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2,407.12679 | Goldfish: Vision-Language Understanding of Arbitrarily Long Videos | ['Kirolos Ataallah', 'Xiaoqian Shen', 'Eslam Abdelrahman', 'Essam Sleiman', 'Mingchen Zhuge', 'Jian Ding', 'Deyao Zhu', 'Jürgen Schmidhuber', 'Mohamed Elhoseiny'] | ['cs.CV'] | Most current LLM-based models for video understanding can process videos
within minutes. However, they struggle with lengthy videos due to challenges
such as "noise and redundancy", as well as "memory and computation"
constraints. In this paper, we present Goldfish, a methodology tailored for
comprehending videos of ar... | 2024-07-17T15:59:32Z | 25 pages, 11 figures, accepted by ECCV 2024 | null | null | Goldfish: Vision-Language Understanding of Arbitrarily Long Videos | ['Kirolos Ataallah', 'Xiaoqian Shen', 'Eslam Abdelrahman', 'Essam Sleiman', 'Mingchen Zhuge', 'Jian Ding', 'Deyao Zhu', 'Jürgen Schmidhuber', 'Mohamed Elhoseiny'] | 2,024 | European Conference on Computer Vision | 20 | 50 | ['Computer Science'] |
2,407.12705 | IMAGDressing-v1: Customizable Virtual Dressing | ['Fei Shen', 'Xin Jiang', 'Xin He', 'Hu Ye', 'Cong Wang', 'Xiaoyu Du', 'Zechao Li', 'Jinhui Tang'] | ['cs.CV'] | Latest advances have achieved realistic virtual try-on (VTON) through
localized garment inpainting using latent diffusion models, significantly
enhancing consumers' online shopping experience. However, existing VTON
technologies neglect the need for merchants to showcase garments
comprehensively, including flexible con... | 2024-07-17T16:26:30Z | null | null | null | IMAGDressing-v1: Customizable Virtual Dressing | ['Fei Shen', 'Xin Jiang', 'Xin He', 'Hu Ye', 'Cong Wang', 'Xiaoyu Du', 'Zechao Li', 'Jinghui Tang'] | 2,024 | AAAI Conference on Artificial Intelligence | 46 | 44 | ['Computer Science'] |
2,407.12784 | AgentPoison: Red-teaming LLM Agents via Poisoning Memory or Knowledge
Bases | ['Zhaorun Chen', 'Zhen Xiang', 'Chaowei Xiao', 'Dawn Song', 'Bo Li'] | ['cs.LG', 'cs.CR', 'cs.IR'] | LLM agents have demonstrated remarkable performance across various
applications, primarily due to their advanced capabilities in reasoning,
utilizing external knowledge and tools, calling APIs, and executing actions to
interact with environments. Current agents typically utilize a memory module or
a retrieval-augmented... | 2024-07-17T17:59:47Z | 22 pages, 13 figures, 7 tables | null | null | AgentPoison: Red-teaming LLM Agents via Poisoning Memory or Knowledge Bases | ['Zhaorun Chen', 'Zhen Xiang', 'Chaowei Xiao', 'D. Song', 'Bo Li'] | 2,024 | Neural Information Processing Systems | 79 | 42 | ['Computer Science'] |
2,407.1279 | GPT Czech Poet: Generation of Czech Poetic Strophes with Language Models | ['Michal Chudoba', 'Rudolf Rosa'] | ['cs.CL'] | High-quality automated poetry generation systems are currently only available
for a small subset of languages. We introduce a new model for generating poetry
in Czech language, based on fine-tuning a pre-trained Large Language Model. We
demonstrate that guiding the generation process by explicitly specifying
strophe pa... | 2024-06-18T06:19:45Z | null | null | null | null | null | null | null | null | null | null |
2,407.12818 | "I understand why I got this grade": Automatic Short Answer Grading with
Feedback | ['Dishank Aggarwal', 'Pritam Sil', 'Bhaskaran Raman', 'Pushpak Bhattacharyya'] | ['cs.CL', 'cs.AI', 'cs.CY'] | In recent years, there has been a growing interest in using Artificial
Intelligence (AI) to automate student assessment in education. Among different
types of assessments, summative assessments play a crucial role in evaluating a
student's understanding level of a course. Such examinations often involve
short-answer qu... | 2024-06-30T15:42:18Z | null | null | null | null | null | null | null | null | null | null |
2,407.12857 | Automated Peer Reviewing in Paper SEA: Standardization, Evaluation, and
Analysis | ['Jianxiang Yu', 'Zichen Ding', 'Jiaqi Tan', 'Kangyang Luo', 'Zhenmin Weng', 'Chenghua Gong', 'Long Zeng', 'Renjing Cui', 'Chengcheng Han', 'Qiushi Sun', 'Zhiyong Wu', 'Yunshi Lan', 'Xiang Li'] | ['cs.CL', 'cs.DL', 'cs.IR'] | In recent years, the rapid increase in scientific papers has overwhelmed
traditional review mechanisms, resulting in varying quality of publications.
