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2,405.14906 | AutoCoder: Enhancing Code Large Language Model with
\textsc{AIEV-Instruct} | ['Bin Lei', 'Yuchen Li', 'Qiuwu Chen'] | ['cs.SE', 'cs.AI'] | We introduce AutoCoder, the first Large Language Model to surpass GPT-4 Turbo
(April 2024) and GPT-4o in pass@1 on the Human Eval benchmark test
($\mathbf{90.9\%}$ vs. $\mathbf{90.2\%}$). In addition, AutoCoder offers a more
versatile code interpreter compared to GPT-4 Turbo and GPT-4o. It's code
interpreter can instal... | 2024-05-23T02:53:25Z | null | null | null | AutoCoder: Enhancing Code Large Language Model with AIEV-Instruct | ['Bin Lei', 'Yuchen Li', 'Qiuwu Chen'] | 2,024 | arXiv.org | 7 | 29 | ['Computer Science'] |
2,405.14917 | SliM-LLM: Salience-Driven Mixed-Precision Quantization for Large
Language Models | ['Wei Huang', 'Haotong Qin', 'Yangdong Liu', 'Yawei Li', 'Qinshuo Liu', 'Xianglong Liu', 'Luca Benini', 'Michele Magno', 'Shiming Zhang', 'Xiaojuan Qi'] | ['cs.LG', 'cs.CL'] | Post-training quantization (PTQ) is an effective technique for compressing
large language models (LLMs). However, while uniform-precision quantization is
computationally efficient, it often compromises model performance. To address
this, we propose SliM-LLM, a salience-driven mixed-precision quantization
framework that... | 2024-05-23T16:21:48Z | 22 pages | null | null | null | null | null | null | null | null | null |
2,405.1493 | AstroPT: Scaling Large Observation Models for Astronomy | ['Michael J. Smith', 'Ryan J. Roberts', 'Eirini Angeloudi', 'Marc Huertas-Company'] | ['astro-ph.IM', 'astro-ph.GA', 'cs.LG'] | This work presents AstroPT, an autoregressive pretrained transformer
developed with astronomical use-cases in mind. The AstroPT models presented
here have been pretrained on 8.6 million $512 \times 512$ pixel $grz$-band
galaxy postage stamp observations from the DESI Legacy Survey DR8. We train a
selection of foundatio... | 2024-05-23T18:00:00Z | 12 pages, 4 figures, 1 table. Code available at
https://github.com/Smith42/astroPT | null | null | null | null | null | null | null | null | null |
2,405.14974 | LOVA3: Learning to Visual Question Answering, Asking and Assessment | ['Henry Hengyuan Zhao', 'Pan Zhou', 'Difei Gao', 'Zechen Bai', 'Mike Zheng Shou'] | ['cs.CV', 'cs.AI', 'cs.CL'] | Question answering, asking, and assessment are three innate human traits
crucial for understanding the world and acquiring knowledge. By enhancing these
capabilities, humans can more effectively utilize data, leading to better
comprehension and learning outcomes. Current Multimodal Large Language Models
(MLLMs) primari... | 2024-05-23T18:21:59Z | NeurIPS 2024. The code is available at
https://github.com/showlab/LOVA3 | null | null | LOVA3: Learning to Visual Question Answering, Asking and Assessment | ['Henry Hengyuan Zhao', 'Pan Zhou', 'Difei Gao', 'Mike Zheng Shou'] | 2,024 | Neural Information Processing Systems | 9 | 112 | ['Computer Science'] |
2,405.14979 | CraftsMan3D: High-fidelity Mesh Generation with 3D Native Generation and
Interactive Geometry Refiner | ['Weiyu Li', 'Jiarui Liu', 'Hongyu Yan', 'Rui Chen', 'Yixun Liang', 'Xuelin Chen', 'Ping Tan', 'Xiaoxiao Long'] | ['cs.GR', 'cs.CV'] | We present a novel generative 3D modeling system, coined CraftsMan, which can
generate high-fidelity 3D geometries with highly varied shapes, regular mesh
topologies, and detailed surfaces, and, notably, allows for refining the
geometry in an interactive manner. Despite the significant advancements in 3D
generation, ex... | 2024-05-23T18:30:12Z | HomePage: https://craftsman3d.github.io/, Code:
https://github.com/wyysf-98/CraftsMan3D | null | null | CraftsMan3D: High-fidelity Mesh Generation with 3D Native Generation and Interactive Geometry Refiner | ['Weiyu Li', 'Jiarui Liu', 'Rui Chen', 'Yixun Liang', 'Xuelin Chen', 'Ping Tan', 'Xiaoxiao Long'] | 2,024 | null | 59 | 65 | ['Computer Science'] |
2,405.15032 | Aya 23: Open Weight Releases to Further Multilingual Progress | ['Viraat Aryabumi', 'John Dang', 'Dwarak Talupuru', 'Saurabh Dash', 'David Cairuz', 'Hangyu Lin', 'Bharat Venkitesh', 'Madeline Smith', 'Jon Ander Campos', 'Yi Chern Tan', 'Kelly Marchisio', 'Max Bartolo', 'Sebastian Ruder', 'Acyr Locatelli', 'Julia Kreutzer', 'Nick Frosst', 'Aidan Gomez', 'Phil Blunsom', 'Marzieh Fada... | ['cs.CL'] | This technical report introduces Aya 23, a family of multilingual language
models. Aya 23 builds on the recent release of the Aya model (\"Ust\"un et al.,
2024), focusing on pairing a highly performant pre-trained model with the
recently released Aya collection (Singh et al., 2024). The result is a powerful
multilingua... | 2024-05-23T20:10:38Z | null | null | null | null | null | null | null | null | null | null |
2,405.15165 | A Solution-based LLM API-using Methodology for Academic Information
Seeking | ['Yuanchun Wang', 'Jifan Yu', 'Zijun Yao', 'Jing Zhang', 'Yuyang Xie', 'Shangqing Tu', 'Yiyang Fu', 'Youhe Feng', 'Jinkai Zhang', 'Jingyao Zhang', 'Bowen Huang', 'Yuanyao Li', 'Huihui Yuan', 'Lei Hou', 'Juanzi Li', 'Jie Tang'] | ['cs.CL', 'cs.AI', 'cs.SE'] | Applying large language models (LLMs) for academic API usage shows promise in
reducing researchers' academic information seeking efforts. However, current
LLM API-using methods struggle with complex API coupling commonly encountered
in academic queries. To address this, we introduce SoAy, a solution-based LLM
API-using... | 2024-05-24T02:44:14Z | 22 pages, 13 figures | null | null | null | null | null | null | null | null | null |
2,405.15199 | ODGEN: Domain-specific Object Detection Data Generation with Diffusion
Models | ['Jingyuan Zhu', 'Shiyu Li', 'Yuxuan Liu', 'Ping Huang', 'Jiulong Shan', 'Huimin Ma', 'Jian Yuan'] | ['cs.CV'] | Modern diffusion-based image generative models have made significant progress
and become promising to enrich training data for the object detection task.
However, the generation quality and the controllability for complex scenes
containing multi-class objects and dense objects with occlusions remain
limited. This paper... | 2024-05-24T04:10:34Z | Accepted by NeurIPS2024 | null | null | null | null | null | null | null | null | null |
2,405.15223 | iVideoGPT: Interactive VideoGPTs are Scalable World Models | ['Jialong Wu', 'Shaofeng Yin', 'Ningya Feng', 'Xu He', 'Dong Li', 'Jianye Hao', 'Mingsheng Long'] | ['cs.CV', 'cs.LG', 'cs.RO'] | World models empower model-based agents to interactively explore, reason, and
plan within imagined environments for real-world decision-making. However, the
high demand for interactivity poses challenges in harnessing recent
advancements in video generative models for developing world models at scale.
This work introdu... | 2024-05-24T05:29:12Z | NeurIPS 2024. Code is available at project website:
https://thuml.github.io/iVideoGPT | null | null | null | null | null | null | null | null | null |
2,405.15234 | Defensive Unlearning with Adversarial Training for Robust Concept
Erasure in Diffusion Models | ['Yimeng Zhang', 'Xin Chen', 'Jinghan Jia', 'Yihua Zhang', 'Chongyu Fan', 'Jiancheng Liu', 'Mingyi Hong', 'Ke Ding', 'Sijia Liu'] | ['cs.CV', 'cs.CR'] | Diffusion models (DMs) have achieved remarkable success in text-to-image
generation, but they also pose safety risks, such as the potential generation
of harmful content and copyright violations. The techniques of machine
unlearning, also known as concept erasing, have been developed to address these
risks. However, th... | 2024-05-24T05:47:23Z | Accepted by NeurIPS'24. Codes are available at
https://github.com/OPTML-Group/AdvUnlearn | null | null | null | null | null | null | null | null | null |
2,405.15306 | DeTikZify: Synthesizing Graphics Programs for Scientific Figures and
Sketches with TikZ | ['Jonas Belouadi', 'Simone Paolo Ponzetto', 'Steffen Eger'] | ['cs.CL', 'cs.CV'] | Creating high-quality scientific figures can be time-consuming and
challenging, even though sketching ideas on paper is relatively easy.
Furthermore, recreating existing figures that are not stored in formats
preserving semantic information is equally complex. To tackle this problem, we
introduce DeTikZify, a novel mul... | 2024-05-24T07:48:35Z | Accepted at NeurIPS 2024 (spotlight); Project page:
https://github.com/potamides/DeTikZify | null | null | null | null | null | null | null | null | null |
2,405.15319 | Stacking Your Transformers: A Closer Look at Model Growth for Efficient
LLM Pre-Training | ['Wenyu Du', 'Tongxu Luo', 'Zihan Qiu', 'Zeyu Huang', 'Yikang Shen', 'Reynold Cheng', 'Yike Guo', 'Jie Fu'] | ['cs.CL', 'cs.AI'] | LLMs are computationally expensive to pre-train due to their large scale.
