', 'Nidhi Rastogi'] | ['cs.CR', 'cs.AI'] | Cyber threat intelligence (CTI) is crucial in today's cybersecurity
landscape, providing essential insights to understand and mitigate the
ever-evolving cyber threats. The recent rise of Large Language Models (LLMs)
have shown potential in this domain, but concerns about their reliability,
accuracy, and hallucinations ... | 2024-06-11T16:42:02Z | null | null | null | CTIBench: A Benchmark for Evaluating LLMs in Cyber Threat Intelligence | ['Md Tanvirul Alam', 'Dipkamal Bhusal', 'Le Nguyen', 'Nidhi Rastogi'] | 2,024 | Neural Information Processing Systems | 22 | 50 | ['Computer Science'] |
2,406.07815 | Are Large Language Models Good Statisticians? | ['Yizhang Zhu', 'Shiyin Du', 'Boyan Li', 'Yuyu Luo', 'Nan Tang'] | ['cs.CL', 'cs.AI'] | Large Language Models (LLMs) have demonstrated impressive capabilities across
a range of scientific tasks including mathematics, physics, and chemistry.
Despite their successes, the effectiveness of LLMs in handling complex
statistical tasks remains systematically under-explored. To bridge this gap, we
introduce StatQA... | 2024-06-12T02:23:51Z | Accepted by NeurIPS 2024 D&B. 34 pages, 11 figures, 21 tables | null | null | null | null | null | null | null | null | null |
2,406.07835 | SciRIFF: A Resource to Enhance Language Model Instruction-Following over
Scientific Literature | ['David Wadden', 'Kejian Shi', 'Jacob Morrison', 'Aakanksha Naik', 'Shruti Singh', 'Nitzan Barzilay', 'Kyle Lo', 'Tom Hope', 'Luca Soldaini', 'Shannon Zejiang Shen', 'Doug Downey', 'Hannaneh Hajishirzi', 'Arman Cohan'] | ['cs.CL', 'cs.AI'] | We present SciRIFF (Scientific Resource for Instruction-Following and
Finetuning), a dataset of 137K instruction-following demonstrations for 54
tasks covering five essential scientific literature understanding capabilities:
information extraction, summarization, question answering, claim verification,
and classificati... | 2024-06-10T21:22:08Z | Submitted to NeurIPS Datasets and Benchmarks 2024 | null | null | null | null | null | null | null | null | null |
2,406.07887 | An Empirical Study of Mamba-based Language Models | ['Roger Waleffe', 'Wonmin Byeon', 'Duncan Riach', 'Brandon Norick', 'Vijay Korthikanti', 'Tri Dao', 'Albert Gu', 'Ali Hatamizadeh', 'Sudhakar Singh', 'Deepak Narayanan', 'Garvit Kulshreshtha', 'Vartika Singh', 'Jared Casper', 'Jan Kautz', 'Mohammad Shoeybi', 'Bryan Catanzaro'] | ['cs.LG', 'cs.CL'] | Selective state-space models (SSMs) like Mamba overcome some of the
shortcomings of Transformers, such as quadratic computational complexity with
sequence length and large inference-time memory requirements from the key-value
cache. Moreover, recent studies have shown that SSMs can match or exceed the
language modeling... | 2024-06-12T05:25:15Z | null | null | null | An Empirical Study of Mamba-based Language Models | ['R. Waleffe', 'Wonmin Byeon', 'Duncan Riach', 'Brandon Norick', 'V. Korthikanti', 'Tri Dao', 'Albert Gu', 'Ali Hatamizadeh', 'Sudhakar Singh', 'Deepak Narayanan', 'Garvit Kulshreshtha', 'Vartika Singh', 'J. Casper', 'Jan Kautz', 'M. Shoeybi', 'Bryan Catanzaro'] | 2,024 | arXiv.org | 79 | 53 | ['Computer Science'] |
2,406.08055 | Learning Job Title Representation from Job Description Aggregation
Network | ['Napat Laosaengpha', 'Thanit Tativannarat', 'Chawan Piansaddhayanon', 'Attapol Rutherford', 'Ekapol Chuangsuwanich'] | ['cs.CL'] | Learning job title representation is a vital process for developing automatic
human resource tools. To do so, existing methods primarily rely on learning the
title representation through skills extracted from the job description,
neglecting the rich and diverse content within. Thus, we propose an alternative
framework ... | 2024-06-12T10:12:52Z | to be published in Findings of the Association for Computational
Linguistics: ACL 2024 | null | null | Learning Job Title Representation from Job Description Aggregation Network | ['Napat Laosaengpha', 'Thanit Tativannarat', 'Chawan Piansaddhayanon', 'Attapol Rutherford', 'Ekapol Chuangsuwanich'] | 2,024 | Annual Meeting of the Association for Computational Linguistics | 1 | 31 | ['Computer Science'] |
2,406.08085 | Flash-VStream: Memory-Based Real-Time Understanding for Long Video
Streams | ['Haoji Zhang', 'Yiqin Wang', 'Yansong Tang', 'Yong Liu', 'Jiashi Feng', 'Jifeng Dai', 'Xiaojie Jin'] | ['cs.CV'] | Benefiting from the advancements in large language models and cross-modal
alignment, existing multi-modal video understanding methods have achieved
prominent performance in offline scenario. However, online video streams, as
one of the most common media forms in the real world, have seldom received
attention. Compared ... | 2024-06-12T11:07:55Z | null | null | null | Flash-VStream: Memory-Based Real-Time Understanding for Long Video Streams | ['Haoji Zhang', 'Yiqin Wang', 'Yansong Tang', 'Yong Liu', 'Jiashi Feng', 'Jifeng Dai', 'Xiaojie Jin'] | 2,024 | arXiv.org | 45 | 50 | ['Computer Science'] |
2,406.081 | Multimodal Table Understanding | ['Mingyu Zheng', 'Xinwei Feng', 'Qingyi Si', 'Qiaoqiao She', 'Zheng Lin', 'Wenbin Jiang', 'Weiping Wang'] | ['cs.CL', 'cs.AI'] | Although great progress has been made by previous table understanding methods
including recent approaches based on large language models (LLMs), they rely
heavily on the premise that given tables must be converted into a certain text
sequence (such as Markdown or HTML) to serve as model input. However, it is
difficult ... | 2024-06-12T11:27:03Z | 23 pages, 16 figures, ACL 2024 main conference, camera-ready version | null | null | Multimodal Table Understanding | ['Mingyu Zheng', 'Xinwei Feng', 'Q. Si', 'Qiaoqiao She', 'Zheng Lin', 'Wenbin Jiang', 'Weiping Wang'] | 2,024 | Annual Meeting of the Association for Computational Linguistics | 20 | 60 | ['Computer Science'] |
2,406.08164 | ConMe: Rethinking Evaluation of Compositional Reasoning for Modern VLMs | ['Irene Huang', 'Wei Lin', 'M. Jehanzeb Mirza', 'Jacob A. Hansen', 'Sivan Doveh', 'Victor Ion Butoi', 'Roei Herzig', 'Assaf Arbelle', 'Hilde Kuehne', 'Trevor Darrell', 'Chuang Gan', 'Aude Oliva', 'Rogerio Feris', 'Leonid Karlinsky'] | ['cs.CV'] | Compositional Reasoning (CR) entails grasping the significance of attributes,
relations, and word order. Recent Vision-Language Models (VLMs), comprising a
visual encoder and a Large Language Model (LLM) decoder, have demonstrated
remarkable proficiency in such reasoning tasks. This prompts a crucial
question: have VLM... | 2024-06-12T12:54:27Z | NeurIPS 2024 Camera Ready | null | null | ConMe: Rethinking Evaluation of Compositional Reasoning for Modern VLMs | ['Irene Huang', 'Wei Lin', 'M. J. Mirza', 'Jacob Hansen', 'Sivan Doveh', 'V. Butoi', 'Roei Herzig', 'Assaf Arbelle', 'Hilde Kuhene', 'Trevor Darrel', 'Chuang Gan', 'Aude Oliva', 'Rogério Feris', 'Leonid Karlinsky'] | 2,024 | Neural Information Processing Systems | 9 | 64 | ['Computer Science'] |
2,406.0831 | GraphFM: A Comprehensive Benchmark for Graph Foundation Model | ['Yuhao Xu', 'Xinqi Liu', 'Keyu Duan', 'Yi Fang', 'Yu-Neng Chuang', 'Daochen Zha', 'Qiaoyu Tan'] | ['cs.LG'] | Foundation Models (FMs) serve as a general class for the development of
artificial intelligence systems, offering broad potential for generalization