Although existing methods have explored the capabilities of Large Language
Models (LLMs) for automated scientific reviewing, their generated contents are
often generic or... | 2024-07-09T15:06:14Z | Accepted by EMNLP 2024 | null | null | Automated Peer Reviewing in Paper SEA: Standardization, Evaluation, and Analysis | ['Jianxiang Yu', 'Zichen Ding', 'Jiaqi Tan', 'Kangyang Luo', 'Zhenmin Weng', 'Chenghua Gong', 'Long Zeng', 'Renjing Cui', 'Chengcheng Han', 'Qiushi Sun', 'Zhiyong Wu', 'Yunshi Lan', 'Xiang Li'] | 2,024 | Conference on Empirical Methods in Natural Language Processing | 6 | 109 | ['Computer Science'] |
2,407.12869 | Bilingual Adaptation of Monolingual Foundation Models | ['Gurpreet Gosal', 'Yishi Xu', 'Gokul Ramakrishnan', 'Rituraj Joshi', 'Avraham Sheinin', 'Zhiming', 'Chen', 'Biswajit Mishra', 'Natalia Vassilieva', 'Joel Hestness', 'Neha Sengupta', 'Sunil Kumar Sahu', 'Bokang Jia', 'Onkar Pandit', 'Satheesh Katipomu', 'Samta Kamboj', 'Samujjwal Ghosh', 'Rahul Pal', 'Parvez Mullah', '... | ['cs.CL', 'cs.AI'] | We present an efficient method for adapting a monolingual Large Language
Model (LLM) to another language, addressing challenges of catastrophic
forgetting and tokenizer limitations. We focus this study on adapting Llama 2
to Arabic. Our two-stage approach begins with expanding the vocabulary and
training only the embed... | 2024-07-13T21:09:38Z | null | null | null | null | null | null | null | null | null | null |
2,407.12891 | Global-Local Similarity for Efficient Fine-Grained Image Recognition
with Vision Transformers | ['Edwin Arkel Rios', 'Min-Chun Hu', 'Bo-Cheng Lai'] | ['cs.CV', 'I.2; I.4'] | Fine-grained recognition involves the classification of images from
subordinate macro-categories, and it is challenging due to small inter-class
differences. To overcome this, most methods perform discriminative feature
selection enabled by a feature extraction backbone followed by a high-level
feature refinement step.... | 2024-07-17T10:04:54Z | Main: 12 pages, 5 figures, 5 tables. Appendix: 9 pages, 9 figures, 10
tables. Total: 21 pages, 14 figures, 15 tables | null | null | Global-Local Similarity for Efficient Fine-Grained Image Recognition with Vision Transformers | ['Edwin Arkel Rios', 'Min-Chun Hu', 'Bo-Cheng Lai'] | 2,024 | International Symposium on Circuits and Systems | 2 | 75 | ['Computer Science'] |
2,407.13097 | AlcLaM: Arabic Dialectal Language Model | ['Murtadha Ahmed', 'Saghir Alfasly', 'Bo Wen', 'Jamaal Qasem', 'Mohammed Ahmed', 'Yunfeng Liu'] | ['cs.CL'] | Pre-trained Language Models (PLMs) are integral to many modern natural
language processing (NLP) systems. Although multilingual models cover a wide
range of languages, they often grapple with challenges like high inference
costs and a lack of diverse non-English training data. Arabic-specific PLMs are
trained predomina... | 2024-07-18T02:13:50Z | Accepted by ArabicNLP 2024, presented in ACL 2024 | null | null | null | null | null | null | null | null | null |
2,407.13301 | CoD, Towards an Interpretable Medical Agent using Chain of Diagnosis | ['Junying Chen', 'Chi Gui', 'Anningzhe Gao', 'Ke Ji', 'Xidong Wang', 'Xiang Wan', 'Benyou Wang'] | ['cs.CL', 'cs.AI', 'cs.LG'] | The field of medical diagnosis has undergone a significant transformation
with the advent of large language models (LLMs), yet the challenges of
interpretability within these models remain largely unaddressed. This study
introduces Chain-of-Diagnosis (CoD) to enhance the interpretability of
LLM-based medical diagnostic... | 2024-07-18T09:06:27Z | null | null | null | null | null | null | null | null | null | null |
2,407.13555 | PetFace: A Large-Scale Dataset and Benchmark for Animal Identification | ['Risa Shinoda', 'Kaede Shiohara'] | ['cs.CV'] | Automated animal face identification plays a crucial role in the monitoring
of behaviors, conducting of surveys, and finding of lost animals. Despite the
advancements in human face identification, the lack of datasets and benchmarks
in the animal domain has impeded progress. In this paper, we introduce the
PetFace data... | 2024-07-18T14:28:31Z | ECCV 2024. Dataset and code: https://dahlian00.github.io/PetFacePage/ | null | null | null | null | null | null | null | null | null |
2,407.13561 | Research on Tibetan Tourism Viewpoints information generation system
based on LLM | ['Jinhu Qi', 'Shuai Yan', 'Wentao Zhang', 'Yibo Zhang', 'Zirui Liu', 'Ke Wang'] | ['cs.CL'] | Tibet, ensconced within China's territorial expanse, is distinguished by its
labyrinthine and heterogeneous topography, a testament to its profound
historical heritage, and the cradle of a unique religious ethos. The very
essence of these attributes, however, has impeded the advancement of Tibet's
tourism service infra... | 2024-07-18T14:31:53Z | null | ICWOC 2024 | 10.1109/ICWOC62055.2024.10684948 | null | null | null | null | null | null | null |
2,407.13579 | Towards Zero-Shot Multimodal Machine Translation | ['Matthieu Futeral', 'Cordelia Schmid', 'Benoît Sagot', 'Rachel Bawden'] | ['cs.CL'] | Current multimodal machine translation (MMT) systems rely on fully supervised
data (i.e models are trained on sentences with their translations and
accompanying images). However, this type of data is costly to collect, limiting
the extension of MMT to other language pairs for which such data does not
exist. In this wor... | 2024-07-18T15:20:31Z | NAACL 2025 (Findings) | null | null | Towards Zero-Shot Multimodal Machine Translation | ['Matthieu Futeral', 'Cordelia Schmid', 'Benoît Sagot', 'Rachel Bawden'] | 2,024 | North American Chapter of the Association for Computational Linguistics | 4 | 61 | ['Computer Science'] |
2,407.13623 | Scaling Laws with Vocabulary: Larger Models Deserve Larger Vocabularies | ['Chaofan Tao', 'Qian Liu', 'Longxu Dou', 'Niklas Muennighoff', 'Zhongwei Wan', 'Ping Luo', 'Min Lin', 'Ngai Wong'] | ['cs.CL', 'cs.AI'] | Research on scaling large language models (LLMs) has primarily focused on