Model growth emerges as a promising approach by leveraging smaller models to
accelerate the training of larger ones. However, the viability of these model
growth methods in efficient LLM pre-training remains underexplored. This work
identifies th... | 2024-05-24T08:00:00Z | NeurIPS 2024 Spotlight | null | null | null | null | null | null | null | null | null |
2,405.15506 | Learning to Discretize Denoising Diffusion ODEs | ['Vinh Tong', 'Hoang Trung-Dung', 'Anji Liu', 'Guy Van den Broeck', 'Mathias Niepert'] | ['cs.LG'] | Diffusion Probabilistic Models (DPMs) are generative models showing
competitive performance in various domains, including image synthesis and 3D
point cloud generation. Sampling from pre-trained DPMs involves multiple neural
function evaluations (NFEs) to transform Gaussian noise samples into images,
resulting in highe... | 2024-05-24T12:51:23Z | null | null | null | Learning to Discretize Denoising Diffusion ODEs | ['Vinh Tong', 'Anji Liu', 'Trung-Dung Hoang', 'Guy Van den Broeck', 'Mathias Niepert'] | 2,024 | International Conference on Learning Representations | 6 | 50 | ['Computer Science'] |
2,405.15574 | Meteor: Mamba-based Traversal of Rationale for Large Language and Vision
Models | ['Byung-Kwan Lee', 'Chae Won Kim', 'Beomchan Park', 'Yong Man Ro'] | ['cs.CV'] | The rapid development of large language and vision models (LLVMs) has been
driven by advances in visual instruction tuning. Recently, open-source LLVMs
have curated high-quality visual instruction tuning datasets and utilized
additional vision encoders or multiple computer vision models in order to
narrow the performan... | 2024-05-24T14:04:03Z | Code is available in https://github.com/ByungKwanLee/Meteor | null | null | null | null | null | null | null | null | null |
2,405.15589 | Efficient Adversarial Training in LLMs with Continuous Attacks | ['Sophie Xhonneux', 'Alessandro Sordoni', 'Stephan Günnemann', 'Gauthier Gidel', 'Leo Schwinn'] | ['cs.LG', 'cs.CR'] | Large language models (LLMs) are vulnerable to adversarial attacks that can
bypass their safety guardrails. In many domains, adversarial training has
proven to be one of the most promising methods to reliably improve robustness
against such attacks. Yet, in the context of LLMs, current methods for
adversarial training ... | 2024-05-24T14:20:09Z | 19 pages, 4 figures | null | null | Efficient Adversarial Training in LLMs with Continuous Attacks | ['Sophie Xhonneux', 'Alessandro Sordoni', 'Stephan Günnemann', 'G. Gidel', 'Leo Schwinn'] | 2,024 | Neural Information Processing Systems | 56 | 46 | ['Computer Science'] |
2,405.1564 | GECKO: Generative Language Model for English, Code and Korean | ['Sungwoo Oh', 'Donggyu Kim'] | ['cs.CL', 'cs.AI'] | We introduce GECKO, a bilingual large language model (LLM) optimized for
Korean and English, along with programming languages. GECKO is pretrained on
the balanced, high-quality corpus of Korean and English employing LLaMA
architecture. In this report, we share the experiences of several efforts to
build a better data p... | 2024-05-24T15:30:41Z | null | null | null | GECKO: Generative Language Model for English, Code and Korean | ['Sungwoo Oh', 'Donggyu Kim'] | 2,024 | arXiv.org | 0 | 49 | ['Computer Science'] |
2,405.15662 | Class Machine Unlearning for Complex Data via Concepts Inference and
Data Poisoning | ['Wenhan Chang', 'Tianqing Zhu', 'Heng Xu', 'Wenjian Liu', 'Wanlei Zhou'] | ['cs.LG'] | In current AI era, users may request AI companies to delete their data from
the training dataset due to the privacy concerns. As a model owner, retraining
a model will consume significant computational resources. Therefore, machine
unlearning is a new emerged technology to allow model owner to delete requested
training... | 2024-05-24T15:59:17Z | null | null | null | null | null | null | null | null | null | null |
2,405.15734 | LM4LV: A Frozen Large Language Model for Low-level Vision Tasks | ['Boyang Zheng', 'Jinjin Gu', 'Shijun Li', 'Chao Dong'] | ['cs.CV'] | The success of large language models (LLMs) has fostered a new research trend
of multi-modality large language models (MLLMs), which changes the paradigm of
various fields in computer vision. Though MLLMs have shown promising results in
numerous high-level vision and vision-language tasks such as VQA and
text-to-image,... | 2024-05-24T17:25:00Z | null | null | null | null | null | null | null | null | null | null |
2,405.15738 | ConvLLaVA: Hierarchical Backbones as Visual Encoder for Large Multimodal
Models | ['Chunjiang Ge', 'Sijie Cheng', 'Ziming Wang', 'Jiale Yuan', 'Yuan Gao', 'Jun Song', 'Shiji Song', 'Gao Huang', 'Bo Zheng'] | ['cs.CV'] | High-resolution Large Multimodal Models (LMMs) encounter the challenges of
excessive visual tokens and quadratic visual complexity. Current
high-resolution LMMs address the quadratic complexity while still generating
excessive visual tokens. However, the redundancy in visual tokens is the key
problem as it leads to mor... | 2024-05-24T17:34:15Z | 17 pages | null | null | null | null | null | null | null | null | null |
2,405.15863 | Quality-aware Masked Diffusion Transformer for Enhanced Music Generation | ['Chang Li', 'Ruoyu Wang', 'Lijuan Liu', 'Jun Du', 'Yixuan Sun', 'Zilu Guo', 'Zhenrong Zhang', 'Yuan Jiang', 'Jianqing Gao', 'Feng Ma'] | ['cs.SD', 'cs.AI', 'eess.AS'] | Text-to-music (TTM) generation, which converts textual descriptions into
audio, opens up innovative avenues for multimedia creation. Achieving high
quality and diversity in this process demands extensive, high-quality data,
which are often scarce in available datasets. Most open-source datasets
frequently suffer from i... | 2024-05-24T18:09:27Z | IJCAI | null | null | null | null | null | null | null | null | null |
2,405.15953 | Activator: GLU Activation Function as the Core Component of a Vision
Transformer | ['Abdullah Nazhat Abdullah', 'Tarkan Aydin'] | ['cs.CV'] | Transformer architecture currently represents the main driver behind many
successes in a variety of tasks addressed by deep learning, especially the
recent advances in natural language processing (NLP) culminating with large
language models (LLM). In addition, transformer architecture has found a wide
spread of interes... | 2024-05-24T21:46:52Z | arXiv admin note: substantial text overlap with arXiv:2403.02411 | null | null | Activator: GLU Activation Function as the Core Component of a Vision Transformer | ['Abdullah Nazhat Abdullah', 'Tarkan Aydin'] | 2,024 | null | 0 | 54 | ['Computer Science'] |
2,405.16153 | DefSent+: Improving sentence embeddings of language models by projecting
definition sentences into a quasi-isotropic or isotropic vector space of
unlimited dictionary entries | ['Xiaodong Liu'] | ['cs.CL', 'cs.AI', 'cs.LG'] | This paper presents a significant improvement on the previous conference
paper known as DefSent. The prior study seeks to improve sentence embeddings of
language models by projecting definition sentences into the vector space of
dictionary entries. We discover that this approach is not fully explored due to
the methodo... | 2024-05-25T09:43:38Z | null | null | null | null | null | null | null | null | null | null |
2,405.16406 | SpinQuant: LLM quantization with learned rotations | ['Zechun Liu', 'Changsheng Zhao', 'Igor Fedorov', 'Bilge Soran', 'Dhruv Choudhary', 'Raghuraman Krishnamoorthi', 'Vikas Chandra', 'Yuandong Tian', 'Tijmen Blankevoort'] | ['cs.LG', 'cs.AI', 'cs.CL', 'cs.CV'] | Post-training quantization (PTQ) techniques applied to weights, activations,
and the KV cache greatly reduce memory usage, latency, and power consumption of
Large Language Models (LLMs), but may lead to large quantization errors when
outliers are present. Rotating activation or weight matrices helps remove
outliers and... | 2024-05-26T02:15:49Z | ICLR 2025 | null | null | null | null | null | null | null | null | null |
2,405.16433 | CPsyCoun: A Report-based Multi-turn Dialogue Reconstruction and
Evaluation Framework for Chinese Psychological Counseling | ['Chenhao Zhang', 'Renhao Li', 'Minghuan Tan', 'Min Yang', 'Jingwei Zhu', 'Di Yang', 'Jiahao Zhao', 'Guancheng Ye', 'Chengming Li', 'Xiping Hu'] | ['cs.CL', 'cs.AI', 'cs.CY'] | Using large language models (LLMs) to assist psychological counseling is a
significant but challenging task at present. Attempts have been made on
improving empathetic conversations or acting as effective assistants in the
treatment with LLMs. However, the existing datasets lack consulting knowledge,
resulting in LLMs ... | 2024-05-26T05:18:00Z | Appectped to Findings of ACL2024 | null | null | CPsyCoun: A Report-based Multi-turn Dialogue Reconstruction and Evaluation Framework for Chinese Psychological Counseling | ['Chenhao Zhang', 'Renhao Li', 'Minghuan Tan', 'Min Yang', 'Jingwei Zhu', 'Di Yang', 'Jiahao Zhao', 'Guancheng Ye', 'Chengming Li', 'Xiping Hu', 'Derek F. Wong'] | 2,024 | Annual Meeting of the Association for Computational Linguistics | 29 | 32 | ['Computer Science'] |
2,405.16436 | Provably Mitigating Overoptimization in RLHF: Your SFT Loss is