across a spectrum of downstream tasks. Despite extensive research into
self-supervised learning as the cornerstone of FMs, several outstanding issues
persist in Graph Foun... | 2024-06-12T15:10:44Z | null | null | null | null | null | null | null | null | null | null |
2,406.08391 | Large Language Models Must Be Taught to Know What They Don't Know | ['Sanyam Kapoor', 'Nate Gruver', 'Manley Roberts', 'Katherine Collins', 'Arka Pal', 'Umang Bhatt', 'Adrian Weller', 'Samuel Dooley', 'Micah Goldblum', 'Andrew Gordon Wilson'] | ['cs.LG', 'cs.AI', 'cs.CL', 'stat.ML'] | When using large language models (LLMs) in high-stakes applications, we need
to know when we can trust their predictions. Some works argue that prompting
high-performance LLMs is sufficient to produce calibrated uncertainties, while
others introduce sampling methods that can be prohibitively expensive. In this
work, we... | 2024-06-12T16:41:31Z | NeurIPS 2024 Camera Ready | null | null | null | null | null | null | null | null | null |
2,406.08414 | Discovering Preference Optimization Algorithms with and for Large
Language Models | ['Chris Lu', 'Samuel Holt', 'Claudio Fanconi', 'Alex J. Chan', 'Jakob Foerster', 'Mihaela van der Schaar', 'Robert Tjarko Lange'] | ['cs.LG'] | Offline preference optimization is a key method for enhancing and controlling
the quality of Large Language Model (LLM) outputs. Typically, preference
optimization is approached as an offline supervised learning task using
manually-crafted convex loss functions. While these methods are based on
theoretical insights, th... | 2024-06-12T16:58:41Z | null | null | null | Discovering Preference Optimization Algorithms with and for Large Language Models | ['Chris Lu', 'Samuel Holt', 'Claudio Fanconi', 'Alex J. Chan', 'J. Foerster', 'M. Schaar', 'R. T. Lange'] | 2,024 | Neural Information Processing Systems | 18 | 84 | ['Computer Science'] |
2,406.08418 | OmniCorpus: A Unified Multimodal Corpus of 10 Billion-Level Images
Interleaved with Text | ['Qingyun Li', 'Zhe Chen', 'Weiyun Wang', 'Wenhai Wang', 'Shenglong Ye', 'Zhenjiang Jin', 'Guanzhou Chen', 'Yinan He', 'Zhangwei Gao', 'Erfei Cui', 'Jiashuo Yu', 'Hao Tian', 'Jiasheng Zhou', 'Chao Xu', 'Bin Wang', 'Xingjian Wei', 'Wei Li', 'Wenjian Zhang', 'Bo Zhang', 'Pinlong Cai', 'Licheng Wen', 'Xiangchao Yan', 'Zhe... | ['cs.CV', 'cs.AI'] | Image-text interleaved data, consisting of multiple images and texts arranged
in a natural document format, aligns with the presentation paradigm of internet
data and closely resembles human reading habits. Recent studies have shown that
such data aids multimodal in-context learning and maintains the capabilities of
la... | 2024-06-12T17:01:04Z | null | null | null | null | null | null | null | null | null | null |
2,406.08446 | OLMES: A Standard for Language Model Evaluations | ['Yuling Gu', 'Oyvind Tafjord', 'Bailey Kuehl', 'Dany Haddad', 'Jesse Dodge', 'Hannaneh Hajishirzi'] | ['cs.CL', 'cs.AI'] | Progress in AI is often demonstrated by new models claiming improved
performance on tasks measuring model capabilities. Evaluating language models
can be particularly challenging, as choices of how a model is evaluated on a
task can lead to large changes in measured performance. There is no common
standard setup, so di... | 2024-06-12T17:37:09Z | Findings of NAACL 2025 | null | null | OLMES: A Standard for Language Model Evaluations | ['Yuling Gu', 'Oyvind Tafjord', 'Bailey Kuehl', 'Dany Haddad', 'Jesse Dodge', 'Hanna Hajishirzi'] | 2,024 | North American Chapter of the Association for Computational Linguistics | 20 | 50 | ['Computer Science'] |
2,406.08464 | Magpie: Alignment Data Synthesis from Scratch by Prompting Aligned LLMs
with Nothing | ['Zhangchen Xu', 'Fengqing Jiang', 'Luyao Niu', 'Yuntian Deng', 'Radha Poovendran', 'Yejin Choi', 'Bill Yuchen Lin'] | ['cs.CL', 'cs.AI'] | High-quality instruction data is critical for aligning large language models
(LLMs). Although some models, such as Llama-3-Instruct, have open weights,
their alignment data remain private, which hinders the democratization of AI.
High human labor costs and a limited, predefined scope for prompting prevent
existing open... | 2024-06-12T17:52:30Z | Link: https://magpie-align.github.io/ | null | null | null | null | null | null | null | null | null |
2,406.08478 | What If We Recaption Billions of Web Images with LLaMA-3? | ['Xianhang Li', 'Haoqin Tu', 'Mude Hui', 'Zeyu Wang', 'Bingchen Zhao', 'Junfei Xiao', 'Sucheng Ren', 'Jieru Mei', 'Qing Liu', 'Huangjie Zheng', 'Yuyin Zhou', 'Cihang Xie'] | ['cs.CV', 'cs.CL'] | Web-crawled image-text pairs are inherently noisy. Prior studies demonstrate
that semantically aligning and enriching textual descriptions of these pairs
can significantly enhance model training across various vision-language tasks,
particularly text-to-image generation. However, large-scale investigations in
this area... | 2024-06-12T17:59:07Z | First five authors contributed equally | null | null | null | null | null | null | null | null | null |
2,406.08479 | Real3D: Scaling Up Large Reconstruction Models with Real-World Images | ['Hanwen Jiang', 'Qixing Huang', 'Georgios Pavlakos'] | ['cs.CV'] | The default strategy for training single-view Large Reconstruction Models
(LRMs) follows the fully supervised route using large-scale datasets of
synthetic 3D assets or multi-view captures. Although these resources simplify
the training procedure, they are hard to scale up beyond the existing datasets
and they are not ... | 2024-06-12T17:59:08Z | Project page: https://hwjiang1510.github.io/Real3D/ | null | null | null | null | null | null | null | null | null |
2,406.08487 | Beyond LLaVA-HD: Diving into High-Resolution Large Multimodal Models | ['Yi-Fan Zhang', 'Qingsong Wen', 'Chaoyou Fu', 'Xue Wang', 'Zhang Zhang', 'Liang Wang', 'Rong Jin'] | ['cs.CV'] | Seeing clearly with high resolution is a foundation of Large Multimodal
Models (LMMs), which has been proven to be vital for visual perception and
reasoning. Existing works usually employ a straightforward resolution upscaling
method, where the image consists of global and local branches, with the latter
being the slic... | 2024-06-12T17:59:49Z | Project page: https://github.com/yfzhang114/SliME | null | null | null | null | null | null | null | null | null |
2,406.08657 | Mistral-C2F: Coarse to Fine Actor for Analytical and Reasoning
Enhancement in RLHF and Effective-Merged LLMs | ['Chen Zheng', 'Ke Sun', 'Xun Zhou'] | ['cs.CL'] | Despite the advances in Large Language Models (LLMs), exemplified by models
like GPT-4 and Claude, smaller-scale LLMs such as Llama and Mistral often
struggle with generating in-depth and coherent dialogues. This paper presents a
novel two-step Coarse-to-Fine Actor model to address the inherent limitations
in conversat... | 2024-06-12T21:42:13Z | null | null | null | null | null | null | null | null | null | null |
2,406.08673 | HelpSteer2: Open-source dataset for training top-performing reward
models | ['Zhilin Wang', 'Yi Dong', 'Olivier Delalleau', 'Jiaqi Zeng', 'Gerald Shen', 'Daniel Egert', 'Jimmy J. Zhang', 'Makesh Narsimhan Sreedhar', 'Oleksii Kuchaiev'] | ['cs.CL', 'cs.AI', 'cs.LG'] | High-quality preference datasets are essential for training reward models