model parameters and training data size, overlooking the role of vocabulary
size. We investigate how vocabulary size impacts LLM scaling laws by training
models ranging from 33M to 3B parameters on up to 500B characters with various
vocabulary co... | 2024-07-18T15:58:54Z | NeurIPS 2024 | null | null | Scaling Laws with Vocabulary: Larger Models Deserve Larger Vocabularies | ['Chaofan Tao', 'Qian Liu', 'Longxu Dou', 'Niklas Muennighoff', 'Zhongwei Wan', 'Ping Luo', 'Min Lin', 'Ngai Wong'] | 2,024 | Neural Information Processing Systems | 54 | 80 | ['Computer Science'] |
2,407.1369 | DART-Math: Difficulty-Aware Rejection Tuning for Mathematical
Problem-Solving | ['Yuxuan Tong', 'Xiwen Zhang', 'Rui Wang', 'Ruidong Wu', 'Junxian He'] | ['cs.CL', 'cs.AI'] | Solving mathematical problems requires advanced reasoning abilities and
presents notable challenges for large language models. Previous works usually
synthesize data from proprietary models to augment existing datasets, followed
by instruction tuning to achieve top-tier results. However, our analysis of
these datasets ... | 2024-06-18T07:14:02Z | NeurIPS 2024. Data and model checkpoints are available at
https://github.com/hkust-nlp/dart-math | null | null | DART-Math: Difficulty-Aware Rejection Tuning for Mathematical Problem-Solving | ['Yuxuan Tong', 'Xiwen Zhang', 'Rui Wang', 'R. Wu', 'Junxian He'] | 2,024 | Neural Information Processing Systems | 43 | 67 | ['Computer Science'] |
2,407.13739 | Scaling Granite Code Models to 128K Context | ['Matt Stallone', 'Vaibhav Saxena', 'Leonid Karlinsky', 'Bridget McGinn', 'Tim Bula', 'Mayank Mishra', 'Adriana Meza Soria', 'Gaoyuan Zhang', 'Aditya Prasad', 'Yikang Shen', 'Saptha Surendran', 'Shanmukha Guttula', 'Hima Patel', 'Parameswaran Selvam', 'Xuan-Hong Dang', 'Yan Koyfman', 'Atin Sood', 'Rogerio Feris', 'Nirm... | ['cs.AI', 'cs.CL', 'cs.SE'] | This paper introduces long-context Granite code models that support effective
context windows of up to 128K tokens. Our solution for scaling context length
of Granite 3B/8B code models from 2K/4K to 128K consists of a light-weight
continual pretraining by gradually increasing its RoPE base frequency with
repository-lev... | 2024-07-18T17:46:02Z | null | null | null | null | null | null | null | null | null | null |
2,407.13833 | Phi-3 Safety Post-Training: Aligning Language Models with a "Break-Fix"
Cycle | ['Emman Haider', 'Daniel Perez-Becker', 'Thomas Portet', 'Piyush Madan', 'Amit Garg', 'Atabak Ashfaq', 'David Majercak', 'Wen Wen', 'Dongwoo Kim', 'Ziyi Yang', 'Jianwen Zhang', 'Hiteshi Sharma', 'Blake Bullwinkel', 'Martin Pouliot', 'Amanda Minnich', 'Shiven Chawla', 'Solianna Herrera', 'Shahed Warreth', 'Maggie Engler... | ['cs.CL', 'cs.AI'] | Recent innovations in language model training have demonstrated that it is
possible to create highly performant models that are small enough to run on a
smartphone. As these models are deployed in an increasing number of domains, it
is critical to ensure that they are aligned with human preferences and safety
considera... | 2024-07-18T18:06:59Z | null | null | null | Phi-3 Safety Post-Training: Aligning Language Models with a "Break-Fix" Cycle | ['Emman Haider', 'D. Perez-Becker', 'Thomas Portet', 'Piyush Madan', 'Amit Garg', 'D. Majercak', 'Wen Wen', 'Dongwoo Kim', 'Ziyi Yang', 'Jianwen Zhang', 'Hiteshi Sharma', 'Blake Bullwinkel', 'Martin Pouliot', 'Amanda Minnich', 'Shiven Chawla', 'Solianna Herrera', 'Shahed Warreth', 'Maggie Engler', 'Gary Lopez', 'Nina C... | 2,024 | arXiv.org | 11 | 19 | ['Computer Science'] |
2,407.14078 | Stable-Hair: Real-World Hair Transfer via Diffusion Model | ['Yuxuan Zhang', 'Qing Zhang', 'Yiren Song', 'Jichao Zhang', 'Hao Tang', 'Jiaming Liu'] | ['cs.CV'] | Current hair transfer methods struggle to handle diverse and intricate
hairstyles, limiting their applicability in real-world scenarios. In this
paper, we propose a novel diffusion-based hair transfer framework, named
\textit{Stable-Hair}, which robustly transfers a wide range of real-world
hairstyles to user-provided ... | 2024-07-19T07:14:23Z | null | null | null | null | null | null | null | null | null | null |
2,407.14329 | Efficient Audio Captioning with Encoder-Level Knowledge Distillation | ['Xuenan Xu', 'Haohe Liu', 'Mengyue Wu', 'Wenwu Wang', 'Mark D. Plumbley'] | ['cs.SD', 'eess.AS'] | Significant improvement has been achieved in automated audio captioning (AAC)
with recent models. However, these models have become increasingly large as
their performance is enhanced. In this work, we propose a knowledge
distillation (KD) framework for AAC. Our analysis shows that in the
encoder-decoder based AAC mode... | 2024-07-19T14:09:50Z | Interspeech 2024 | null | null | null | null | null | null | null | null | null |
2,407.14358 | Stable Audio Open | ['Zach Evans', 'Julian D. Parker', 'CJ Carr', 'Zack Zukowski', 'Josiah Taylor', 'Jordi Pons'] | ['cs.SD', 'cs.AI', 'eess.AS'] | Open generative models are vitally important for the community, allowing for
fine-tunes and serving as baselines when presenting new models. However, most
current text-to-audio models are private and not accessible for artists and
researchers to build upon. Here we describe the architecture and training
process of a ne... | 2024-07-19T14:40:23Z | Demo: https://stability-ai.github.io/stable-audio-open-demo/ Weights:
https://huggingface.co/stabilityai/stable-audio-open-1.0 Code:
https://github.com/Stability-AI/stable-audio-tools. arXiv admin note: text
overlap with arXiv:2404.10301 | null | null | Stable Audio Open | ['Zach Evans', 'Julian Parker', 'CJ Carr', 'Zack Zukowski', 'Josiah Taylor', 'Jordi Pons'] | 2,024 | IEEE International Conference on Acoustics, Speech, and Signal Processing | 53 | 32 | ['Computer Science', 'Engineering'] |