Implicitly an Adversarial Regularizer | ['Zhihan Liu', 'Miao Lu', 'Shenao Zhang', 'Boyi Liu', 'Hongyi Guo', 'Yingxiang Yang', 'Jose Blanchet', 'Zhaoran Wang'] | ['cs.LG', 'cs.AI', 'stat.ML'] | Aligning generative models with human preference via RLHF typically suffers
from overoptimization, where an imperfectly learned reward model can misguide
the generative model to output undesired responses. We investigate this problem
in a principled manner by identifying the source of the misalignment as a form
of dist... | 2024-05-26T05:38:50Z | Accepted by The Thirty-Eighth Annual Conference on Neural Information
Processing Systems. 31 pages, 7 figures | null | null | null | null | null | null | null | null | null |
2,405.16579 | Automatically Generating Numerous Context-Driven SFT Data for LLMs
across Diverse Granularity | ['Shanghaoran Quan'] | ['cs.CL'] | Constructing high-quality query-response pairs from custom corpus is crucial
for supervised fine-tuning (SFT) large language models (LLMs) in many
applications, like creating domain-specific AI assistants or roleplaying
agents. However, sourcing this data through human annotation is costly, and
existing automated metho... | 2024-05-26T14:14:18Z | null | null | null | null | null | null | null | null | null | null |
2,405.16635 | Compressing Lengthy Context With UltraGist | ['Peitian Zhang', 'Zheng Liu', 'Shitao Xiao', 'Ninglu Shao', 'Qiwei Ye', 'Zhicheng Dou'] | ['cs.CL'] | Compressing lengthy context is a critical but technically challenging
problem. In this paper, we propose a new method called UltraGist, which is
distinguished for its high-quality compression of lengthy context due to the
innovative design of the compression and learning algorithm. UltraGist brings
forth the following ... | 2024-05-26T17:23:56Z | Superceded by arXiv:2401.03462v3 | null | null | Compressing Lengthy Context With UltraGist | ['Peitian Zhang', 'Zheng Liu', 'Shitao Xiao', 'Ninglu Shao', 'Qiwei Ye', 'Zhicheng Dou'] | 2,024 | arXiv.org | 4 | 32 | ['Computer Science'] |
2,405.16646 | A Provably Effective Method for Pruning Experts in Fine-tuned Sparse
Mixture-of-Experts | ['Mohammed Nowaz Rabbani Chowdhury', 'Meng Wang', 'Kaoutar El Maghraoui', 'Naigang Wang', 'Pin-Yu Chen', 'Christopher Carothers'] | ['cs.LG'] | The sparsely gated mixture of experts (MoE) architecture sends different
inputs to different subnetworks, i.e., experts, through trainable routers. MoE
reduces the training computation significantly for large models, but its
deployment can be still memory or computation expensive for some downstream
tasks. Model prunin... | 2024-05-26T17:52:58Z | null | The 41st International Conference on Machine Learning, ICML 2024 | null | null | null | null | null | null | null | null |
2,405.16681 | Triple Preference Optimization: Achieving Better Alignment using a
Single Step Optimization | ['Amir Saeidi', 'Shivanshu Verma', 'Aswin RRV', 'Kashif Rasul', 'Chitta Baral'] | ['cs.CL'] | Reinforcement Learning with Human Feedback (RLHF) enhances the alignment of
Large Language Models (LLMs). However, its limitations have led to the
development of Direct Preference Optimization (DPO), an RL-free approach
designed to overcome these shortcomings. While studies have shown that DPO
improves instruction-foll... | 2024-05-26T20:18:11Z | null | null | null | null | null | null | null | null | null | null |
2,405.167 | Implicit Multimodal Alignment: On the Generalization of Frozen LLMs to
Multimodal Inputs | ['Mustafa Shukor', 'Matthieu Cord'] | ['cs.CV', 'cs.CL', 'cs.LG'] | Large Language Models (LLMs) have demonstrated impressive performance on
multimodal tasks, without any multimodal finetuning. They are the building
block for Large Multimodal Models, yet, we still lack a proper understanding of
their success. In this work, we expose frozen LLMs to image, video, audio and
text inputs an... | 2024-05-26T21:31:59Z | NeurIPS 2024. Code: https://github.com/mshukor/ima-lmms. Project
page: https://ima-lmms.github.io/ | null | null | null | null | null | null | null | null | null |
2,405.16712 | Zamba: A Compact 7B SSM Hybrid Model | ['Paolo Glorioso', 'Quentin Anthony', 'Yury Tokpanov', 'James Whittington', 'Jonathan Pilault', 'Adam Ibrahim', 'Beren Millidge'] | ['cs.LG', 'cs.AI', 'cs.CL'] | In this technical report, we present Zamba, a novel 7B SSM-transformer hybrid
model which achieves competitive performance against leading open-weight models
at a comparable scale. Zamba is trained on 1T tokens from openly available
datasets and is the best non-transformer model at this scale. Zamba pioneers a
unique a... | 2024-05-26T22:23:02Z | null | null | null | null | null | null | null | null | null | null |
2,405.16727 | Disentangling and Integrating Relational and Sensory Information in
Transformer Architectures | ['Awni Altabaa', 'John Lafferty'] | ['cs.LG'] | Relational reasoning is a central component of generally intelligent systems,
enabling robust and data-efficient inductive generalization. Recent empirical
evidence shows that many existing neural architectures, including Transformers,
struggle with tasks requiring relational reasoning. In this work, we
distinguish bet... | 2024-05-26T23:52:51Z | ICML 2025 | null | null | null | null | null | null | null | null | null |
2,405.16785 | PromptFix: You Prompt and We Fix the Photo | ['Yongsheng Yu', 'Ziyun Zeng', 'Hang Hua', 'Jianlong Fu', 'Jiebo Luo'] | ['cs.CV'] | Diffusion models equipped with language models demonstrate excellent
controllability in image generation tasks, allowing image processing to adhere
to human instructions. However, the lack of diverse instruction-following data
hampers the development of models that effectively recognize and execute
user-customized inst... | 2024-05-27T03:13:28Z | Accepted to NeurIPS 2024 | null | null | null | null | null | null | null | null | null |
2,405.16886 | Hawk: Learning to Understand Open-World Video Anomalies | ['Jiaqi Tang', 'Hao Lu', 'Ruizheng Wu', 'Xiaogang Xu', 'Ke Ma', 'Cheng Fang', 'Bin Guo', 'Jiangbo Lu', 'Qifeng Chen', 'Ying-Cong Chen'] | ['cs.CV'] | Video Anomaly Detection (VAD) systems can autonomously monitor and identify
disturbances, reducing the need for manual labor and associated costs. However,
current VAD systems are often limited by their superficial semantic
understanding of scenes and minimal user interaction. Additionally, the
prevalent data scarcity ... | 2024-05-27T07:08:58Z | null | null | null | null | null | null | null | null | null | null |
2,405.17057 | ReflectionCoder: Learning from Reflection Sequence for Enhanced One-off
Code Generation | ['Houxing Ren', 'Mingjie Zhan', 'Zhongyuan Wu', 'Aojun Zhou', 'Junting Pan', 'Hongsheng Li'] | ['cs.CL', 'cs.AI'] | Code generation plays a crucial role in various tasks, such as code
auto-completion and mathematical reasoning. Previous work has proposed numerous
methods to enhance code generation performance, including integrating feedback
from the compiler. Inspired by this, we present ReflectionCoder, a novel
approach that effect... | 2024-05-27T11:27:00Z | Accepted to ACL 2025 (main conference) | null | null | null | null | null | null | null | null | null |
2,405.17093 | DeeperImpact: Optimizing Sparse Learned Index Structures | ['Soyuj Basnet', 'Jerry Gou', 'Antonio Mallia', 'Torsten Suel'] | ['cs.IR'] | A lot of recent work has focused on sparse learned indexes that use deep
neural architectures to significantly improve retrieval quality while keeping
the efficiency benefits of the inverted index. While such sparse learned
structures achieve effectiveness far beyond those of traditional inverted
index-based rankers, t... | 2024-05-27T12:08:59Z | null | null | null | null | null | null | null | null | null | null |
2,405.17103 | Empowering Character-level Text Infilling by Eliminating Sub-Tokens | ['Houxing Ren', 'Mingjie Zhan', 'Zhongyuan Wu', 'Hongsheng Li'] | ['cs.CL', 'cs.AI'] | In infilling tasks, sub-tokens, representing instances where a complete token
is segmented into two parts, often emerge at the boundaries of prefixes,
middles, and suffixes. Traditional methods focused on training models at the
token level, leading to sub-optimal performance in character-level infilling
tasks during th... | 2024-05-27T12:21:48Z | Accepted to ACL 2024 (main conference) | null | null | Empowering Character-level Text Infilling by Eliminating Sub-Tokens | ['Houxing Ren', 'Mingjie Zhan', 'Zhongyuan Wu', 'Hongsheng Li'] | 2,024 | Annual Meeting of the Association for Computational Linguistics | 1 | 45 | ['Computer Science'] |
2,405.17176 | DreamMat: High-quality PBR Material Generation with Geometry- and
Light-aware Diffusion Models | ['Yuqing Zhang', 'Yuan Liu', 'Zhiyu Xie', 'Lei Yang', 'Zhongyuan Liu', 'Mengzhou Yang', 'Runze Zhang', 'Qilong Kou', 'Cheng Lin', 'Wenping Wang', 'Xiaogang Jin'] | ['cs.GR', 'cs.AI'] | 2D diffusion model, which often contains unwanted baked-in shading effects
and results in unrealistic rendering effects in the downstream applications.