that can effectively guide large language models (LLMs) in generating
high-quality responses aligned with human preferences. As LLMs become stronger
and better aligned, permissively licensed preference datasets, such as Open
Assistant, HH-RLHF, a... | 2024-06-12T22:28:08Z | null | null | null | null | null | null | null | null | null | null |
2,406.08707 | mOSCAR: A Large-scale Multilingual and Multimodal Document-level Corpus | ['Matthieu Futeral', 'Armel Zebaze', 'Pedro Ortiz Suarez', 'Julien Abadji', 'Rémi Lacroix', 'Cordelia Schmid', 'Rachel Bawden', 'Benoît Sagot'] | ['cs.CL', 'cs.CV'] | Multimodal Large Language Models (mLLMs) are trained on a large amount of
text-image data. While most mLLMs are trained on caption-like data only,
Alayrac et al. (2022) showed that additionally training them on interleaved
sequences of text and images can lead to the emergence of in-context learning
capabilities. Howev... | 2024-06-13T00:13:32Z | ACL 2025 (Findings) | null | null | mOSCAR: A Large-scale Multilingual and Multimodal Document-level Corpus | ['Matthieu Futeral', 'A. Zebaze', 'Pedro Ortiz Suarez', 'Julien Abadji', "R'emi Lacroix", 'Cordelia Schmid', 'Rachel Bawden', 'Benoît Sagot'] | 2,024 | arXiv.org | 3 | 107 | ['Computer Science'] |
2,406.08801 | Hallo: Hierarchical Audio-Driven Visual Synthesis for Portrait Image
Animation | ['Mingwang Xu', 'Hui Li', 'Qingkun Su', 'Hanlin Shang', 'Liwei Zhang', 'Ce Liu', 'Jingdong Wang', 'Yao Yao', 'Siyu Zhu'] | ['cs.CV'] | The field of portrait image animation, driven by speech audio input, has
experienced significant advancements in the generation of realistic and dynamic
portraits. This research delves into the complexities of synchronizing facial
movements and creating visually appealing, temporally consistent animations
within the fr... | 2024-06-13T04:33:20Z | 20 pages | null | null | Hallo: Hierarchical Audio-Driven Visual Synthesis for Portrait Image Animation | ['Mingwang Xu', 'Hui Li', 'Qingkun Su', 'Hanlin Shang', 'Liwei Zhang', 'Ce Liu', 'Jingdong Wang', 'Yao Yao', 'Siyu Zhu'] | 2,024 | arXiv.org | 90 | 54 | ['Computer Science'] |
2,406.08845 | Rethinking Human Evaluation Protocol for Text-to-Video Models: Enhancing
Reliability,Reproducibility, and Practicality | ['Tianle Zhang', 'Langtian Ma', 'Yuchen Yan', 'Yuchen Zhang', 'Kai Wang', 'Yue Yang', 'Ziyao Guo', 'Wenqi Shao', 'Yang You', 'Yu Qiao', 'Ping Luo', 'Kaipeng Zhang'] | ['cs.CV'] | Recent text-to-video (T2V) technology advancements, as demonstrated by models
such as Gen2, Pika, and Sora, have significantly broadened its applicability
and popularity. Despite these strides, evaluating these models poses
substantial challenges. Primarily, due to the limitations inherent in automatic
metrics, manual ... | 2024-06-13T06:09:22Z | null | null | null | Rethinking Human Evaluation Protocol for Text-to-Video Models: Enhancing Reliability, Reproducibility, and Practicality | ['Tianle Zhang', 'Langtian Ma', 'Yuchen Yan', 'Yuchen Zhang', 'Kai Wang', 'Yue Yang', 'Ziyao Guo', 'Wenqi Shao', 'Yang You', 'Yu Qiao', 'Ping Luo', 'Kaipeng Zhang'] | 2,024 | Neural Information Processing Systems | 2 | 131 | ['Computer Science'] |
2,406.0914 | Investigating the translation capabilities of Large Language Models
trained on parallel data only | ['Javier García Gilabert', 'Carlos Escolano', 'Aleix Sant Savall', 'Francesca De Luca Fornaciari', 'Audrey Mash', 'Xixian Liao', 'Maite Melero'] | ['cs.CL'] | In recent years, Large Language Models (LLMs) have demonstrated exceptional
proficiency across a broad spectrum of Natural Language Processing (NLP) tasks,
including Machine Translation. However, previous methods predominantly relied
on iterative processes such as instruction fine-tuning or continual
pre-training, leav... | 2024-06-13T14:08:56Z | We release our code at: https://github.com/projecte-aina/Plume | null | null | null | null | null | null | null | null | null |
2,406.09168 | SR-CACO-2: A Dataset for Confocal Fluorescence Microscopy Image
Super-Resolution | ['Soufiane Belharbi', 'Mara KM Whitford', 'Phuong Hoang', 'Shakeeb Murtaza', 'Luke McCaffrey', 'Eric Granger'] | ['eess.IV', 'cs.CV', 'cs.LG'] | Confocal fluorescence microscopy is one of the most accessible and widely
used imaging techniques for the study of biological processes at the cellular
and subcellular levels. Scanning confocal microscopy allows the capture of
high-quality images from thick three-dimensional (3D) samples, yet suffers from
well-known li... | 2024-06-13T14:30:35Z | 27 pages, 15 figures, NeurIPS 2024 | null | null | null | null | null | null | null | null | null |
2,406.09246 | OpenVLA: An Open-Source Vision-Language-Action Model | ['Moo Jin Kim', 'Karl Pertsch', 'Siddharth Karamcheti', 'Ted Xiao', 'Ashwin Balakrishna', 'Suraj Nair', 'Rafael Rafailov', 'Ethan Foster', 'Grace Lam', 'Pannag Sanketi', 'Quan Vuong', 'Thomas Kollar', 'Benjamin Burchfiel', 'Russ Tedrake', 'Dorsa Sadigh', 'Sergey Levine', 'Percy Liang', 'Chelsea Finn'] | ['cs.RO', 'cs.LG'] | Large policies pretrained on a combination of Internet-scale vision-language
data and diverse robot demonstrations have the potential to change how we teach
robots new skills: rather than training new behaviors from scratch, we can
fine-tune such vision-language-action (VLA) models to obtain robust,
generalizable polic... | 2024-06-13T15:46:55Z | Website: https://openvla.github.io/ | null | null | OpenVLA: An Open-Source Vision-Language-Action Model | ['Moo Jin Kim', 'Karl Pertsch', 'Siddharth Karamcheti', 'Ted Xiao', 'A. Balakrishna', 'Suraj Nair', 'Rafael Rafailov', 'Ethan Foster', 'Grace Lam', 'Pannag R. Sanketi', 'Quan Vuong', 'Thomas Kollar', 'Benjamin Burchfiel', 'Russ Tedrake', 'Dorsa Sadigh', 'Sergey Levine', 'Percy Liang', 'Chelsea Finn'] | 2,024 | Conference on Robot Learning | 535 | 110 | ['Computer Science'] |
2,406.09279 | Unpacking DPO and PPO: Disentangling Best Practices for Learning from
Preference Feedback | ['Hamish Ivison', 'Yizhong Wang', 'Jiacheng Liu', 'Zeqiu Wu', 'Valentina Pyatkin', 'Nathan Lambert', 'Noah A. Smith', 'Yejin Choi', 'Hannaneh Hajishirzi'] | ['cs.CL'] | Learning from preference feedback has emerged as an essential step for
improving the generation quality and performance of modern language models
(LMs). Despite its widespread use, the way preference-based learning is applied
varies wildly, with differing data, learning algorithms, and evaluations used,
making disentan... | 2024-06-13T16:17:21Z | Neurips 2024 camera-ready | null | null | Unpacking DPO and PPO: Disentangling Best Practices for Learning from Preference Feedback | ['Hamish Ivison', 'Yizhong Wang', 'Jiacheng Liu', 'Zeqiu Wu', 'Valentina Pyatkin', 'Nathan Lambert', 'Noah A. Smith', 'Yejin Choi', 'Hanna Hajishirzi'] | 2,024 | Neural Information Processing Systems | 64 | 55 | ['Computer Science'] |
2,406.09282 | On the Effects of Heterogeneous Data Sources on Speech-to-Text
Foundation Models | ['Jinchuan Tian', 'Yifan Peng', 'William Chen', 'Kwanghee Choi', 'Karen Livescu', 'Shinji Watanabe'] | ['cs.CL', 'cs.SD', 'eess.AS'] | The Open Whisper-style Speech Model (OWSM) series was introduced to achieve
full transparency in building advanced speech-to-text (S2T) foundation models.