2,407.14482 | ChatQA 2: Bridging the Gap to Proprietary LLMs in Long Context and RAG
Capabilities | ['Peng Xu', 'Wei Ping', 'Xianchao Wu', 'Chejian Xu', 'Zihan Liu', 'Mohammad Shoeybi', 'Bryan Catanzaro'] | ['cs.CL', 'cs.AI', 'cs.IR', 'cs.LG'] | In this work, we introduce ChatQA 2, an Llama 3.0-based model with a 128K
context window, designed to bridge the gap between open-source LLMs and leading
proprietary models (e.g., GPT-4-Turbo-2024-04-09) in long context understanding
and retrieval-augmented generation (RAG) capabilities. These two capabilities
are comp... | 2024-07-19T17:35:47Z | Accepted at ICLR 2025 | null | null | null | null | null | null | null | null | null |
2,407.14494 | InterpBench: Semi-Synthetic Transformers for Evaluating Mechanistic
Interpretability Techniques | ['Rohan Gupta', 'Iván Arcuschin', 'Thomas Kwa', 'Adrià Garriga-Alonso'] | ['cs.LG'] | Mechanistic interpretability methods aim to identify the algorithm a neural
network implements, but it is difficult to validate such methods when the true
algorithm is unknown. This work presents InterpBench, a collection of
semi-synthetic yet realistic transformers with known circuits for evaluating
these techniques. ... | 2024-07-19T17:46:51Z | null | null | null | null | null | null | null | null | null | null |
2,407.14505 | T2V-CompBench: A Comprehensive Benchmark for Compositional Text-to-video
Generation | ['Kaiyue Sun', 'Kaiyi Huang', 'Xian Liu', 'Yue Wu', 'Zihan Xu', 'Zhenguo Li', 'Xihui Liu'] | ['cs.CV'] | Text-to-video (T2V) generative models have advanced significantly, yet their
ability to compose different objects, attributes, actions, and motions into a
video remains unexplored. Previous text-to-video benchmarks also neglect this
important ability for evaluation. In this work, we conduct the first systematic
study o... | 2024-07-19T17:58:36Z | Project page: https://t2v-compbench-2025.github.io/ Code:
https://github.com/KaiyueSun98/T2V-CompBench/tree/V2 | null | null | null | null | null | null | null | null | null |
2,407.14679 | Compact Language Models via Pruning and Knowledge Distillation | ['Saurav Muralidharan', 'Sharath Turuvekere Sreenivas', 'Raviraj Joshi', 'Marcin Chochowski', 'Mostofa Patwary', 'Mohammad Shoeybi', 'Bryan Catanzaro', 'Jan Kautz', 'Pavlo Molchanov'] | ['cs.CL', 'cs.AI', 'cs.LG'] | Large language models (LLMs) targeting different deployment scales and sizes
are currently produced by training each variant from scratch; this is extremely
compute-intensive. In this paper, we investigate if pruning an existing LLM and
then re-training it with a fraction (<3%) of the original training data can be
a su... | 2024-07-19T21:47:57Z | null | null | null | null | null | null | null | null | null | null |
2,407.14757 | Enhancing Skin Disease Classification Leveraging Transformer-based Deep
Learning Architectures and Explainable AI | ['Jayanth Mohan', 'Arrun Sivasubramanian', 'V Sowmya', 'Ravi Vinayakumar'] | ['cs.CV'] | Skin diseases affect over a third of the global population, yet their impact
is often underestimated. Automating skin disease classification to assist
doctors with their prognosis might be difficult. Nevertheless, due to efficient
feature extraction pipelines, deep learning techniques have shown much promise
for variou... | 2024-07-20T05:38:00Z | Submitted to Computers in Biology and Medicine | null | 10.1016/j.compbiomed.2025.110007 | null | null | null | null | null | null | null |
2,407.14885 | Falcon2-11B Technical Report | ['Quentin Malartic', 'Nilabhra Roy Chowdhury', 'Ruxandra Cojocaru', 'Mugariya Farooq', 'Giulia Campesan', 'Yasser Abdelaziz Dahou Djilali', 'Sanath Narayan', 'Ankit Singh', 'Maksim Velikanov', 'Basma El Amel Boussaha', 'Mohammed Al-Yafeai', 'Hamza Alobeidli', 'Leen Al Qadi', 'Mohamed El Amine Seddik', 'Kirill Fedyanin'... | ['cs.CL', 'cs.CV'] | We introduce Falcon2-11B, a foundation model trained on over five trillion
tokens, and its multimodal counterpart, Falcon2-11B-vlm, which is a
vision-to-text model. We report our findings during the training of the
Falcon2-11B which follows a multi-stage approach where the early stages are
distinguished by their contex... | 2024-07-20T14:23:15Z | null | null | null | null | null | null | null | null | null | null |
2,407.14904 | Large-vocabulary forensic pathological analyses via prototypical
cross-modal contrastive learning | ['Chen Shen', 'Chunfeng Lian', 'Wanqing Zhang', 'Fan Wang', 'Jianhua Zhang', 'Shuanliang Fan', 'Xin Wei', 'Gongji Wang', 'Kehan Li', 'Hongshu Mu', 'Hao Wu', 'Xinggong Liang', 'Jianhua Ma', 'Zhenyuan Wang'] | ['eess.IV', 'cs.AI', 'cs.CL', 'cs.CV'] | Forensic pathology is critical in determining the cause and manner of death
through post-mortem examinations, both macroscopic and microscopic. The field,
however, grapples with issues such as outcome variability, laborious processes,
and a scarcity of trained professionals. This paper presents SongCi, an
innovative vi... | 2024-07-20T15:34:52Z | 28 pages, 6 figures, under review | null | null | null | null | null | null | null | null | null |
2,407.15317 | Open-CD: A Comprehensive Toolbox for Change Detection | ['Kaiyu Li', 'Jiawei Jiang', 'Andrea Codegoni', 'Chengxi Han', 'Yupeng Deng', 'Keyan Chen', 'Zhuo Zheng', 'Hao Chen', 'Ziyuan Liu', 'Yuantao Gu', 'Zhengxia Zou', 'Zhenwei Shi', 'Sheng Fang', 'Deyu Meng', 'Zhi Wang', 'Xiangyong Cao'] | ['cs.CV'] | We present Open-CD, a change detection toolbox that contains a rich set of
change detection methods as well as related components and modules. The toolbox
started from a series of open source general vision task tools, including
OpenMMLab Toolkits, PyTorch Image Models, etc. It gradually evolves into a
unified platform... | 2024-07-22T01:04:16Z | 9 pages | null | null | Open-CD: A Comprehensive Toolbox for Change Detection | ['Kaiyu Li', 'Jiawei Jiang', 'Andrea Codegoni', 'Chengxi Han', 'Yupeng Deng', 'Keyan Chen', 'Zhuo Zheng', 'Hao Chen', 'Zhengxia Zou', 'Z. Shi', 'Sheng Fang', 'Deyu Meng', 'Zhi Wang', 'Xiangyong Cao'] | 2,024 | arXiv.org | 4 | 42 | ['Computer Science'] |