Generating Physically Based Rendering (PBR) materials instead of just RGB
textures would be a promising solution. However, directly distilling the PBR
material paramete... | 2024-05-27T13:55:08Z | Accepted to SIGGRAPH 2024 | null | null | null | null | null | null | null | null | null |
2,405.1722 | RLAIF-V: Open-Source AI Feedback Leads to Super GPT-4V Trustworthiness | ['Tianyu Yu', 'Haoye Zhang', 'Qiming Li', 'Qixin Xu', 'Yuan Yao', 'Da Chen', 'Xiaoman Lu', 'Ganqu Cui', 'Yunkai Dang', 'Taiwen He', 'Xiaocheng Feng', 'Jun Song', 'Bo Zheng', 'Zhiyuan Liu', 'Tat-Seng Chua', 'Maosong Sun'] | ['cs.CL'] | Traditional feedback learning for hallucination reduction relies on
labor-intensive manual labeling or expensive proprietary models. This leaves
the community without foundational knowledge about how to build high-quality
feedback with open-source MLLMs. In this work, we introduce RLAIF-V, a novel
framework that aligns... | 2024-05-27T14:37:01Z | Project Website: https://github.com/RLHF-V/RLAIF-V | null | null | RLAIF-V: Open-Source AI Feedback Leads to Super GPT-4V Trustworthiness | ['Tianyu Yu', 'Haoye Zhang', 'Yuan Yao', 'Yunkai Dang', 'Dawn Chen', 'Xiaoman Lu', 'Ganqu Cui', 'Taiwen He', 'Zhiyuan Liu', 'Tat-Seng Chua', 'Maosong Sun'] | 2,024 | null | 35 | 75 | ['Computer Science'] |
2,405.17251 | GenWarp: Single Image to Novel Views with Semantic-Preserving Generative
Warping | ['Junyoung Seo', 'Kazumi Fukuda', 'Takashi Shibuya', 'Takuya Narihira', 'Naoki Murata', 'Shoukang Hu', 'Chieh-Hsin Lai', 'Seungryong Kim', 'Yuki Mitsufuji'] | ['cs.CV'] | Generating novel views from a single image remains a challenging task due to
the complexity of 3D scenes and the limited diversity in the existing
multi-view datasets to train a model on. Recent research combining large-scale
text-to-image (T2I) models with monocular depth estimation (MDE) has shown
promise in handling... | 2024-05-27T15:07:04Z | Accepted to NeurIPS 2024 / Project page:
https://GenWarp-NVS.github.io | null | null | null | null | null | null | null | null | null |
2,405.17382 | ReMoDetect: Reward Models Recognize Aligned LLM's Generations | ['Hyunseok Lee', 'Jihoon Tack', 'Jinwoo Shin'] | ['cs.LG', 'cs.CL'] | The remarkable capabilities and easy accessibility of large language models
(LLMs) have significantly increased societal risks (e.g., fake news
generation), necessitating the development of LLM-generated text (LGT)
detection methods for safe usage. However, detecting LGTs is challenging due to
the vast number of LLMs, ... | 2024-05-27T17:38:33Z | Published as a conference proceeding for NeurIPS 2024 | null | null | null | null | null | null | null | null | null |
2,405.17398 | Vista: A Generalizable Driving World Model with High Fidelity and
Versatile Controllability | ['Shenyuan Gao', 'Jiazhi Yang', 'Li Chen', 'Kashyap Chitta', 'Yihang Qiu', 'Andreas Geiger', 'Jun Zhang', 'Hongyang Li'] | ['cs.CV', 'cs.AI'] | World models can foresee the outcomes of different actions, which is of
paramount importance for autonomous driving. Nevertheless, existing driving
world models still have limitations in generalization to unseen environments,
prediction fidelity of critical details, and action controllability for
flexible application. ... | 2024-05-27T17:49:15Z | NeurIPS 2024. Code and model: https://github.com/OpenDriveLab/Vista,
demo page: https://vista-demo.github.io | null | null | null | null | null | null | null | null | null |
2,405.17399 | Transformers Can Do Arithmetic with the Right Embeddings | ['Sean McLeish', 'Arpit Bansal', 'Alex Stein', 'Neel Jain', 'John Kirchenbauer', 'Brian R. Bartoldson', 'Bhavya Kailkhura', 'Abhinav Bhatele', 'Jonas Geiping', 'Avi Schwarzschild', 'Tom Goldstein'] | ['cs.LG', 'cs.AI'] | The poor performance of transformers on arithmetic tasks seems to stem in
large part from their inability to keep track of the exact position of each
digit inside of a large span of digits. We mend this problem by adding an
embedding to each digit that encodes its position relative to the start of the
number. In additi... | 2024-05-27T17:49:18Z | null | null | null | Transformers Can Do Arithmetic with the Right Embeddings | ['Sean McLeish', 'Arpit Bansal', 'Alex Stein', 'Neel Jain', 'John Kirchenbauer', 'Brian R. Bartoldson', 'B. Kailkhura', 'A. Bhatele', 'Jonas Geiping', 'Avi Schwarzschild', 'Tom Goldstein'] | 2,024 | Neural Information Processing Systems | 37 | 48 | ['Computer Science'] |
2,405.17428 | NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding
Models | ['Chankyu Lee', 'Rajarshi Roy', 'Mengyao Xu', 'Jonathan Raiman', 'Mohammad Shoeybi', 'Bryan Catanzaro', 'Wei Ping'] | ['cs.CL', 'cs.AI', 'cs.IR', 'cs.LG'] | Decoder-only LLM-based embedding models are beginning to outperform BERT or
T5-based embedding models in general-purpose text embedding tasks, including
dense vector-based retrieval. In this work, we introduce NV-Embed,
incorporating architectural designs, training procedures, and curated datasets
to significantly enha... | 2024-05-27T17:59:45Z | ICLR 2025 (Spotlight). We open-source the model at:
https://huggingface.co/nvidia/NV-Embed-v2 | null | null | null | null | null | null | null | null | null |
2,405.1743 | Matryoshka Multimodal Models | ['Mu Cai', 'Jianwei Yang', 'Jianfeng Gao', 'Yong Jae Lee'] | ['cs.CV', 'cs.AI', 'cs.CL', 'cs.LG'] | Large Multimodal Models (LMMs) such as LLaVA have shown strong performance in
visual-linguistic reasoning. These models first embed images into a fixed large
number of visual tokens and then feed them into a Large Language Model (LLM).
However, this design causes an excessive number of tokens for dense visual
scenarios... | 2024-05-27T17:59:56Z | Project Page: https://matryoshka-mm.github.io/ | null | null | null | null | null | null | null | null | null |
2,405.17455 | WeatherFormer: A Pretrained Encoder Model for Learning Robust Weather
Representations from Small Datasets | ['Adib Hasan', 'Mardavij Roozbehani', 'Munther Dahleh'] | ['cs.CV', 'cs.AI', 'cs.LG', 'physics.ao-ph', 'stat.ML'] | This paper introduces WeatherFormer, a transformer encoder-based model
designed to learn robust weather features from minimal observations. It
addresses the challenge of modeling complex weather dynamics from small
datasets, a bottleneck for many prediction tasks in agriculture, epidemiology,
and climate science. Weath... | 2024-05-22T17:43:46Z | null | null | null | null | null | null | null | null | null | null |
2,405.17537 | CLIBD: Bridging Vision and Genomics for Biodiversity Monitoring at Scale | ['ZeMing Gong', 'Austin T. Wang', 'Xiaoliang Huo', 'Joakim Bruslund Haurum', 'Scott C. Lowe', 'Graham W. Taylor', 'Angel X. Chang'] | ['cs.AI', 'cs.CL', 'cs.CV'] | Measuring biodiversity is crucial for understanding ecosystem health. While
prior works have developed machine learning models for taxonomic classification
of photographic images and DNA separately, in this work, we introduce a
multimodal approach combining both, using CLIP-style contrastive learning to
align images, b... | 2024-05-27T17:57:48Z | 31 pages with 14 figures | null | null | null | null | null | null | null | null | null |
2,405.17743 | ORLM: A Customizable Framework in Training Large Models for Automated
Optimization Modeling | ['Chenyu Huang', 'Zhengyang Tang', 'Shixi Hu', 'Ruoqing Jiang', 'Xin Zheng', 'Dongdong Ge', 'Benyou Wang', 'Zizhuo Wang'] | ['cs.CL', 'cs.AI', 'cs.CE', 'cs.LG'] | Optimization modeling plays a critical role in the application of Operations
Research (OR) tools to address real-world problems, yet they pose challenges
and require extensive expertise from OR experts. With the advent of large
language models (LLMs), new opportunities have emerged to streamline and
automate such task.... | 2024-05-28T01:55:35Z | accepted by Operations Research | null | null | ORLM: A Customizable Framework in Training Large Models for Automated Optimization Modeling | ['Chenyu Huang', 'Zhengyang Tang', 'Shixi Hu', 'Ruoqing Jiang', 'Xin Zheng', 'Dongdong Ge', 'Benyou Wang', 'Zizhuo Wang'] | 2,024 | null | 6 | 0 | ['Computer Science'] |
2,405.17767 | Linguistic Collapse: Neural Collapse in (Large) Language Models | ['Robert Wu', 'Vardan Papyan'] | ['cs.LG', 'cs.CL', 'stat.ML', '68T07 (Primary) 68T50 (Secondary)', 'I.2.6; I.2.7'] | Neural collapse ($\mathcal{NC}$) is a phenomenon observed in classification
tasks where top-layer representations collapse into their class means, which
become equinorm, equiangular and aligned with the classifiers. These behaviours
-- associated with generalization and robustness -- would manifest under
specific condi... | 2024-05-28T02:46:11Z | NeurIPS 2024; 35 pages; 30 figures; reverted to log mean norms for
NC2 | null | null | Linguistic Collapse: Neural Collapse in (Large) Language Models | ['Robert Wu', 'Vardan Papyan'] | 2,024 | Neural Information Processing Systems | 16 | 123 | ['Computer Science', 'Mathematics'] |
2,405.17829 | LDMol: A Text-to-Molecule Diffusion Model with Structurally Informative
Latent Space Surpasses AR Models | ['Jinho Chang', 'Jong Chul Ye'] | ['cs.LG', 'cs.AI'] | With the emergence of diffusion models as a frontline generative model, many
researchers have proposed molecule generation techniques with conditional
diffusion models. However, the unavoidable discreteness of a molecule makes it
difficult for a diffusion model to connect raw data with highly complex
conditions like na... | 2024-05-28T04:59:13Z | Poster in ICML 2025; 19 pages, 13 figures | null | null | null | null | null | null | null | null | null |
2,405.17842 | MMDisCo: Multi-Modal Discriminator-Guided Cooperative Diffusion for
Joint Audio and Video Generation | ['Akio Hayakawa', 'Masato Ishii', 'Takashi Shibuya', 'Yuki Mitsufuji'] | ['cs.CV', 'cs.LG', 'cs.MM', 'cs.SD', 'eess.AS'] | This study aims to construct an audio-video generative model with minimal
computational cost by leveraging pre-trained single-modal generative models for
audio and video. To achieve this, we propose a novel method that guides
single-modal models to cooperatively generate well-aligned samples across
modalities. Specific... | 2024-05-28T05:43:03Z | ICLR 2025 | null | null | null | null | null | null | null | null | null |
2,405.17846 | Safety Control of Service Robots with LLMs and Embodied Knowledge Graphs | ['Yong Qi', 'Gabriel Kyebambo', 'Siyuan Xie', 'Wei Shen', 'Shenghui Wang', 'Bitao Xie', 'Bin He', 'Zhipeng Wang', 'Shuo Jiang'] | ['cs.RO', 'cs.AI'] | Safety limitations in service robotics across various industries have raised
significant concerns about the need for robust mechanisms ensuring that robots
adhere to safe practices, thereby preventing actions that might harm humans or
cause property damage. Despite advances, including the integration of Knowledge
Graph... | 2024-05-28T05:50:25Z | null | null | null | Safety Control of Service Robots with LLMs and Embodied Knowledge Graphs | ['Yong Qi', 'Gabriel Kyebambo', 'Siyuan Xie', 'Wei Shen', 'Shenghui Wang', 'Bitao Xie', 'Bin He', 'Zhipeng Wang', 'Shuo Jiang'] | 2,024 | arXiv.org | 2 | 55 | ['Computer Science'] |
2,405.17873 | MixDQ: Memory-Efficient Few-Step Text-to-Image Diffusion Models with
Metric-Decoupled Mixed Precision Quantization | ['Tianchen Zhao', 'Xuefei Ning', 'Tongcheng Fang', 'Enshu Liu', 'Guyue Huang', 'Zinan Lin', 'Shengen Yan', 'Guohao Dai', 'Yu Wang'] | ['cs.CV', 'cs.AI'] | Diffusion models have achieved significant visual generation quality.