To this end, OWSM models are trained on 25 public speech datasets, which are
heterogeneous in multiple ways. In this study, we advance the OWSM series by
introducing... | 2024-06-13T16:22:37Z | null | null | null | null | null | null | null | null | null | null |
2,406.09293 | StableMaterials: Enhancing Diversity in Material Generation via
Semi-Supervised Learning | ['Giuseppe Vecchio'] | ['cs.CV', 'cs.GR'] | We introduce StableMaterials, a novel approach for generating photorealistic
physical-based rendering (PBR) materials that integrate semi-supervised
learning with Latent Diffusion Models (LDMs). Our method employs adversarial
training to distill knowledge from existing large-scale image generation
models, minimizing th... | 2024-06-13T16:29:46Z | null | null | null | null | null | null | null | null | null | null |
2,406.09326 | PianoMotion10M: Dataset and Benchmark for Hand Motion Generation in
Piano Performance | ['Qijun Gan', 'Song Wang', 'Shengtao Wu', 'Jianke Zhu'] | ['cs.SD', 'cs.AI', 'cs.CV', 'cs.MM', 'eess.AS'] | Recently, artificial intelligence techniques for education have been received
increasing attentions, while it still remains an open problem to design the
effective music instrument instructing systems. Although key presses can be
directly derived from sheet music, the transitional movements among key presses
require mo... | 2024-06-13T17:05:23Z | ICLR 2025 Spotlight | null | null | PianoMotion10M: Dataset and Benchmark for Hand Motion Generation in Piano Performance | ['Qijun Gan', 'Song Wang', 'Shengtao Wu', 'Jianke Zhu'] | 2,024 | International Conference on Learning Representations | 1 | 92 | ['Computer Science', 'Engineering'] |
2,406.09367 | Needle In A Video Haystack: A Scalable Synthetic Evaluator for Video
MLLMs | ['Zijia Zhao', 'Haoyu Lu', 'Yuqi Huo', 'Yifan Du', 'Tongtian Yue', 'Longteng Guo', 'Bingning Wang', 'Weipeng Chen', 'Jing Liu'] | ['cs.CV'] | Video understanding is a crucial next step for multimodal large language
models (MLLMs). Various benchmarks are introduced for better evaluating the
MLLMs. Nevertheless, current video benchmarks are still inefficient for
evaluating video models during iterative development due to the high cost of
constructing datasets ... | 2024-06-13T17:50:05Z | ICLR 2025 | null | null | Needle In A Video Haystack: A Scalable Synthetic Evaluator for Video MLLMs | ['Zijia Zhao', 'Haoyu Lu', 'Yuqi Huo', 'Yifan Du', 'Tongtian Yue', 'Longteng Guo', 'Bingning Wang', 'Weipeng Chen', 'Jing Liu'] | 2,024 | International Conference on Learning Representations | 5 | 55 | ['Computer Science'] |
2,406.09396 | Too Many Frames, Not All Useful: Efficient Strategies for Long-Form
Video QA | ['Jongwoo Park', 'Kanchana Ranasinghe', 'Kumara Kahatapitiya', 'Wonjeong Ryu', 'Donghyun Kim', 'Michael S. Ryoo'] | ['cs.CV'] | Long-form videos that span across wide temporal intervals are highly
information redundant and contain multiple distinct events or entities that are
often loosely related. Therefore, when performing long-form video question
answering (LVQA), all information necessary to generate a correct response can
often be containe... | 2024-06-13T17:59:16Z | null | null | null | null | null | null | null | null | null | null |
2,406.09406 | 4M-21: An Any-to-Any Vision Model for Tens of Tasks and Modalities | ['Roman Bachmann', 'Oğuzhan Fatih Kar', 'David Mizrahi', 'Ali Garjani', 'Mingfei Gao', 'David Griffiths', 'Jiaming Hu', 'Afshin Dehghan', 'Amir Zamir'] | ['cs.CV', 'cs.AI', 'cs.LG'] | Current multimodal and multitask foundation models like 4M or UnifiedIO show
promising results, but in practice their out-of-the-box abilities to accept
diverse inputs and perform diverse tasks are limited by the (usually rather
small) number of modalities and tasks they are trained on. In this paper, we
expand upon th... | 2024-06-13T17:59:42Z | Project page at 4m.epfl.ch | null | null | null | null | null | null | null | null | null |
2,406.09412 | Explore the Limits of Omni-modal Pretraining at Scale | ['Yiyuan Zhang', 'Handong Li', 'Jing Liu', 'Xiangyu Yue'] | ['cs.CV', 'cs.AI', 'cs.LG', 'cs.MM'] | We propose to build omni-modal intelligence, which is capable of
understanding any modality and learning universal representations. In specific,
we propose a scalable pretraining paradigm, named Multimodal Context (MiCo),
which can scale up the numbers of modalities and amount of data, together with
the model parameter... | 2024-06-13T17:59:53Z | Project Website: https://invictus717.github.io/MiCo/ | null | null | null | null | null | null | null | null | null |
2,406.09413 | Interpreting the Weight Space of Customized Diffusion Models | ['Amil Dravid', 'Yossi Gandelsman', 'Kuan-Chieh Wang', 'Rameen Abdal', 'Gordon Wetzstein', 'Alexei A. Efros', 'Kfir Aberman'] | ['cs.CV', 'cs.GR', 'cs.LG'] | We investigate the space of weights spanned by a large collection of
customized diffusion models. We populate this space by creating a dataset of
over 60,000 models, each of which is a base model fine-tuned to insert a
different person's visual identity. We model the underlying manifold of these
weights as a subspace, ... | 2024-06-13T17:59:56Z | Project Page: https://snap-research.github.io/weights2weights | null | null | Interpreting the Weight Space of Customized Diffusion Models | ['Amil Dravid', 'Yossi Gandelsman', 'Kuan-Chieh Jackson Wang', 'Rameen Abdal', 'Gordon Wetzstein', 'Alexei A. Efros', 'Kfir Aberman'] | 2,024 | Neural Information Processing Systems | 12 | 80 | ['Computer Science'] |
2,406.09414 | Depth Anything V2 | ['Lihe Yang', 'Bingyi Kang', 'Zilong Huang', 'Zhen Zhao', 'Xiaogang Xu', 'Jiashi Feng', 'Hengshuang Zhao'] | ['cs.CV'] | This work presents Depth Anything V2. Without pursuing fancy techniques, we
aim to reveal crucial findings to pave the way towards building a powerful
monocular depth estimation model. Notably, compared with V1, this version
produces much finer and more robust depth predictions through three key
practices: 1) replacing... | 2024-06-13T17:59:56Z | Accepted by NeurIPS 2024. Project page:
https://depth-anything-v2.github.io | null | null | null | null | null | null | null | null | null |
2,406.09418 | VideoGPT+: Integrating Image and Video Encoders for Enhanced Video
Understanding | ['Muhammad Maaz', 'Hanoona Rasheed', 'Salman Khan', 'Fahad Khan'] | ['cs.CV'] | Building on the advances of language models, Large Multimodal Models (LMMs)