2,407.15353 | Customized Retrieval Augmented Generation and Benchmarking for EDA Tool
Documentation QA | ['Yuan Pu', 'Zhuolun He', 'Tairu Qiu', 'Haoyuan Wu', 'Bei Yu'] | ['cs.CL', 'cs.AR'] | Retrieval augmented generation (RAG) enhances the accuracy and reliability of
generative AI models by sourcing factual information from external databases,
which is extensively employed in document-grounded question-answering (QA)
tasks. Off-the-shelf RAG flows are well pretrained on general-purpose
documents, yet they... | 2024-07-22T03:44:27Z | Accepted by ICCAD 2024 | null | null | null | null | null | null | null | null | null |
2,407.15362 | A Multimodal Knowledge-enhanced Whole-slide Pathology Foundation Model | ['Yingxue Xu', 'Yihui Wang', 'Fengtao Zhou', 'Jiabo Ma', 'Cheng Jin', 'Shu Yang', 'Jinbang Li', 'Zhengyu Zhang', 'Chenglong Zhao', 'Huajun Zhou', 'Zhenhui Li', 'Huangjing Lin', 'Xin Wang', 'Jiguang Wang', 'Anjia Han', 'Ronald Cheong Kin Chan', 'Li Liang', 'Xiuming Zhang', 'Hao Chen'] | ['cs.CV', 'cs.AI'] | Remarkable strides in computational pathology have been made in the
task-agnostic foundation model that advances the performance of a wide array of
downstream clinical tasks. Despite the promising performance, there are still
several challenges. First, prior works have resorted to either vision-only or
image-caption da... | 2024-07-22T04:09:27Z | 62 pages | null | null | A Multimodal Knowledge-enhanced Whole-slide Pathology Foundation Model | ['Yingxue Xu', 'Yihui Wang', 'Fengtao Zhou', 'Jiabo Ma', 'Shu Yang', 'Huangjing Lin', 'Xin Wang', 'Jiguang Wang', 'Li Liang', 'Anjia Han', 'R. Chan', 'Hao Chen'] | 2,024 | arXiv.org | 22 | 60 | ['Computer Science'] |
2,407.15408 | Chronologically Accurate Retrieval for Temporal Grounding of
Motion-Language Models | ['Kent Fujiwara', 'Mikihiro Tanaka', 'Qing Yu'] | ['cs.CV'] | With the release of large-scale motion datasets with textual annotations, the
task of establishing a robust latent space for language and 3D human motion has
recently witnessed a surge of interest. Methods have been proposed to convert
human motion and texts into features to achieve accurate correspondence between
them... | 2024-07-22T06:25:21Z | To appear at ECCV 2024. Project page: https://kfworks.com/CAR-WP/ | null | null | Chronologically Accurate Retrieval for Temporal Grounding of Motion-Language Models | ['Kent Fujiwara', 'Mikihiro Tanaka', 'Qing Yu'] | 2,024 | European Conference on Computer Vision | 2 | 54 | ['Computer Science'] |
2,407.15447 | SIGMA: Sinkhorn-Guided Masked Video Modeling | ['Mohammadreza Salehi', 'Michael Dorkenwald', 'Fida Mohammad Thoker', 'Efstratios Gavves', 'Cees G. M. Snoek', 'Yuki M. Asano'] | ['cs.CV'] | Video-based pretraining offers immense potential for learning strong visual
representations on an unprecedented scale. Recently, masked video modeling
methods have shown promising scalability, yet fall short in capturing
higher-level semantics due to reconstructing predefined low-level targets such
as pixels. To tackle... | 2024-07-22T08:04:09Z | Accepted at ECCV 24 | null | null | null | null | null | null | null | null | null |
2,407.15498 | Refining Corpora from a Model Calibration Perspective for Chinese
Spelling Correction | ['Dingyao Yu', 'Yang An', 'Wei Ye', 'Xiongfeng Xiao', 'Shaoguang Mao', 'Tao Ge', 'Shikun Zhang'] | ['cs.CL'] | Chinese Spelling Correction (CSC) commonly lacks large-scale high-quality
corpora, due to the labor-intensive labeling of spelling errors in real-life
human writing or typing scenarios. Two data augmentation methods are widely
adopted: (1) \textit{Random Replacement} with the guidance of confusion sets
and (2) \textit{... | 2024-07-22T09:26:35Z | null | null | null | null | null | null | null | null | null | null |
2,407.15642 | Cinemo: Consistent and Controllable Image Animation with Motion
Diffusion Models | ['Xin Ma', 'Yaohui Wang', 'Gengyun Jia', 'Xinyuan Chen', 'Yuan-Fang Li', 'Cunjian Chen', 'Yu Qiao'] | ['cs.CV'] | Diffusion models have achieved great progress in image animation due to
powerful generative capabilities. However, maintaining spatio-temporal
consistency with detailed information from the input static image over time
(e.g., style, background, and object of the input static image) and ensuring
smoothness in animated v... | 2024-07-22T14:00:03Z | Project webpage: https://maxin-cn.github.io/cinemo_project/ | null | null | Cinemo: Consistent and Controllable Image Animation with Motion Diffusion Models | ['Xin Ma', 'Yaohui Wang', 'Gengyun Jia', 'Xinyuan Chen', 'Yuan-Fang Li', 'Cunjian Chen', 'Yu Qiao'] | 2,024 | arXiv.org | 7 | 77 | ['Computer Science'] |
2,407.15754 | LongVideoBench: A Benchmark for Long-context Interleaved Video-Language
Understanding | ['Haoning Wu', 'Dongxu Li', 'Bei Chen', 'Junnan Li'] | ['cs.CV', 'cs.CL', 'cs.LG'] | Large multimodal models (LMMs) are processing increasingly longer and richer
inputs. Albeit the progress, few public benchmark is available to measure such
development. To mitigate this gap, we introduce LongVideoBench, a
question-answering benchmark that features video-language interleaved inputs up
to an hour long. O... | 2024-07-22T16:00:55Z | 29 pages | null | null | null | null | null | null | null | null | null |
2,407.15795 | AdaCLIP: Adapting CLIP with Hybrid Learnable Prompts for Zero-Shot
Anomaly Detection | ['Yunkang Cao', 'Jiangning Zhang', 'Luca Frittoli', 'Yuqi Cheng', 'Weiming Shen', 'Giacomo Boracchi'] | ['cs.CV'] | Zero-shot anomaly detection (ZSAD) targets the identification of anomalies
within images from arbitrary novel categories. This study introduces AdaCLIP
for the ZSAD task, leveraging a pre-trained vision-language model (VLM), CLIP.