However, their significant computational and memory costs pose challenge for
their application on resource-constrained mobile devices or even desktop GPUs.
Recent few-step diffusion models reduces the inference time by reducing the
denoising steps. H... | 2024-05-28T06:50:58Z | Project Page: https://a-suozhang.xyz/mixdq.github.io/ | null | null | null | null | null | null | null | null | null |
2,405.17933 | ToonCrafter: Generative Cartoon Interpolation | ['Jinbo Xing', 'Hanyuan Liu', 'Menghan Xia', 'Yong Zhang', 'Xintao Wang', 'Ying Shan', 'Tien-Tsin Wong'] | ['cs.CV'] | We introduce ToonCrafter, a novel approach that transcends traditional
correspondence-based cartoon video interpolation, paving the way for generative
interpolation. Traditional methods, that implicitly assume linear motion and
the absence of complicated phenomena like dis-occlusion, often struggle with
the exaggerated... | 2024-05-28T07:58:33Z | Project page: https://doubiiu.github.io/projects/ToonCrafter/ | null | null | null | null | null | null | null | null | null |
2,405.17976 | Yuan 2.0-M32: Mixture of Experts with Attention Router | ['Shaohua Wu', 'Jiangang Luo', 'Xi Chen', 'Lingjun Li', 'Xudong Zhao', 'Tong Yu', 'Chao Wang', 'Yue Wang', 'Fei Wang', 'Weixu Qiao', 'Houbo He', 'Zeru Zhang', 'Zeyu Sun', 'Junxiong Mao', 'Chong Shen'] | ['cs.AI', 'cs.CL'] | Yuan 2.0-M32, with a similar base architecture as Yuan-2.0 2B, uses a
mixture-of-experts architecture with 32 experts of which 2 experts are active.
A new router network, Attention Router, is proposed and adopted for a more
efficient selection of experts, which improves the accuracy compared to the
model with classical... | 2024-05-28T09:05:08Z | 14 pages,3 figures, 7 tables | null | null | Yuan 2.0-M32: Mixture of Experts with Attention Router | ['Shaohua Wu', 'Jiangang Luo', 'Xi Chen', 'Lingjun Li', 'Xudong Zhao', 'Tong Yu', 'Chao Wang', 'Yue Wang', 'Fei Wang', 'Weixu Qiao', 'Houbo He', 'Zeru Zhang', 'Zeyu Sun', 'Junxiong Mao', 'Chong Shen'] | 2,024 | arXiv.org | 11 | 2 | ['Computer Science'] |
2,405.17977 | Aligning to Thousands of Preferences via System Message Generalization | ['Seongyun Lee', 'Sue Hyun Park', 'Seungone Kim', 'Minjoon Seo'] | ['cs.CL'] | Although humans inherently have diverse values, current large language model
(LLM) alignment methods often assume that aligning LLMs with the general
public's preferences is optimal. A major challenge in adopting a more
individualized approach to LLM alignment is its lack of scalability, as it
involves repeatedly acqui... | 2024-05-28T09:06:18Z | Accepted to NeurIPS 2024 | null | null | Aligning to Thousands of Preferences via System Message Generalization | ['Seongyun Lee', 'Sue Hyun Park', 'Seungone Kim', 'Minjoon Seo'] | 2,024 | Neural Information Processing Systems | 49 | 90 | ['Computer Science'] |
2,405.18357 | Faithful Logical Reasoning via Symbolic Chain-of-Thought | ['Jundong Xu', 'Hao Fei', 'Liangming Pan', 'Qian Liu', 'Mong-Li Lee', 'Wynne Hsu'] | ['cs.CL'] | While the recent Chain-of-Thought (CoT) technique enhances the reasoning
ability of large language models (LLMs) with the theory of mind, it might still
struggle in handling logical reasoning that relies much on symbolic expressions
and rigid deducing rules. To strengthen the logical reasoning capability of
LLMs, we pr... | 2024-05-28T16:55:33Z | Accepted by ACL 2024 (main proceeding) | null | null | null | null | null | null | null | null | null |
2,405.18369 | PromptWizard: Task-Aware Prompt Optimization Framework | ['Eshaan Agarwal', 'Joykirat Singh', 'Vivek Dani', 'Raghav Magazine', 'Tanuja Ganu', 'Akshay Nambi'] | ['cs.CL', 'cs.AI', 'cs.LG'] | Large language models (LLMs) have transformed AI across diverse domains, with
prompting being central to their success in guiding model outputs. However,
manual prompt engineering is both labor-intensive and domain-specific,
necessitating the need for automated solutions. We introduce PromptWizard, a
novel, fully autom... | 2024-05-28T17:08:31Z | null | null | null | null | null | null | null | null | null | null |
2,405.18392 | Scaling Laws and Compute-Optimal Training Beyond Fixed Training
Durations | ['Alexander Hägele', 'Elie Bakouch', 'Atli Kosson', 'Loubna Ben Allal', 'Leandro Von Werra', 'Martin Jaggi'] | ['cs.LG'] | Scale has become a main ingredient in obtaining strong machine learning
models. As a result, understanding a model's scaling properties is key to
effectively designing both the right training setup as well as future
generations of architectures. In this work, we argue that scale and training
research has been needlessl... | 2024-05-28T17:33:54Z | Spotlight at NeurIPS 2024 | null | null | null | null | null | null | null | null | null |
2,405.18407 | Phased Consistency Models | ['Fu-Yun Wang', 'Zhaoyang Huang', 'Alexander William Bergman', 'Dazhong Shen', 'Peng Gao', 'Michael Lingelbach', 'Keqiang Sun', 'Weikang Bian', 'Guanglu Song', 'Yu Liu', 'Xiaogang Wang', 'Hongsheng Li'] | ['cs.LG', 'cs.CV'] | Consistency Models (CMs) have made significant progress in accelerating the
generation of diffusion models. However, their application to high-resolution,
text-conditioned image generation in the latent space remains unsatisfactory.
In this paper, we identify three key flaws in the current design of Latent
Consistency ... | 2024-05-28T17:47:19Z | NeurIPS 2024 | null | null | Phased Consistency Models | ['Fu-Yun Wang', 'Zhaoyang Huang', 'Alexander William Bergman', 'Dazhong Shen', 'Peng Gao', 'Michael Lingelbach', 'Keqiang Sun', 'Weikang Bian', 'Guanglu Song', 'Yu Liu', 'Hongsheng Li', 'Xiaogang Wang'] | 2,024 | Neural Information Processing Systems | 12 | 0 | ['Computer Science'] |
2,405.18416 | 3D StreetUnveiler with Semantic-aware 2DGS -- a simple baseline | ['Jingwei Xu', 'Yikai Wang', 'Yiqun Zhao', 'Yanwei Fu', 'Shenghua Gao'] | ['cs.CV'] | Unveiling an empty street from crowded observations captured by in-car
cameras is crucial for autonomous driving. However, removing all temporarily
static objects, such as stopped vehicles and standing pedestrians, presents a
significant challenge. Unlike object-centric 3D inpainting, which relies on
thorough observati... | 2024-05-28T17:57:12Z | Project page: https://streetunveiler.github.io | null | null | null | null | null | null | null | null | null |
2,405.18425 | ViG: Linear-complexity Visual Sequence Learning with Gated Linear
Attention | ['Bencheng Liao', 'Xinggang Wang', 'Lianghui Zhu', 'Qian Zhang', 'Chang Huang'] | ['cs.CV', 'cs.AI'] | Recently, linear complexity sequence modeling networks have achieved modeling
capabilities similar to Vision Transformers on a variety of computer vision
tasks, while using fewer FLOPs and less memory. However, their advantage in
terms of actual runtime speed is not significant. To address this issue, we
introduce Gate... | 2024-05-28T17:59:21Z | Work in progress. Code is available at
\url{https://github.com/hustvl/ViG} | null | null | ViG: Linear-complexity Visual Sequence Learning with Gated Linear Attention | ['Bencheng Liao', 'Xinggang Wang', 'Lianghui Zhu', 'Qian Zhang', 'Chang Huang'] | 2,024 | AAAI Conference on Artificial Intelligence | 4 | 116 | ['Computer Science'] |
2,405.18503 | SoundCTM: Unifying Score-based and Consistency Models for Full-band
Text-to-Sound Generation | ['Koichi Saito', 'Dongjun Kim', 'Takashi Shibuya', 'Chieh-Hsin Lai', 'Zhi Zhong', 'Yuhta Takida', 'Yuki Mitsufuji'] | ['cs.SD', 'cs.LG', 'eess.AS'] | Sound content creation, essential for multimedia works such as video games
and films, often involves extensive trial-and-error, enabling creators to
semantically reflect their artistic ideas and inspirations, which evolve
throughout the creation process, into the sound. Recent high-quality
diffusion-based Text-to-Sound... | 2024-05-28T18:14:52Z | Audio samples: https://anonymus-soundctm.github.io/soundctm_iclr/.