have contributed significant improvements in video understanding. While the
current video LMMs utilize advanced Large Language Models (LLMs), they rely on
either image or video encoders to process visual inputs, each of which has its
own limita... | 2024-06-13T17:59:59Z | Technical Report | null | null | null | null | null | null | null | null | null |
2,406.09455 | Pandora: Towards General World Model with Natural Language Actions and
Video States | ['Jiannan Xiang', 'Guangyi Liu', 'Yi Gu', 'Qiyue Gao', 'Yuting Ning', 'Yuheng Zha', 'Zeyu Feng', 'Tianhua Tao', 'Shibo Hao', 'Yemin Shi', 'Zhengzhong Liu', 'Eric P. Xing', 'Zhiting Hu'] | ['cs.CV', 'cs.AI', 'cs.CL'] | World models simulate future states of the world in response to different
actions. They facilitate interactive content creation and provides a foundation
for grounded, long-horizon reasoning. Current foundation models do not fully
meet the capabilities of general world models: large language models (LLMs) are
constrain... | 2024-06-12T18:55:51Z | Website: https://world-model.maitrix.org/ | null | null | null | null | null | null | null | null | null |
2,406.0949 | Newswire: A Large-Scale Structured Database of a Century of Historical
News | ['Emily Silcock', 'Abhishek Arora', "Luca D'Amico-Wong", 'Melissa Dell'] | ['cs.CL', 'econ.GN', 'q-fin.EC'] | In the U.S. historically, local newspapers drew their content largely from
newswires like the Associated Press. Historians argue that newswires played a
pivotal role in creating a national identity and shared understanding of the
world, but there is no comprehensive archive of the content sent over
newswires. We recons... | 2024-06-13T16:20:05Z | arXiv admin note: text overlap with arXiv:2306.17810,
arXiv:2308.12477 | null | null | null | null | null | null | null | null | null |
2,406.09627 | RobustSAM: Segment Anything Robustly on Degraded Images | ['Wei-Ting Chen', 'Yu-Jiet Vong', 'Sy-Yen Kuo', 'Sizhuo Ma', 'Jian Wang'] | ['cs.CV', 'cs.AI', 'eess.IV'] | Segment Anything Model (SAM) has emerged as a transformative approach in
image segmentation, acclaimed for its robust zero-shot segmentation
capabilities and flexible prompting system. Nonetheless, its performance is
challenged by images with degraded quality. Addressing this limitation, we
propose the Robust Segment A... | 2024-06-13T23:33:59Z | Accepted by CVPR2024 (Highlight); Project Page:
https://robustsam.github.io/ | null | null | null | null | null | null | null | null | null |
2,406.09756 | Grounding Image Matching in 3D with MASt3R | ['Vincent Leroy', 'Yohann Cabon', 'Jérôme Revaud'] | ['cs.CV'] | Image Matching is a core component of all best-performing algorithms and
pipelines in 3D vision. Yet despite matching being fundamentally a 3D problem,
intrinsically linked to camera pose and scene geometry, it is typically treated
as a 2D problem. This makes sense as the goal of matching is to establish
correspondence... | 2024-06-14T06:46:30Z | null | null | null | Grounding Image Matching in 3D with MASt3R | ['Vincent Leroy', 'Yohann Cabon', 'Jérôme Revaud'] | 2,024 | European Conference on Computer Vision | 164 | 114 | ['Computer Science'] |
2,406.0976 | Bootstrapping Language Models with DPO Implicit Rewards | ['Changyu Chen', 'Zichen Liu', 'Chao Du', 'Tianyu Pang', 'Qian Liu', 'Arunesh Sinha', 'Pradeep Varakantham', 'Min Lin'] | ['cs.CL', 'cs.LG'] | Human alignment in large language models (LLMs) is an active area of
research. A recent groundbreaking work, direct preference optimization (DPO),
has greatly simplified the process from past work in reinforcement learning
from human feedback (RLHF) by bypassing the reward learning stage in RLHF. DPO,
after training, p... | 2024-06-14T06:57:18Z | Accepted in ICLR 2025 | null | null | Bootstrapping Language Models with DPO Implicit Rewards | ['Changyu Chen', 'Zi-Yan Liu', 'Chao Du', 'Tianyu Pang', 'Qian Liu', 'Arunesh Sinha', 'Pradeep Varakantham', 'Min Lin'] | 2,024 | International Conference on Learning Representations | 27 | 43 | ['Computer Science'] |
2,406.09788 | OpenCapBench: A Benchmark to Bridge Pose Estimation and Biomechanics | ['Yoni Gozlan', 'Antoine Falisse', 'Scott Uhlrich', 'Anthony Gatti', 'Michael Black', 'Akshay Chaudhari'] | ['cs.CV'] | Pose estimation has promised to impact healthcare by enabling more practical
methods to quantify nuances of human movement and biomechanics. However,
despite the inherent connection between pose estimation and biomechanics, these
disciplines have largely remained disparate. For example, most current pose
estimation ben... | 2024-06-14T07:37:28Z | null | null | null | null | null | null | null | null | null | null |
2,406.099 | GEB-1.3B: Open Lightweight Large Language Model | ['Jie Wu', 'Yufeng Zhu', 'Lei Shen', 'Xuqing Lu'] | ['cs.CL'] | Recently developed large language models (LLMs) such as ChatGPT, Claude, and
Llama have demonstrated impressive abilities, and even surpass human-level
performance in several tasks. Despite their success, the resource-intensive
demands of these models, requiring significant computational power for both
training and inf... | 2024-06-14T10:15:49Z | GEB-1.3B technical report | null | null | null | null | null | null | null | null | null |
2,406.09904 | QQQ: Quality Quattuor-Bit Quantization for Large Language Models | ['Ying Zhang', 'Peng Zhang', 'Mincong Huang', 'Jingyang Xiang', 'Yujie Wang', 'Chao Wang', 'Yineng Zhang', 'Lei Yu', 'Chuan Liu', 'Wei Lin'] | ['cs.LG'] | Quantization is a proven effective method for compressing large language
models. Although popular techniques like W8A8 and W4A16 effectively maintain
model performance, they often fail to concurrently speed up the prefill and
decoding stages of inference. W4A8 is a promising strategy to accelerate both
of them while us... | 2024-06-14T10:23:45Z | null | null | null | QQQ: Quality Quattuor-Bit Quantization for Large Language Models | ['Ying Zhang', 'Peng Zhang', 'Mincong Huang', 'Jingyang Xiang', 'Yujie Wang', 'Chao Wang', 'Yineng Zhang', 'Lei Yu', 'Chuan Liu', 'Wei Lin'] | 2,024 | arXiv.org | 6 | 26 | ['Computer Science'] |
2,406.09913 | OpenECAD: An Efficient Visual Language Model for Editable 3D-CAD Design | ['Zhe Yuan', 'Jianqi Shi', 'Yanhong Huang'] | ['cs.CV'] | Computer-aided design (CAD) tools are utilized in the manufacturing industry
for modeling everything from cups to spacecraft. These programs are complex to
use and typically require years of training and experience to master.