AdaCLIP incorporates learnable prompts into CLIP and optimizes them through
training on a... | 2024-07-22T16:52:37Z | Accepted by ECCV 2024 | European Conference on Computer Vision, 2024 | 10.1007/978-3-031-72761-0_4 | null | null | null | null | null | null | null |
2,407.15811 | Stretching Each Dollar: Diffusion Training from Scratch on a
Micro-Budget | ['Vikash Sehwag', 'Xianghao Kong', 'Jingtao Li', 'Michael Spranger', 'Lingjuan Lyu'] | ['cs.CV', 'cs.AI', 'cs.LG'] | As scaling laws in generative AI push performance, they also simultaneously
concentrate the development of these models among actors with large
computational resources. With a focus on text-to-image (T2I) generative models,
we aim to address this bottleneck by demonstrating very low-cost training of
large-scale T2I dif... | 2024-07-22T17:23:28Z | 41 pages, 28 figures, 5 tables | null | null | null | null | null | null | null | null | null |
2,407.15815 | Learning to Manipulate Anywhere: A Visual Generalizable Framework For
Reinforcement Learning | ['Zhecheng Yuan', 'Tianming Wei', 'Shuiqi Cheng', 'Gu Zhang', 'Yuanpei Chen', 'Huazhe Xu'] | ['cs.RO', 'cs.AI', 'cs.CV'] | Can we endow visuomotor robots with generalization capabilities to operate in
diverse open-world scenarios? In this paper, we propose \textbf{Maniwhere}, a
generalizable framework tailored for visual reinforcement learning, enabling
the trained robot policies to generalize across a combination of multiple
visual distur... | 2024-07-22T17:29:02Z | Webpage: https://gemcollector.github.io/maniwhere/ | null | null | null | null | null | null | null | null | null |
2,407.15828 | J-CHAT: Japanese Large-scale Spoken Dialogue Corpus for Spoken Dialogue
Language Modeling | ['Wataru Nakata', 'Kentaro Seki', 'Hitomi Yanaka', 'Yuki Saito', 'Shinnosuke Takamichi', 'Hiroshi Saruwatari'] | ['cs.CL', 'cs.SD', 'eess.AS'] | Spoken dialogue plays a crucial role in human-AI interactions, necessitating
dialogue-oriented spoken language models (SLMs). To develop versatile SLMs,
large-scale and diverse speech datasets are essential. Additionally, to ensure
hiqh-quality speech generation, the data must be spontaneous like in-wild data
and must ... | 2024-07-22T17:46:50Z | 8 pages, 6 figures | null | null | J-CHAT: Japanese Large-scale Spoken Dialogue Corpus for Spoken Dialogue Language Modeling | ['Wataru Nakata', 'Kentaro Seki', 'Hitomi Yanaka', 'Yuki Saito', 'Shinnosuke Takamichi', 'H. Saruwatari'] | 2,024 | arXiv.org | 2 | 25 | ['Computer Science', 'Engineering'] |
2,407.15831 | NV-Retriever: Improving text embedding models with effective
hard-negative mining | ['Gabriel de Souza P. Moreira', 'Radek Osmulski', 'Mengyao Xu', 'Ronay Ak', 'Benedikt Schifferer', 'Even Oldridge'] | ['cs.IR', 'cs.AI'] | Text embedding models have been popular for information retrieval
applications such as semantic search and Question-Answering systems based on
Retrieval-Augmented Generation (RAG). Those models are typically Transformer
models that are fine-tuned with contrastive learning objectives. One of the
challenging aspects of f... | 2024-07-22T17:50:31Z | null | null | null | NV-Retriever: Improving text embedding models with effective hard-negative mining | ['G. D. S. P. Moreira', 'Radek Osmulski', 'Mengyao Xu', 'Ronay Ak', 'Benedikt D. Schifferer', 'Even Oldridge'] | 2,024 | arXiv.org | 47 | 34 | ['Computer Science'] |
2,407.15886 | CatVTON: Concatenation Is All You Need for Virtual Try-On with Diffusion
Models | ['Zheng Chong', 'Xiao Dong', 'Haoxiang Li', 'Shiyue Zhang', 'Wenqing Zhang', 'Xujie Zhang', 'Hanqing Zhao', 'Dongmei Jiang', 'Xiaodan Liang'] | ['cs.CV', 'cs.AI', '68T42 (Primary) 168T45 (Secondary)', 'I.4.9'] | Virtual try-on methods based on diffusion models achieve realistic effects
but often require additional encoding modules, a large number of training
parameters, and complex preprocessing, which increases the burden on training
and inference. In this work, we re-evaluate the necessity of additional modules
and analyze h... | 2024-07-21T11:58:53Z | Accepted by ICLR 2025 | null | null | null | null | null | null | null | null | null |
2,407.16074 | Schrödinger Bridge for Generative Speech Enhancement | ['Ante Jukić', 'Roman Korostik', 'Jagadeesh Balam', 'Boris Ginsburg'] | ['eess.AS'] | This paper proposes a generative speech enhancement model based on
Schr\"odinger bridge (SB). The proposed model is employing a tractable SB to
formulate a data-to-data process between the clean speech distribution and the
observed noisy speech distribution. The model is trained with a data prediction
loss, aiming to r... | 2024-07-22T22:17:20Z | null | null | null | null | null | null | null | null | null | null |
2,407.16237 | OriGen:Enhancing RTL Code Generation with Code-to-Code Augmentation and
Self-Reflection | ['Fan Cui', 'Chenyang Yin', 'Kexing Zhou', 'Youwei Xiao', 'Guangyu Sun', 'Qiang Xu', 'Qipeng Guo', 'Demin Song', 'Dahua Lin', 'Xingcheng Zhang', 'Yun', 'Liang'] | ['cs.AR', 'cs.AI', 'cs.LG'] | Recent studies have demonstrated the significant potential of Large Language
Models (LLMs) in generating Register Transfer Level (RTL) code, with notable
advancements showcased by commercial models such as GPT-4 and Claude3-Opus.
However, these proprietary LLMs often raise concerns regarding privacy and
security. While... | 2024-07-23T07:22:25Z | null | null | null | null | null | null | null | null | null | null |
2,407.16354 | Strike a Balance in Continual Panoptic Segmentation | ['Jinpeng Chen', 'Runmin Cong', 'Yuxuan Luo', 'Horace Ho Shing Ip', 'Sam Kwong'] | ['cs.CV', 'cs.LG'] | This study explores the emerging area of continual panoptic segmentation,
highlighting three key balances. First, we introduce past-class backtrace
distillation to balance the stability of existing knowledge with the
adaptability to new information. This technique retraces the features
associated with past classes base... | 2024-07-23T09:58:20Z | null | null | null | null | null | null | null | null | null | null |
2,407.16382 | TookaBERT: A Step Forward for Persian NLU | ['MohammadAli SadraeiJavaheri', 'Ali Moghaddaszadeh', 'Milad Molazadeh', 'Fariba Naeiji', 'Farnaz Aghababaloo', 'Hamideh Rafiee', 'Zahra Amirmahani', 'Tohid Abedini', 'Fatemeh Zahra Sheikhi', 'Amirmohammad Salehoof'] | ['cs.CL'] | The field of natural language processing (NLP) has seen remarkable
advancements, thanks to the power of deep learning and foundation models.