Codes: https://github.com/sony/soundctm. Checkpoints:
https://huggingface.co/Sony/soundctm | null | null | SoundCTM: Unifying Score-based and Consistency Models for Full-band Text-to-Sound Generation | ['Koichi Saito', 'Dongjun Kim', 'Takashi Shibuya', 'Chieh-Hsin Lai', 'Zhi-Wei Zhong', 'Yuhta Takida', 'Yuki Mitsufuji'] | 2,024 | International Conference on Learning Representations | 4 | 65 | ['Computer Science', 'Engineering'] |
2,405.18585 | Transfer Learning for Emulating Ocean Climate Variability across $CO_2$
forcing | ['Surya Dheeshjith', 'Adam Subel', 'Shubham Gupta', 'Alistair Adcroft', 'Carlos Fernandez-Granda', 'Julius Busecke', 'Laure Zanna'] | ['physics.ao-ph'] | With the success of machine learning (ML) applied to climate reaching further
every day, emulators have begun to show promise not only for weather but for
multi-year time scales in the atmosphere. Similar work for the ocean remains
nascent, with state-of-the-art limited to models running for shorter time
scales or only... | 2024-05-28T21:05:21Z | null | null | null | Transfer Learning for Emulating Ocean Climate Variability across $CO_2$ forcing | ['Surya Dheeshjith', 'Adam Subel', 'Shubham Gupta', 'Alistair Adcroft', 'C. Fernandez‐Granda', 'Julius Busecke', 'Laure Zanna'] | 2,024 | null | 3 | 25 | ['Physics'] |
2,405.18654 | Mitigating Object Hallucination in MLLMs via Data-augmented Phrase-level
Alignment | ['Pritam Sarkar', 'Sayna Ebrahimi', 'Ali Etemad', 'Ahmad Beirami', 'Sercan Ö. Arık', 'Tomas Pfister'] | ['cs.CV'] | Despite their significant advancements, Multimodal Large Language Models
(MLLMs) often generate factually inaccurate information, referred to as
hallucination. In this work, we address object hallucinations in MLLMs, where
information is generated about an object not present in the input image. We
introduce Data-augmen... | 2024-05-28T23:36:00Z | Published in ICLR 2025 | null | null | null | null | null | null | null | null | null |
2,405.18749 | A SARS-CoV-2 Interaction Dataset and VHH Sequence Corpus for Antibody
Language Models | ['Hirofumi Tsuruta', 'Hiroyuki Yamazaki', 'Ryota Maeda', 'Ryotaro Tamura', 'Akihiro Imura'] | ['cs.LG', 'q-bio.GN'] | Antibodies are crucial proteins produced by the immune system to eliminate
harmful foreign substances and have become pivotal therapeutic agents for
treating human diseases. To accelerate the discovery of antibody therapeutics,
there is growing interest in constructing language models using antibody
sequences. However,... | 2024-05-29T04:22:18Z | null | null | null | null | null | null | null | null | null | null |
2,405.18952 | Are You Sure? Rank Them Again: Repeated Ranking For Better Preference
Datasets | ['Peter Devine'] | ['cs.CL', 'cs.AI', 'cs.LG'] | Training Large Language Models (LLMs) with Reinforcement Learning from AI
Feedback (RLAIF) aligns model outputs more closely with human preferences. This
involves an evaluator model ranking multiple candidate responses to user
prompts. However, the rankings from popular evaluator models such as GPT-4 can
be inconsisten... | 2024-05-29T10:08:31Z | null | null | null | null | null | null | null | null | null | null |
2,405.18991 | EasyAnimate: A High-Performance Long Video Generation Method based on
Transformer Architecture | ['Jiaqi Xu', 'Xinyi Zou', 'Kunzhe Huang', 'Yunkuo Chen', 'Bo Liu', 'MengLi Cheng', 'Xing Shi', 'Jun Huang'] | ['cs.CV', 'cs.CL', 'cs.MM'] | This paper presents EasyAnimate, an advanced method for video generation that
leverages the power of transformer architecture for high-performance outcomes.
We have expanded the DiT framework originally designed for 2D image synthesis
to accommodate the complexities of 3D video generation by incorporating a
motion modu... | 2024-05-29T11:11:07Z | 8 pages, 6 figures | null | null | null | null | null | null | null | null | null |
2,405.19076 | Cephalo: Multi-Modal Vision-Language Models for Bio-Inspired Materials
Analysis and Design | ['Markus J. Buehler'] | ['cs.CV', 'cond-mat.mes-hall', 'cond-mat.mtrl-sci', 'cs.CL', 'cs.LG'] | We present Cephalo, a series of multimodal vision large language models
(V-LLMs) designed for materials science applications, integrating visual and
linguistic data for enhanced understanding. A key innovation of Cephalo is its
advanced dataset generation method. Cephalo is trained on integrated image and
text data fro... | 2024-05-29T13:34:32Z | null | null | null | null | null | null | null | null | null | null |
2,405.19101 | Poseidon: Efficient Foundation Models for PDEs | ['Maximilian Herde', 'Bogdan Raonić', 'Tobias Rohner', 'Roger Käppeli', 'Roberto Molinaro', 'Emmanuel de Bézenac', 'Siddhartha Mishra'] | ['cs.LG'] | We introduce Poseidon, a foundation model for learning the solution operators
of PDEs. It is based on a multiscale operator transformer, with
time-conditioned layer norms that enable continuous-in-time evaluations. A
novel training strategy leveraging the semi-group property of time-dependent
PDEs to allow for signific... | 2024-05-29T14:06:51Z | null | null | null | null | null | null | null | null | null | null |
2,405.19265 | AlchemistCoder: Harmonizing and Eliciting Code Capability by Hindsight
Tuning on Multi-source Data | ['Zifan Song', 'Yudong Wang', 'Wenwei Zhang', 'Kuikun Liu', 'Chengqi Lyu', 'Demin Song', 'Qipeng Guo', 'Hang Yan', 'Dahua Lin', 'Kai Chen', 'Cairong Zhao'] | ['cs.CL'] | Open-source Large Language Models (LLMs) and their specialized variants,
particularly Code LLMs, have recently delivered impressive performance.
However, previous Code LLMs are typically fine-tuned on single-source data with
limited quality and diversity, which may insufficiently elicit the potential of
pre-trained Cod... | 2024-05-29T16:57:33Z | Preprint with 20 pages and 20 figures. Source code and models at
https://github.com/InternLM/AlchemistCoder | null | null | null | null | null | null | null | null | null |
2,405.19298 | Adaptive Image Quality Assessment via Teaching Large Multimodal Model to
Compare | ['Hanwei Zhu', 'Haoning Wu', 'Yixuan Li', 'Zicheng Zhang', 'Baoliang Chen', 'Lingyu Zhu', 'Yuming Fang', 'Guangtao Zhai', 'Weisi Lin', 'Shiqi Wang'] | ['cs.CV', 'eess.IV'] | While recent advancements in large multimodal models (LMMs) have
significantly improved their abilities in image quality assessment (IQA)
relying on absolute quality rating, how to transfer reliable relative quality
comparison outputs to continuous perceptual quality scores remains largely
unexplored. To address this g... | 2024-05-29T17:26:09Z | null | null | null | Adaptive Image Quality Assessment via Teaching Large Multimodal Model to Compare | ['Hanwei Zhu', 'Haoning Wu', 'Yixuan Li', 'Zicheng Zhang', 'Baoliang Chen', 'Lingyu Zhu', 'Yuming Fang', 'Guangtao Zhai', 'Weisi Lin', 'Shiqi Wang'] | 2,024 | Neural Information Processing Systems | 23 | 76 | ['Computer Science', 'Engineering'] |
2,405.19315 | Matryoshka Query Transformer for Large Vision-Language Models | ['Wenbo Hu', 'Zi-Yi Dou', 'Liunian Harold Li', 'Amita Kamath', 'Nanyun Peng', 'Kai-Wei Chang'] | ['cs.CV', 'cs.CL', 'cs.LG'] | Large Vision-Language Models (LVLMs) typically encode an image into a fixed
number of visual tokens (e.g., 576) and process these tokens with a language
model. Despite their strong performance, LVLMs face challenges in adapting to
varying computational constraints. This raises the question: can we achieve
flexibility i... | 2024-05-29T17:39:42Z | Preprint. Our code and model are publicly available at
https://github.com/gordonhu608/MQT-LLaVA | null | null | Matryoshka Query Transformer for Large Vision-Language Models | ['Wenbo Hu', 'Zi-Yi Dou', 'Liunian Harold Li', 'Amita Kamath', 'Nanyun Peng', 'Kai-Wei Chang'] | 2,024 | Neural Information Processing Systems | 10 | 44 | ['Computer Science'] |
2,405.19332 | Self-Exploring Language Models: Active Preference Elicitation for Online
Alignment | ['Shenao Zhang', 'Donghan Yu', 'Hiteshi Sharma', 'Han Zhong', 'Zhihan Liu', 'Ziyi Yang', 'Shuohang Wang', 'Hany Hassan', 'Zhaoran Wang'] | ['cs.LG', 'cs.AI'] | Preference optimization, particularly through Reinforcement Learning from
Human Feedback (RLHF), has achieved significant success in aligning Large
Language Models (LLMs) to adhere to human intentions. Unlike offline alignment
with a fixed dataset, online feedback collection from humans or AI on model
generations typic... | 2024-05-29T17:59:07Z | null | null | null | null | null | null | null | null | null | null |
2,405.1936 | ART: Automatic Red-teaming for Text-to-Image Models to Protect Benign
Users | ['Guanlin Li', 'Kangjie Chen', 'Shudong Zhang', 'Jie Zhang', 'Tianwei Zhang'] | ['cs.CR', 'cs.AI'] | Large-scale pre-trained generative models are taking the world by storm, due
to their abilities in generating creative content. Meanwhile, safeguards for
these generative models are developed, to protect users' rights and safety,
most of which are designed for large language models. Existing methods
primarily focus on ... | 2024-05-24T07:44:27Z | Accepted by NeurIPS 2024 | null | null | null | null | null | null | null | null | null |
2,405.19495 | Qiskit Code Assistant: Training LLMs for generating Quantum Computing
Code | ['Nicolas Dupuis', 'Luca Buratti', 'Sanjay Vishwakarma', 'Aitana Viudes Forrat', 'David Kremer', 'Ismael Faro', 'Ruchir Puri', 'Juan Cruz-Benito'] | ['quant-ph', 'cs.AI'] | Code Large Language Models (Code LLMs) have emerged as powerful tools,
revolutionizing the software development landscape by automating the coding
process and reducing time and effort required to build applications. This paper
focuses on training Code LLMs to specialize in the field of quantum computing.