Structured and well-constrained 2D sketches and 3D constructions are crucial
components of CAD... | 2024-06-14T10:47:52Z | null | Computers & Graphics 124C (2024) 104048 | 10.1016/j.cag.2024.104048 | null | null | null | null | null | null | null |
2,406.09952 | BiVLC: Extending Vision-Language Compositionality Evaluation with
Text-to-Image Retrieval | ['Imanol Miranda', 'Ander Salaberria', 'Eneko Agirre', 'Gorka Azkune'] | ['cs.CV', 'cs.CL', 'cs.LG'] | Existing Vision-Language Compositionality (VLC) benchmarks like SugarCrepe
are formulated as image-to-text retrieval problems, where, given an image, the
models need to select between the correct textual description and a synthetic
hard negative text. In this work, we present the Bidirectional Vision-Language
Compositi... | 2024-06-14T11:58:49Z | Accepted to NeurIPS 24 Datasets and Benchmarks Track; Project page
at: https://imirandam.github.io/BiVLC_project_page/ | null | null | BiVLC: Extending Vision-Language Compositionality Evaluation with Text-to-Image Retrieval | ['Imanol Miranda', 'Ander Salaberria', 'Eneko Agirre', 'Gorka Azkune'] | 2,024 | Neural Information Processing Systems | 2 | 31 | ['Computer Science'] |
2,406.10099 | Know the Unknown: An Uncertainty-Sensitive Method for LLM Instruction
Tuning | ['Jiaqi Li', 'Yixuan Tang', 'Yi Yang'] | ['cs.CL'] | Large language models (LLMs) demonstrate remarkable capabilities but face
challenges from hallucinations, which typically arise from insufficient
knowledge or context. While instructing LLMs to acknowledge knowledge
limitations by responding with "I don't know" appears promising, we find that
models consistently strugg... | 2024-06-14T14:56:04Z | null | null | null | Know the Unknown: An Uncertainty-Sensitive Method for LLM Instruction Tuning | ['Jiaqi Li', 'Yixuan Tang', 'Yi Yang'] | 2,024 | arXiv.org | 8 | 54 | ['Computer Science'] |
2,406.10118 | SEACrowd: A Multilingual Multimodal Data Hub and Benchmark Suite for
Southeast Asian Languages | ['Holy Lovenia', 'Rahmad Mahendra', 'Salsabil Maulana Akbar', 'Lester James V. Miranda', 'Jennifer Santoso', 'Elyanah Aco', 'Akhdan Fadhilah', 'Jonibek Mansurov', 'Joseph Marvin Imperial', 'Onno P. Kampman', 'Joel Ruben Antony Moniz', 'Muhammad Ravi Shulthan Habibi', 'Frederikus Hudi', 'Railey Montalan', 'Ryan Ignatius... | ['cs.CL'] | Southeast Asia (SEA) is a region rich in linguistic diversity and cultural
variety, with over 1,300 indigenous languages and a population of 671 million
people. However, prevailing AI models suffer from a significant lack of
representation of texts, images, and audio datasets from SEA, compromising the
quality of AI mo... | 2024-06-14T15:23:39Z | https://seacrowd.github.io/ Published in EMNLP 2024 | null | null | SEACrowd: A Multilingual Multimodal Data Hub and Benchmark Suite for Southeast Asian Languages | ['Holy Lovenia', 'Rahmad Mahendra', 'Salsabil Maulana Akbar', 'Lester James Validad Miranda', 'Jennifer Santoso', 'Elyanah Aco', 'Akhdan Fadhilah', 'Jonibek Mansurov', 'Joseph Marvin Imperial', 'Onno P. Kampman', 'Joel Ruben Antony Moniz', 'Muhammad Ravi Shulthan Habibi', 'Frederikus Hudi', 'Railey Montalan', 'Ryan Ign... | 2,024 | Conference on Empirical Methods in Natural Language Processing | 14 | 143 | ['Computer Science'] |
2,406.10163 | MeshAnything: Artist-Created Mesh Generation with Autoregressive
Transformers | ['Yiwen Chen', 'Tong He', 'Di Huang', 'Weicai Ye', 'Sijin Chen', 'Jiaxiang Tang', 'Xin Chen', 'Zhongang Cai', 'Lei Yang', 'Gang Yu', 'Guosheng Lin', 'Chi Zhang'] | ['cs.CV', 'cs.AI'] | Recently, 3D assets created via reconstruction and generation have matched
the quality of manually crafted assets, highlighting their potential for
replacement. However, this potential is largely unrealized because these assets
always need to be converted to meshes for 3D industry applications, and the
meshes produced ... | 2024-06-14T16:30:25Z | Project Page: https://buaacyw.github.io/mesh-anything/ Code:
https://github.com/buaacyw/MeshAnything | null | null | null | null | null | null | null | null | null |
2,406.10173 | IntentionQA: A Benchmark for Evaluating Purchase Intention Comprehension
Abilities of Language Models in E-commerce | ['Wenxuan Ding', 'Weiqi Wang', 'Sze Heng Douglas Kwok', 'Minghao Liu', 'Tianqing Fang', 'Jiaxin Bai', 'Xin Liu', 'Changlong Yu', 'Zheng Li', 'Chen Luo', 'Qingyu Yin', 'Bing Yin', 'Junxian He', 'Yangqiu Song'] | ['cs.CL'] | Enhancing Language Models' (LMs) ability to understand purchase intentions in
E-commerce scenarios is crucial for their effective assistance in various
downstream tasks. However, previous approaches that distill intentions from LMs
often fail to generate meaningful and human-centric intentions applicable in
real-world ... | 2024-06-14T16:51:21Z | Findings of EMNLP 2024 | null | null | IntentionQA: A Benchmark for Evaluating Purchase Intention Comprehension Abilities of Language Models in E-commerce | ['Wenxuan Ding', 'Weiqi Wang', 'Sze Heng Douglas Kwok', 'Minghao Liu', 'Tianqing Fang', 'Jiaxin Bai', 'Junxian He', 'Yangqiu Song'] | 2,024 | Conference on Empirical Methods in Natural Language Processing | 8 | 68 | ['Computer Science'] |
2,406.10208 | Glyph-ByT5-v2: A Strong Aesthetic Baseline for Accurate Multilingual
Visual Text Rendering | ['Zeyu Liu', 'Weicong Liang', 'Yiming Zhao', 'Bohan Chen', 'Lin Liang', 'Lijuan Wang', 'Ji Li', 'Yuhui Yuan'] | ['cs.CV'] | Recently, Glyph-ByT5 has achieved highly accurate visual text rendering
performance in graphic design images. However, it still focuses solely on
English and performs relatively poorly in terms of visual appeal. In this work,
we address these two fundamental limitations by presenting Glyph-ByT5-v2 and
Glyph-SDXL-v2, wh... | 2024-06-14T17:44:09Z | Project page: https://glyph-byt5-v2.github.io/ | null | null | null | null | null | null | null | null | null |
2,406.10209 | Be like a Goldfish, Don't Memorize! Mitigating Memorization in
Generative LLMs | ['Abhimanyu Hans', 'Yuxin Wen', 'Neel Jain', 'John Kirchenbauer', 'Hamid Kazemi', 'Prajwal Singhania', 'Siddharth Singh', 'Gowthami Somepalli', 'Jonas Geiping', 'Abhinav Bhatele', 'Tom Goldstein'] | ['cs.CL'] | Large language models can memorize and repeat their training data, causing
privacy and copyright risks. To mitigate memorization, we introduce a subtle
modification to the next-token training objective that we call the goldfish
loss. During training, randomly sampled subsets of tokens are excluded from the
loss computa... | 2024-06-14T17:44:22Z | 10 pages, 8 figures, and 1 table in the main body. Code available at
https://github.com/ahans30/goldfish-loss and checkpoints at
https://huggingface.co/collections/tomg-group-umd/goldfish-loss-mitigating-memorization-in-llms-66c175becb6aab07744f7272 | null | null | null | null | null | null | null | null | null |
2,406.10216 | Regularizing Hidden States Enables Learning Generalizable Reward Model
for LLMs | ['Rui Yang', 'Ruomeng Ding', 'Yong Lin', 'Huan Zhang', 'Tong Zhang'] | ['cs.CL', 'cs.AI'] | Reward models trained on human preference data have been proven to