Language models, and specifically BERT, have been key players in this progress.
In this study, we trained and introduced two new BERT models using Persian
data. We put our models ... | 2024-07-23T11:12:47Z | null | null | null | null | null | null | null | null | null | null |
2,407.16434 | Enhancing LLM's Cognition via Structurization | ['Kai Liu', 'Zhihang Fu', 'Chao Chen', 'Wei Zhang', 'Rongxin Jiang', 'Fan Zhou', 'Yaowu Chen', 'Yue Wu', 'Jieping Ye'] | ['cs.CL'] | When reading long-form text, human cognition is complex and structurized.
While large language models (LLMs) process input contexts through a causal and
sequential perspective, this approach can potentially limit their ability to
handle intricate and complex inputs effectively. To enhance LLM's cognition
capability, th... | 2024-07-23T12:33:58Z | This paper has been accepted by NeurIPS 2024. Code is available at
https://github.com/alibaba/struxgpt | null | null | null | null | null | null | null | null | null |
2,407.16615 | Lawma: The Power of Specialization for Legal Annotation | ['Ricardo Dominguez-Olmedo', 'Vedant Nanda', 'Rediet Abebe', 'Stefan Bechtold', 'Christoph Engel', 'Jens Frankenreiter', 'Krishna Gummadi', 'Moritz Hardt', 'Michael Livermore'] | ['cs.CL', 'cs.AI', 'cs.LG'] | Annotation and classification of legal text are central components of
empirical legal research. Traditionally, these tasks are often delegated to
trained research assistants. Motivated by the advances in language modeling,
empirical legal scholars are increasingly turning to prompting commercial
models, hoping that it ... | 2024-07-23T16:23:04Z | ICLR 2025 | null | null | Lawma: The Power of Specialization for Legal Annotation | ['Ricardo Dominguez-Olmedo', 'Vedant Nanda', 'Rediet Abebe', 'Stefan Bechtold', 'Christoph Engel', 'Jens Frankenreiter', 'Krishna P. Gummadi', 'Moritz Hardt', 'Michael A. Livermore'] | 2,024 | International Conference on Learning Representations | 3 | 59 | ['Computer Science'] |
2,407.16637 | Course-Correction: Safety Alignment Using Synthetic Preferences | ['Rongwu Xu', 'Yishuo Cai', 'Zhenhong Zhou', 'Renjie Gu', 'Haiqin Weng', 'Yan Liu', 'Tianwei Zhang', 'Wei Xu', 'Han Qiu'] | ['cs.CL', 'cs.AI', 'cs.LG'] | The risk of harmful content generated by large language models (LLMs) becomes
a critical concern. This paper presents a systematic study on assessing and
improving LLMs' capability to perform the task of \textbf{course-correction},
\ie, the model can steer away from generating harmful content autonomously. To
start wit... | 2024-07-23T16:54:28Z | Paper accepted to EMNLP 2024. Camera-ready version. We have released
our dataset and scripts at https://github.com/pillowsofwind/Course-Correction | null | null | Course-Correction: Safety Alignment Using Synthetic Preferences | ['Rongwu Xu', 'Yishuo Cai', 'Zhenhong Zhou', 'Renjie Gu', 'Haiqin Weng', 'Yan Liu', 'Tianwei Zhang', 'Wei Xu', 'Han Qiu'] | 2,024 | Conference on Empirical Methods in Natural Language Processing | 7 | 59 | ['Computer Science'] |
2,407.16674 | KAN or MLP: A Fairer Comparison | ['Runpeng Yu', 'Weihao Yu', 'Xinchao Wang'] | ['cs.LG', 'cs.AI'] | This paper does not introduce a novel method. Instead, it offers a fairer and
more comprehensive comparison of KAN and MLP models across various tasks,
including machine learning, computer vision, audio processing, natural language
processing, and symbolic formula representation. Specifically, we control the
number of ... | 2024-07-23T17:43:35Z | Technical Report | null | null | KAN or MLP: A Fairer Comparison | ['Runpeng Yu', 'Weihao Yu', 'Xinchao Wang'] | 2,024 | arXiv.org | 57 | 9 | ['Computer Science'] |
2,407.16724 | Structure-aware Domain Knowledge Injection for Large Language Models | ['Kai Liu', 'Ze Chen', 'Zhihang Fu', 'Wei Zhang', 'Rongxin Jiang', 'Fan Zhou', 'Yaowu Chen', 'Yue Wu', 'Jieping Ye'] | ['cs.CL'] | This paper introduces a pioneering methodology, termed StructTuning, to
efficiently transform foundation Large Language Models (LLMs) into domain
specialists. It significantly reduces the training corpus needs to a mere 5%
while achieving an impressive 100% of traditional knowledge injection
performance. Motivated by s... | 2024-07-23T12:38:48Z | Preprint. Code is available at https://github.com/alibaba/struxgpt | null | null | Structure-aware Domain Knowledge Injection for Large Language Models | ['Kai Liu', 'Ze Chen', 'Zhihang Fu', 'Wei Zhang', 'Rongxin Jiang', 'Fan Zhou', 'Yao-Shen Chen', 'Yue Wu', 'Jieping Ye'] | 2,024 | null | 1 | 70 | ['Computer Science'] |
2,407.16732 | PyBench: Evaluating LLM Agent on various real-world coding tasks | ['Yaolun Zhang', 'Yinxu Pan', 'Yudong Wang', 'Jie Cai'] | ['cs.SE', 'cs.AI'] | The LLM Agent, equipped with a code interpreter, is capable of automatically
solving real-world coding tasks, such as data analysis and image editing.