We begin by di... | 2024-05-29T20:21:00Z | null | null | null | Qiskit Code Assistant: Training LLMs for generating Quantum Computing Code | ['Nicolas Dupuis', 'Luca Buratti', 'Sanjay Vishwakarma', 'Aitana Viudes Forrat', 'David Kremer', 'Ismael Faro', 'Ruchir Puri', 'Juan Cruz-Benito'] | 2,024 | 2024 IEEE LLM Aided Design Workshop (LAD) | 11 | 39 | ['Computer Science', 'Physics'] |
2,405.19538 | CheXpert Plus: Augmenting a Large Chest X-ray Dataset with Text
Radiology Reports, Patient Demographics and Additional Image Formats | ['Pierre Chambon', 'Jean-Benoit Delbrouck', 'Thomas Sounack', 'Shih-Cheng Huang', 'Zhihong Chen', 'Maya Varma', 'Steven QH Truong', 'Chu The Chuong', 'Curtis P. Langlotz'] | ['cs.CL', 'cs.AI', 'cs.CV', 'cs.LG'] | Since the release of the original CheXpert paper five years ago, CheXpert has
become one of the most widely used and cited clinical AI datasets. The
emergence of vision language models has sparked an increase in demands for
sharing reports linked to CheXpert images, along with a growing interest among
AI fairness resea... | 2024-05-29T21:48:56Z | 13 pages Updated title | null | null | CheXpert Plus: Augmenting a Large Chest X-ray Dataset with Text Radiology Reports, Patient Demographics and Additional Image Formats | ['Pierre J. Chambon', 'Jean-Benoit Delbrouck', 'Thomas Sounack', 'Shih-Cheng Huang', 'Zhihong Chen', 'Maya Varma', 'Steven Q. H. Truong', 'Chu The Chuong', 'Curtis P. Langlotz'] | 2,024 | arXiv.org | 16 | 30 | ['Computer Science'] |
2,405.1967 | One Token Can Help! Learning Scalable and Pluggable Virtual Tokens for
Retrieval-Augmented Large Language Models | ['Yutao Zhu', 'Zhaoheng Huang', 'Zhicheng Dou', 'Ji-Rong Wen'] | ['cs.CL'] | Retrieval-augmented generation (RAG) is a promising way to improve large
language models (LLMs) for generating more factual, accurate, and up-to-date
content. Existing methods either optimize prompts to guide LLMs in leveraging
retrieved information or directly fine-tune LLMs to adapt to RAG scenarios.
Although fine-tu... | 2024-05-30T03:44:54Z | Accepted by AAAI 2025, repo: https://github.com/DaoD/SPRING/ | null | null | One Token Can Help! Learning Scalable and Pluggable Virtual Tokens for Retrieval-Augmented Large Language Models | ['Yutao Zhu', 'Zhaoheng Huang', 'Zhicheng Dou', 'Ji-Rong Wen'] | 2,024 | AAAI Conference on Artificial Intelligence | 6 | 65 | ['Computer Science'] |
2,405.19715 | SpecDec++: Boosting Speculative Decoding via Adaptive Candidate Lengths | ['Kaixuan Huang', 'Xudong Guo', 'Mengdi Wang'] | ['cs.CL', 'cs.AI', 'cs.LG'] | Speculative decoding reduces the inference latency of a target large language
model via utilizing a smaller and faster draft model. Its performance depends
on a hyperparameter K -- the candidate length, i.e., the number of candidate
tokens for the target model to verify in each round. However, previous methods
often us... | 2024-05-30T05:49:38Z | Accepted to COLM 2025 | null | null | null | null | null | null | null | null | null |
2,405.19783 | Instruction-Guided Visual Masking | ['Jinliang Zheng', 'Jianxiong Li', 'Sijie Cheng', 'Yinan Zheng', 'Jiaming Li', 'Jihao Liu', 'Yu Liu', 'Jingjing Liu', 'Xianyuan Zhan'] | ['cs.CV', 'cs.AI', 'cs.LG', 'cs.RO'] | Instruction following is crucial in contemporary LLM. However, when extended
to multimodal setting, it often suffers from misalignment between specific
textual instruction and targeted local region of an image. To achieve more
accurate and nuanced multimodal instruction following, we introduce
Instruction-guided Visual... | 2024-05-30T07:48:32Z | NeurIPS 2024 | null | null | null | null | null | null | null | null | null |
2,405.19941 | Synthetic Patients: Simulating Difficult Conversations with Multimodal
Generative AI for Medical Education | ['Simon N. Chu', 'Alex J. Goodell'] | ['cs.HC', 'cs.CY'] | Problem: Effective patient-centered communication is a core competency for
physicians. However, both seasoned providers and medical trainees report
decreased confidence in leading conversations on sensitive topics such as goals
of care or end-of-life discussions. The significant administrative burden and
the resources ... | 2024-05-30T11:02:08Z | null | null | null | null | null | null | null | null | null | null |
2,405.20053 | Would I Lie To You? Inference Time Alignment of Language Models using
Direct Preference Heads | ['Avelina Asada Hadji-Kyriacou', 'Ognjen Arandjelovic'] | ['cs.CL', 'cs.AI', 'cs.LG'] | Pre-trained Language Models (LMs) exhibit strong zero-shot and in-context
learning capabilities; however, their behaviors are often difficult to control.
By utilizing Reinforcement Learning from Human Feedback (RLHF), it is possible
to fine-tune unsupervised LMs to follow instructions and produce outputs that
reflect h... | 2024-05-30T13:38:52Z | null | null | null | null | null | null | null | null | null | null |
2,405.20079 | Student Answer Forecasting: Transformer-Driven Answer Choice Prediction
for Language Learning | ['Elena Grazia Gado', 'Tommaso Martorella', 'Luca Zunino', 'Paola Mejia-Domenzain', 'Vinitra Swamy', 'Jibril Frej', 'Tanja Käser'] | ['cs.CL', 'cs.CY', 'cs.LG'] | Intelligent Tutoring Systems (ITS) enhance personalized learning by
predicting student answers to provide immediate and customized instruction.
However, recent research has primarily focused on the correctness of the answer
rather than the student's performance on specific answer choices, limiting
insights into student... | 2024-05-30T14:09:43Z | Accepted as a poster paper at EDM 2024: 17th International Conference
on Educational Data Mining in Atlanta, USA | null | null | null | null | null | null | null | null | null |
2,405.20145 | Heidelberg-Boston @ SIGTYP 2024 Shared Task: Enhancing Low-Resource
Language Analysis With Character-Aware Hierarchical Transformers | ['Frederick Riemenschneider', 'Kevin Krahn'] | ['cs.CL', 'I.2.7'] | Historical languages present unique challenges to the NLP community, with one
prominent hurdle being the limited resources available in their closed corpora.
This work describes our submission to the constrained subtask of the SIGTYP
2024 shared task, focusing on PoS tagging, morphological tagging, and
lemmatization fo... | 2024-05-30T15:23:34Z | Accepted for publication at the 6th Workshop on Research in
Computational Linguistic Typology and Multilingual NLP (SIGTYP-WS) 2024; 11
pages, 1 figure, 9 tables | null | null | null | null | null | null | null | null | null |
2,405.20204 | Jina CLIP: Your CLIP Model Is Also Your Text Retriever | ['Andreas Koukounas', 'Georgios Mastrapas', 'Michael Günther', 'Bo Wang', 'Scott Martens', 'Isabelle Mohr', 'Saba Sturua', 'Mohammad Kalim Akram', 'Joan Fontanals Martínez', 'Saahil Ognawala', 'Susana Guzman', 'Maximilian Werk', 'Nan Wang', 'Han Xiao'] | ['cs.CL', 'cs.AI', 'cs.CV', 'cs.IR', '68T50', 'I.2.7'] | Contrastive Language-Image Pretraining (CLIP) is widely used to train models
to align images and texts in a common embedding space by mapping them to
fixed-sized vectors. These models are key to multimodal information retrieval
and related tasks. However, CLIP models generally underperform in text-only
tasks compared t... | 2024-05-30T16:07:54Z | 4 pages, MFM-EAI@ICML2024 | null | null | Jina CLIP: Your CLIP Model Is Also Your Text Retriever | ['Andreas Koukounas', 'Georgios Mastrapas', 'Michael Günther', 'Bo Wang', 'Scott Martens', 'Isabelle Mohr', 'Saba Sturua', 'Mohammad Kalim Akram', "Joan Fontanals Mart'inez", 'Saahil Ognawala', 'Susana Guzman', 'Maximilian Werk', 'Nan Wang', 'Han Xiao'] | 2,024 | arXiv.org | 18 | 36 | ['Computer Science'] |
2,405.20215 | TS-Align: A Teacher-Student Collaborative Framework for Scalable
Iterative Finetuning of Large Language Models | ['Chen Zhang', 'Chengguang Tang', 'Dading Chong', 'Ke Shi', 'Guohua Tang', 'Feng Jiang', 'Haizhou Li'] | ['cs.CL'] | Mainstream approaches to aligning large language models (LLMs) heavily rely
on human preference data, particularly when models require periodic updates.