effectively align Large Language Models (LLMs) with human intent within the
framework of reinforcement learning from human feedback (RLHF). However,
current reward models have limited generalization capabilities to unseen
prompts and responses, which ca... | 2024-06-14T17:49:59Z | NeurIPS 2024 | null | null | null | null | null | null | null | null | null |
2,406.10224 | EFM3D: A Benchmark for Measuring Progress Towards 3D Egocentric
Foundation Models | ['Julian Straub', 'Daniel DeTone', 'Tianwei Shen', 'Nan Yang', 'Chris Sweeney', 'Richard Newcombe'] | ['cs.CV'] | The advent of wearable computers enables a new source of context for AI that
is embedded in egocentric sensor data. This new egocentric data comes equipped
with fine-grained 3D location information and thus presents the opportunity for
a novel class of spatial foundation models that are rooted in 3D space. To
measure p... | 2024-06-14T17:57:35Z | null | null | null | EFM3D: A Benchmark for Measuring Progress Towards 3D Egocentric Foundation Models | ['Julian Straub', 'Daniel DeTone', 'Tianwei Shen', 'Nan Yang', 'Chris Sweeney', 'Richard A. Newcombe'] | 2,024 | arXiv.org | 9 | 57 | ['Computer Science'] |
2,406.10258 | Curating Grounded Synthetic Data with Global Perspectives for Equitable
AI | ['Elin Törnquist', 'Robert Alexander Caulk'] | ['cs.CL', 'I.2.7'] | The development of robust AI models relies heavily on the quality and variety
of training data available. In fields where data scarcity is prevalent,
synthetic data generation offers a vital solution. In this paper, we introduce
a novel approach to creating synthetic datasets, grounded in real-world
diversity and enric... | 2024-06-10T17:59:11Z | null | null | null | null | null | null | null | null | null | null |
2,406.10324 | L4GM: Large 4D Gaussian Reconstruction Model | ['Jiawei Ren', 'Kevin Xie', 'Ashkan Mirzaei', 'Hanxue Liang', 'Xiaohui Zeng', 'Karsten Kreis', 'Ziwei Liu', 'Antonio Torralba', 'Sanja Fidler', 'Seung Wook Kim', 'Huan Ling'] | ['cs.CV', 'cs.LG'] | We present L4GM, the first 4D Large Reconstruction Model that produces
animated objects from a single-view video input -- in a single feed-forward
pass that takes only a second. Key to our success is a novel dataset of
multiview videos containing curated, rendered animated objects from Objaverse.
This dataset depicts 4... | 2024-06-14T17:51:18Z | Project page: https://research.nvidia.com/labs/toronto-ai/l4gm | null | null | L4GM: Large 4D Gaussian Reconstruction Model | ['Jiawei Ren', 'Kevin Xie', 'Ashkan Mirzaei', 'Hanxue Liang', 'Xiaohui Zeng', 'Karsten Kreis', 'Ziwei Liu', 'Antonio Torralba', 'Sanja Fidler', 'Seung Wook Kim', 'Huan Ling'] | 2,024 | Neural Information Processing Systems | 45 | 72 | ['Computer Science'] |
2,406.10328 | From Pixels to Prose: A Large Dataset of Dense Image Captions | ['Vasu Singla', 'Kaiyu Yue', 'Sukriti Paul', 'Reza Shirkavand', 'Mayuka Jayawardhana', 'Alireza Ganjdanesh', 'Heng Huang', 'Abhinav Bhatele', 'Gowthami Somepalli', 'Tom Goldstein'] | ['cs.CV', 'cs.CL', 'cs.LG'] | Training large vision-language models requires extensive, high-quality
image-text pairs. Existing web-scraped datasets, however, are noisy and lack
detailed image descriptions. To bridge this gap, we introduce PixelProse, a
comprehensive dataset of over 16M (million) synthetically generated captions,
leveraging cutting... | 2024-06-14T17:59:53Z | pixelprose 16M dataset | null | null | null | null | null | null | null | null | null |
2,406.10429 | Consistency-diversity-realism Pareto fronts of conditional image
generative models | ['Pietro Astolfi', 'Marlene Careil', 'Melissa Hall', 'Oscar Mañas', 'Matthew Muckley', 'Jakob Verbeek', 'Adriana Romero Soriano', 'Michal Drozdzal'] | ['cs.CV', 'cs.AI'] | Building world models that accurately and comprehensively represent the real
world is the utmost aspiration for conditional image generative models as it
would enable their use as world simulators. For these models to be successful
world models, they should not only excel at image quality and prompt-image
consistency b... | 2024-06-14T22:14:11Z | null | null | null | null | null | null | null | null | null | null |
2,406.10454 | HumanPlus: Humanoid Shadowing and Imitation from Humans | ['Zipeng Fu', 'Qingqing Zhao', 'Qi Wu', 'Gordon Wetzstein', 'Chelsea Finn'] | ['cs.RO', 'cs.AI', 'cs.CV', 'cs.LG', 'cs.SY', 'eess.SY'] | One of the key arguments for building robots that have similar form factors
to human beings is that we can leverage the massive human data for training.
Yet, doing so has remained challenging in practice due to the complexities in
humanoid perception and control, lingering physical gaps between humanoids and
humans in ... | 2024-06-15T00:41:34Z | project website: https://humanoid-ai.github.io/ | null | null | null | null | null | null | null | null | null |
2,406.10601 | The Devil is in the Details: StyleFeatureEditor for Detail-Rich StyleGAN
Inversion and High Quality Image Editing | ['Denis Bobkov', 'Vadim Titov', 'Aibek Alanov', 'Dmitry Vetrov'] | ['cs.CV'] | The task of manipulating real image attributes through StyleGAN inversion has
been extensively researched. This process involves searching latent variables
from a well-trained StyleGAN generator that can synthesize a real image,
modifying these latent variables, and then synthesizing an image with the
desired edits. A ... | 2024-06-15T11:28:32Z | Accepted to CVPR 2024 | null | null | null | null | null | null | null | null | null |
2,406.10638 | Unveiling the Ignorance of MLLMs: Seeing Clearly, Answering Incorrectly | ['Yexin Liu', 'Zhengyang Liang', 'Yueze Wang', 'Xianfeng Wu', 'Feilong Tang', 'Muyang He', 'Jian Li', 'Zheng Liu', 'Harry Yang', 'Sernam Lim', 'Bo Zhao'] | ['cs.CV'] | Multimodal Large Language Models (MLLMs) have displayed remarkable
performance in multi-modal tasks, particularly in visual comprehension.
However, we reveal that MLLMs often generate incorrect answers even when they
understand the visual content. To this end, we manually construct a benchmark
with 12 categories and de... | 2024-06-15T13:58:26Z | null | null | null | Unveiling the Ignorance of MLLMs: Seeing Clearly, Answering Incorrectly | ['Yexin Liu', 'Zhengyang Liang', 'Yueze Wang', 'Xianfeng Wu', 'Feilong Tang', 'Muyang He', 'Jian Li', 'Zheng Liu', 'Harry Yang', 'Ser-Nam Lim', 'Bo Zhao'] | 2,024 | Computer Vision and Pattern Recognition | 7 | 98 | ['Computer Science'] |
2,406.10721 | RoboPoint: A Vision-Language Model for Spatial Affordance Prediction for
Robotics | ['Wentao Yuan', 'Jiafei Duan', 'Valts Blukis', 'Wilbert Pumacay', 'Ranjay Krishna', 'Adithyavairavan Murali', 'Arsalan Mousavian', 'Dieter Fox'] | ['cs.RO', 'cs.AI', 'cs.CV'] | From rearranging objects on a table to putting groceries into shelves, robots
must plan precise action points to perform tasks accurately and reliably. In
spite of the recent adoption of vision language models (VLMs) to control robot
behavior, VLMs struggle to precisely articulate robot actions using language.