The standard process for iterative alignment of LLMs involves collecting new
human feedback for each update. However, the data collection process is costly
and challen... | 2024-05-30T16:17:40Z | EMNLP-2024 Findings | null | null | TS-Align: A Teacher-Student Collaborative Framework for Scalable Iterative Finetuning of Large Language Models | ['Chen Zhang', 'Chengguang Tang', 'Dading Chong', 'Ke Shi', 'Guohua Tang', 'Feng Jiang', 'Haizhou Li'] | 2,024 | Conference on Empirical Methods in Natural Language Processing | 4 | 76 | ['Computer Science'] |
2,405.20222 | MOFA-Video: Controllable Image Animation via Generative Motion Field
Adaptions in Frozen Image-to-Video Diffusion Model | ['Muyao Niu', 'Xiaodong Cun', 'Xintao Wang', 'Yong Zhang', 'Ying Shan', 'Yinqiang Zheng'] | ['cs.CV', 'cs.AI'] | We present MOFA-Video, an advanced controllable image animation method that
generates video from the given image using various additional controllable
signals (such as human landmarks reference, manual trajectories, and another
even provided video) or their combinations. This is different from previous
methods which on... | 2024-05-30T16:22:22Z | ECCV 2024 ; Project Page: https://myniuuu.github.io/MOFA_Video/ ;
Codes: https://github.com/MyNiuuu/MOFA-Video | null | null | null | null | null | null | null | null | null |
2,405.20233 | Grokfast: Accelerated Grokking by Amplifying Slow Gradients | ['Jaerin Lee', 'Bong Gyun Kang', 'Kihoon Kim', 'Kyoung Mu Lee'] | ['cs.LG', 'cs.AI'] | One puzzling artifact in machine learning dubbed grokking is where delayed
generalization is achieved tenfolds of iterations after near perfect
overfitting to the training data. Focusing on the long delay itself on behalf
of machine learning practitioners, our goal is to accelerate generalization of
a model under grokk... | 2024-05-30T16:35:30Z | 17 pages, 13 figures. Typo fixed. Project page:
https://jaerinlee.com/research/grokfast | null | null | Grokfast: Accelerated Grokking by Amplifying Slow Gradients | ['Jaerin Lee', 'Bong Gyun Kang', 'Kihoon Kim', 'Kyoung Mu Lee'] | 2,024 | arXiv.org | 13 | 28 | ['Computer Science'] |
2,405.20315 | ANAH: Analytical Annotation of Hallucinations in Large Language Models | ['Ziwei Ji', 'Yuzhe Gu', 'Wenwei Zhang', 'Chengqi Lyu', 'Dahua Lin', 'Kai Chen'] | ['cs.CL', 'cs.AI'] | Reducing the `$\textit{hallucination}$' problem of Large Language Models
(LLMs) is crucial for their wide applications. A comprehensive and fine-grained
measurement of the hallucination is the first key step for the governance of
this issue but is under-explored in the community. Thus, we present
$\textbf{ANAH}$, a bil... | 2024-05-30T17:54:40Z | Accepted by ACL 2024 | null | null | ANAH: Analytical Annotation of Hallucinations in Large Language Models | ['Ziwei Ji', 'Yuzhe Gu', 'Wenwei Zhang', 'Chengqi Lyu', 'Dahua Lin', 'Kai Chen'] | 2,024 | Annual Meeting of the Association for Computational Linguistics | 3 | 61 | ['Computer Science'] |
2,405.20324 | Don't drop your samples! Coherence-aware training benefits Conditional
diffusion | ['Nicolas Dufour', 'Victor Besnier', 'Vicky Kalogeiton', 'David Picard'] | ['cs.CV', 'cs.LG'] | Conditional diffusion models are powerful generative models that can leverage
various types of conditional information, such as class labels, segmentation
masks, or text captions. However, in many real-world scenarios, conditional
information may be noisy or unreliable due to human annotation errors or weak
alignment. ... | 2024-05-30T17:57:26Z | Accepted at CVPR 2024 as a Highlight. Project page:
https://nicolas-dufour.github.io/cad.html | null | null | null | null | null | null | null | null | null |
2,405.20335 | Xwin-LM: Strong and Scalable Alignment Practice for LLMs | ['Bolin Ni', 'JingCheng Hu', 'Yixuan Wei', 'Houwen Peng', 'Zheng Zhang', 'Gaofeng Meng', 'Han Hu'] | ['cs.CL'] | In this work, we present Xwin-LM, a comprehensive suite of alignment
methodologies for large language models (LLMs). This suite encompasses several
key techniques, including supervised finetuning (SFT), reward modeling (RM),
rejection sampling finetuning (RS), and direct preference optimization (DPO).
The key component... | 2024-05-30T17:59:31Z | null | null | null | null | null | null | null | null | null | null |
2,405.2034 | MotionLLM: Understanding Human Behaviors from Human Motions and Videos | ['Ling-Hao Chen', 'Shunlin Lu', 'Ailing Zeng', 'Hao Zhang', 'Benyou Wang', 'Ruimao Zhang', 'Lei Zhang'] | ['cs.CV'] | This study delves into the realm of multi-modality (i.e., video and motion
modalities) human behavior understanding by leveraging the powerful
capabilities of Large Language Models (LLMs). Diverging from recent LLMs
designed for video-only or motion-only understanding, we argue that
understanding human behavior necessi... | 2024-05-30T17:59:50Z | MotionLLM version 1.0, project page see https://lhchen.top/MotionLLM | null | null | MotionLLM: Understanding Human Behaviors from Human Motions and Videos | ['Ling-Hao Chen', 'Shunlin Lu', 'Ailing Zeng', 'Hao Zhang', 'Benyou Wang', 'Ruimao Zhang', 'Lei Zhang'] | 2,024 | arXiv.org | 38 | 91 | ['Computer Science'] |
2,405.20343 | Unique3D: High-Quality and Efficient 3D Mesh Generation from a Single
Image | ['Kailu Wu', 'Fangfu Liu', 'Zhihan Cai', 'Runjie Yan', 'Hanyang Wang', 'Yating Hu', 'Yueqi Duan', 'Kaisheng Ma'] | ['cs.CV', 'cs.GR', 'cs.LG', 'I.2.10'] | In this work, we introduce Unique3D, a novel image-to-3D framework for
efficiently generating high-quality 3D meshes from single-view images,
featuring state-of-the-art generation fidelity and strong generalizability.
Previous methods based on Score Distillation Sampling (SDS) can produce
diversified 3D results by dist... | 2024-05-30T17:59:54Z | Project page: https://wukailu.github.io/Unique3D | null | null | null | null | null | null | null | null | null |
2,405.20462 | Multi-Label Guided Soft Contrastive Learning for Efficient Earth
Observation Pretraining | ['Yi Wang', 'Conrad M Albrecht', 'Xiao Xiang Zhu'] | ['cs.CV'] | Self-supervised pretraining on large-scale satellite data has raised great
interest in building Earth observation (EO) foundation models. However, many
important resources beyond pure satellite imagery, such as land-cover-land-use
products that provide free global semantic information, as well as vision
foundation mode... | 2024-05-30T20:19:42Z | Accepted by IEEE Transactions on Geoscience and Remote Sensing. 16
pages, 10 figures | null | null | null | null | null | null | null | null | null |
2,405.20494 | Slight Corruption in Pre-training Data Makes Better Diffusion Models | ['Hao Chen', 'Yujin Han', 'Diganta Misra', 'Xiang Li', 'Kai Hu', 'Difan Zou', 'Masashi Sugiyama', 'Jindong Wang', 'Bhiksha Raj'] | ['cs.CV', 'cs.AI', 'cs.LG'] | Diffusion models (DMs) have shown remarkable capabilities in generating
realistic high-quality images, audios, and videos. They benefit significantly
from extensive pre-training on large-scale datasets, including web-crawled data
with paired data and conditions, such as image-text and image-class pairs.
Despite rigorou... | 2024-05-30T21:35:48Z | NeurIPS 2024 Spotlight | null | null | null | null | null | null | null | null | null |
2,405.20541 | Perplexed by Perplexity: Perplexity-Based Data Pruning With Small
Reference Models | ['Zachary Ankner', 'Cody Blakeney', 'Kartik Sreenivasan', 'Max Marion', 'Matthew L. Leavitt', 'Mansheej Paul'] | ['cs.LG', 'cs.CL'] | In this work, we investigate whether small language models can determine
high-quality subsets of large-scale text datasets that improve the performance
of larger language models. While existing work has shown that pruning based on
the perplexity of a larger model can yield high-quality data, we investigate
whether smal... | 2024-05-30T23:50:20Z | null | null | null | Perplexed by Perplexity: Perplexity-Based Data Pruning With Small Reference Models | ['Zachary Ankner', 'Cody Blakeney', 'Kartik K. Sreenivasan', 'Max Marion', 'Matthew L. Leavitt', 'Mansheej Paul'] | 2,024 | International Conference on Learning Representations | 34 | 60 | ['Computer Science'] |
2,405.20768 | Expanded Gating Ranges Improve Activation Functions | ['Allen Hao Huang'] | ['cs.NE', 'cs.LG'] | Activation functions are core components of all deep learning architectures.
Currently, the most popular activation functions are smooth ReLU variants like
GELU and SiLU. These are self-gated activation functions where the range of the
gating function is between zero and one. In this paper, we explore the
viability of ... | 2024-05-25T09:12:17Z | null | null | null | null | null | null | null | null | null | null |
2,405.20797 | Ovis: Structural Embedding Alignment for Multimodal Large Language Model | ['Shiyin Lu', 'Yang Li', 'Qing-Guo Chen', 'Zhao Xu', 'Weihua Luo', 'Kaifu Zhang', 'Han-Jia Ye'] | ['cs.CV', 'cs.AI', 'cs.CL', 'cs.LG'] | Current Multimodal Large Language Models (MLLMs) typically integrate a
pre-trained LLM with another pre-trained vision transformer through a
connector, such as an MLP, endowing the LLM with visual capabilities. However,
the misalignment between two embedding strategies in MLLMs -- the structural
textual embeddings base... | 2024-05-31T13:59:18Z | null | null | null | null | null | null | null | null | null | null |
2,405.21028 | LACIE: Listener-Aware Finetuning for Confidence Calibration in Large
Language Models | ['Elias Stengel-Eskin', 'Peter Hase', 'Mohit Bansal'] | ['cs.CL', 'cs.AI'] | When answering questions, LLMs can convey not only an answer, but a level of
confidence about the answer being correct. This includes explicit confidence
markers (e.g. giving a numeric score) as well as implicit markers, like an
authoritative tone or elaborating with additional knowledge. For LLMs to be
trustworthy kno... | 2024-05-31T17:16:38Z | 18 pages. Code: https://github.com/esteng/pragmatic_calibration | null | null | null | null | null | null | null | null | null |
2,405.21046 | Exploratory Preference Optimization: Harnessing Implicit
Q*-Approximation for Sample-Efficient RLHF | ['Tengyang Xie', 'Dylan J. Foster', 'Akshay Krishnamurthy', 'Corby Rosset', 'Ahmed Awadallah', 'Alexander Rakhlin'] | ['cs.LG', 'cs.AI', 'cs.CL', 'stat.ML'] | Reinforcement learning from human feedback (RLHF) has emerged as a central
tool for language model alignment. We consider online exploration in RLHF,
which exploits interactive access to human or AI feedback by deliberately
encouraging the model to produce diverse, maximally informative responses. By
allowing RLHF to c... | 2024-05-31T17:39:06Z | null | null | null | Exploratory Preference Optimization: Harnessing Implicit Q*-Approximation for Sample-Efficient RLHF | ['Tengyang Xie', 'Dylan J. Foster', 'Akshay Krishnamurthy', 'Corby Rosset', 'Ahmed Awadallah', 'A. Rakhlin'] | 2,024 | arXiv.org | 45 | 73 | ['Computer Science', 'Mathematics'] |
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