We intro... | 2024-06-15T19:22:51Z | null | null | null | null | null | null | null | null | null | null |
2,406.10735 | How Should We Extract Discrete Audio Tokens from Self-Supervised Models? | ['Pooneh Mousavi', 'Jarod Duret', 'Salah Zaiem', 'Luca Della Libera', 'Artem Ploujnikov', 'Cem Subakan', 'Mirco Ravanelli'] | ['cs.SD', 'cs.AI', 'cs.CL', 'eess.AS'] | Discrete audio tokens have recently gained attention for their potential to
bridge the gap between audio and language processing. Ideal audio tokens must
preserve content, paralinguistic elements, speaker identity, and many other
audio details. Current audio tokenization methods fall into two categories:
Semantic token... | 2024-06-15T20:43:07Z | 4 pages, 2 figures, 2 tables, Accepted at Interspeech 2024 | null | null | How Should We Extract Discrete Audio Tokens from Self-Supervised Models? | ['Pooneh Mousavi', 'J. Duret', 'Salah Zaiem', 'Luca Della Libera', 'Artem Ploujnikov', 'Cem Subakan', 'M. Ravanelli'] | 2,024 | Interspeech | 15 | 45 | ['Computer Science', 'Engineering'] |
2,406.10806 | ptt5-v2: A Closer Look at Continued Pretraining of T5 Models for the
Portuguese Language | ['Marcos Piau', 'Roberto Lotufo', 'Rodrigo Nogueira'] | ['cs.CL', 'cs.AI', 'cs.IR'] | Despite advancements in Natural Language Processing (NLP) and the growing
availability of pretrained models, the English language remains the primary
focus of model development. Continued pretraining on language-specific corpora
provides a practical solution for adapting models to other languages. However,
the impact o... | 2024-06-16T05:17:56Z | null | null | null | null | null | null | null | null | null | null |
2,406.10819 | GUI-World: A Video Benchmark and Dataset for Multimodal GUI-oriented
Understanding | ['Dongping Chen', 'Yue Huang', 'Siyuan Wu', 'Jingyu Tang', 'Liuyi Chen', 'Yilin Bai', 'Zhigang He', 'Chenlong Wang', 'Huichi Zhou', 'Yiqiang Li', 'Tianshuo Zhou', 'Yue Yu', 'Chujie Gao', 'Qihui Zhang', 'Yi Gui', 'Zhen Li', 'Yao Wan', 'Pan Zhou', 'Jianfeng Gao', 'Lichao Sun'] | ['cs.CV', 'cs.AI', 'cs.CL'] | Recently, Multimodal Large Language Models (MLLMs) have been used as agents
to control keyboard and mouse inputs by directly perceiving the Graphical User
Interface (GUI) and generating corresponding commands. However, current agents
primarily demonstrate strong understanding capabilities in static environments
and are... | 2024-06-16T06:56:53Z | Accepted by ICLR 2025 | null | null | null | null | null | null | null | null | null |
2,406.10858 | Step-level Value Preference Optimization for Mathematical Reasoning | ['Guoxin Chen', 'Minpeng Liao', 'Chengxi Li', 'Kai Fan'] | ['cs.CL', 'cs.AI'] | Direct Preference Optimization (DPO) using an implicit reward model has
proven to be an effective alternative to reinforcement learning from human
feedback (RLHF) for fine-tuning preference aligned large language models
(LLMs). However, the overall preference annotations of responses do not fully
capture the fine-grain... | 2024-06-16T09:06:17Z | Camera ready version for EMNLP2024-Findings | null | null | Step-level Value Preference Optimization for Mathematical Reasoning | ['Guoxin Chen', 'Minpeng Liao', 'Chengxi Li', 'Kai Fan'] | 2,024 | Conference on Empirical Methods in Natural Language Processing | 42 | 42 | ['Computer Science'] |
2,406.1097 | Joint Audio and Symbolic Conditioning for Temporally Controlled
Text-to-Music Generation | ['Or Tal', 'Alon Ziv', 'Itai Gat', 'Felix Kreuk', 'Yossi Adi'] | ['cs.SD', 'eess.AS'] | We present JASCO, a temporally controlled text-to-music generation model
utilizing both symbolic and audio-based conditions. JASCO can generate
high-quality music samples conditioned on global text descriptions along with
fine-grained local controls. JASCO is based on the Flow Matching modeling
paradigm together with a... | 2024-06-16T15:06:06Z | null | null | null | null | null | null | null | null | null | null |
2,406.11037 | NAST: Noise Aware Speech Tokenization for Speech Language Models | ['Shoval Messica', 'Yossi Adi'] | ['cs.SD', 'eess.AS'] | Speech tokenization is the task of representing speech signals as a sequence
of discrete units. Such representations can be later used for various
downstream tasks including automatic speech recognition, text-to-speech, etc.
More relevant to this study, such representation serves as the basis of Speech
Language Models.... | 2024-06-16T18:20:45Z | Accepted at Interspeech 2024 | null | null | null | null | null | null | null | null | null |
2,406.11192 | Beyond Boundaries: Learning a Universal Entity Taxonomy across Datasets
and Languages for Open Named Entity Recognition | ['Yuming Yang', 'Wantong Zhao', 'Caishuang Huang', 'Junjie Ye', 'Xiao Wang', 'Huiyuan Zheng', 'Yang Nan', 'Yuran Wang', 'Xueying Xu', 'Kaixin Huang', 'Yunke Zhang', 'Tao Gui', 'Qi Zhang', 'Xuanjing Huang'] | ['cs.CL'] | Open Named Entity Recognition (NER), which involves identifying arbitrary
types of entities from arbitrary domains, remains challenging for Large
Language Models (LLMs). Recent studies suggest that fine-tuning LLMs on
extensive NER data can boost their performance. However, training directly on
existing datasets neglec... | 2024-06-17T03:57:35Z | Accepted at COLING 2025. Camera-ready version updated. Project page:
https://github.com/UmeanNever/B2NER | Proceedings of the 31st International Conference on Computational
Linguistics (2025) 10902-10923 | null | null | null | null | null | null | null | null |
2,406.11251 | Unifying Multimodal Retrieval via Document Screenshot Embedding | ['Xueguang Ma', 'Sheng-Chieh Lin', 'Minghan Li', 'Wenhu Chen', 'Jimmy Lin'] | ['cs.IR'] | In the real world, documents are organized in different formats and varied
modalities. Traditional retrieval pipelines require tailored document parsing
techniques and content extraction modules to prepare input for indexing. This
process is tedious, prone to errors, and has information loss. To this end, we
propose Do... | 2024-06-17T06:27:35Z | EMNLP2024 main | null | null | null | null | null | null | null | null | null |
2,406.11317 | GUICourse: From General Vision Language Models to Versatile GUI Agents | ['Wentong Chen', 'Junbo Cui', 'Jinyi Hu', 'Yujia Qin', 'Junjie Fang', 'Yue Zhao', 'Chongyi Wang', 'Jun Liu', 'Guirong Chen', 'Yupeng Huo', 'Yuan Yao', 'Yankai Lin', 'Zhiyuan Liu', 'Maosong Sun'] | ['cs.AI', 'cs.CL', 'cs.CV', 'cs.HC'] | Utilizing Graphic User Interface (GUI) for human-computer interaction is
essential for accessing a wide range of digital tools. Recent advancements in
Vision Language Models (VLMs) highlight the compelling potential to develop
versatile agents to help humans finish GUI navigation tasks. However, current
VLMs are challe... | 2024-06-17T08:30:55Z | null | 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.