However, existing benchmarks primarily focus on either simplistic tasks, such
as completing a few lines of code, or on extremely complex and specific tasks
at the repo... | 2024-07-23T15:23:14Z | 16 pages | null | null | PyBench: Evaluating LLM Agent on various real-world coding tasks | ['Yaolun Zhang', 'Yinxu Pan', 'Yudong Wang', 'Jie Cai', 'Zhi Zheng', 'Guoyang Zeng', 'Zhiyuan Liu'] | 2,024 | arXiv.org | 11 | 49 | ['Computer Science'] |
2,407.16826 | SINDER: Repairing the Singular Defects of DINOv2 | ['Haoqi Wang', 'Tong Zhang', 'Mathieu Salzmann'] | ['cs.CV'] | Vision Transformer models trained on large-scale datasets, although
effective, often exhibit artifacts in the patch token they extract. While such
defects can be alleviated by re-training the entire model with additional
classification tokens, the underlying reasons for the presence of these tokens
remain unclear. In t... | 2024-07-23T20:34:23Z | ECCV 2024 | null | null | SINDER: Repairing the Singular Defects of DINOv2 | ['Haoqian Wang', 'Tong Zhang', 'Mathieu Salzmann'] | 2,024 | European Conference on Computer Vision | 4 | 29 | ['Computer Science'] |
2,407.1697 | Towards Aligning Language Models with Textual Feedback | ['Saüc Abadal Lloret', 'Shehzaad Dhuliawala', 'Keerthiram Murugesan', 'Mrinmaya Sachan'] | ['cs.CL', 'cs.AI', 'cs.LG'] | We present ALT (ALignment with Textual feedback), an approach that aligns
language models with user preferences expressed in text. We argue that text
offers greater expressiveness, enabling users to provide richer feedback than
simple comparative preferences and this richer feedback can lead to more
efficient and effec... | 2024-07-24T03:32:05Z | Accepted to EMNLP 2024 | null | null | Towards Aligning Language Models with Textual Feedback | ['Sauc Abadal Lloret', 'S. Dhuliawala', 'K. Murugesan', 'Mrinmaya Sachan'] | 2,024 | Conference on Empirical Methods in Natural Language Processing | 1 | 38 | ['Computer Science'] |
2,407.16982 | Diffree: Text-Guided Shape Free Object Inpainting with Diffusion Model | ['Lirui Zhao', 'Tianshuo Yang', 'Wenqi Shao', 'Yuxin Zhang', 'Yu Qiao', 'Ping Luo', 'Kaipeng Zhang', 'Rongrong Ji'] | ['cs.CV', 'cs.AI'] | This paper addresses an important problem of object addition for images with
only text guidance. It is challenging because the new object must be integrated
seamlessly into the image with consistent visual context, such as lighting,
texture, and spatial location. While existing text-guided image inpainting
methods can ... | 2024-07-24T03:58:58Z | null | null | null | Diffree: Text-Guided Shape Free Object Inpainting with Diffusion Model | ['Lirui Zhao', 'Tianshuo Yang', 'Wenqi Shao', 'Yuxin Zhang', 'Yu Qiao', 'Ping Luo', 'Kaipeng Zhang', 'Rongrong Ji'] | 2,024 | arXiv.org | 3 | 45 | ['Computer Science'] |
2,407.1714 | RT-DETRv2: Improved Baseline with Bag-of-Freebies for Real-Time
Detection Transformer | ['Wenyu Lv', 'Yian Zhao', 'Qinyao Chang', 'Kui Huang', 'Guanzhong Wang', 'Yi Liu'] | ['cs.CV'] | In this report, we present RT-DETRv2, an improved Real-Time DEtection
TRansformer (RT-DETR). RT-DETRv2 builds upon the previous state-of-the-art
real-time detector, RT-DETR, and opens up a set of bag-of-freebies for
flexibility and practicality, as well as optimizing the training strategy to
achieve enhanced performanc... | 2024-07-24T10:20:19Z | null | null | null | RT-DETRv2: Improved Baseline with Bag-of-Freebies for Real-Time Detection Transformer | ['Wenyu Lv', 'Yian Zhao', 'Qinyao Chang', 'Kui Huang', 'Guanzhong Wang', 'Yi Liu'] | 2,024 | arXiv.org | 50 | 0 | ['Computer Science'] |
2,407.1716 | A Comparative Analysis of Bilingual and Trilingual Wav2Vec Models for
Automatic Speech Recognition in Multilingual Oral History Archives | ['Jan Lehečka', 'Josef V. Psutka', 'Luboš Šmídl', 'Pavel Ircing', 'Josef Psutka'] | ['cs.CL', 'cs.AI'] | In this paper, we are comparing monolingual Wav2Vec 2.0 models with various
multilingual models to see whether we could improve speech recognition
performance on a unique oral history archive containing a lot of mixed-language
sentences. Our main goal is to push forward research on this unique dataset,
which is an extr... | 2024-07-24T11:03:47Z | Accepted to INTERSPEECH2024 | Proceedings of Interspeech 2024 | 10.21437/Interspeech.2024-472 | null | null | null | null | null | null | null |
2,407.17167 | Zero-Shot vs. Few-Shot Multi-Speaker TTS Using Pre-trained Czech
SpeechT5 Model | ['Jan Lehečka', 'Zdeněk Hanzlíček', 'Jindřich Matoušek', 'Daniel Tihelka'] | ['cs.SD', 'cs.CL', 'eess.AS'] | In this paper, we experimented with the SpeechT5 model pre-trained on
large-scale datasets. We pre-trained the foundation model from scratch and
fine-tuned it on a large-scale robust multi-speaker text-to-speech (TTS) task.
We tested the model capabilities in a zero- and few-shot scenario. Based on two
listening tests,... | 2024-07-24T11:14:06Z | Accepted to TSD2024 | Text, Speech, and Dialogue. TSD 2024. Lecture Notes in Computer
Science(), vol 15049 | 10.1007/978-3-031-70566-3_5 | null | null | null | null | null | null | null |
2,407.17227 | LEAN-GitHub: Compiling GitHub LEAN repositories for a versatile LEAN
prover | ['Zijian Wu', 'Jiayu Wang', 'Dahua Lin', 'Kai Chen'] | ['cs.AI', 'cs.CL'] | Recently, large language models have presented promising results in aiding
formal mathematical reasoning. However, their performance is restricted due to
the scarcity of formal theorem-proving data, which requires additional effort
to be extracted from raw formal language corpora. Meanwhile, a significant
amount of hum... | 2024-07-24T12:28:03Z | null | null | null | LEAN-GitHub: Compiling GitHub LEAN repositories for a versatile LEAN prover | ['Zijian Wu', 'Jiayu Wang', 'Dahua Lin', 'Kai Chen'] | 2,024 | arXiv.org | 15 | 29 | ['Computer Science'] |
2,407.17331 | Multi-label Cluster Discrimination for Visual Representation Learning | ['Xiang An', 'Kaicheng Yang', 'Xiangzi Dai', 'Ziyong Feng', 'Jiankang Deng'] | ['cs.CV'] | Contrastive Language Image Pre-training (CLIP) has recently demonstrated
success across various tasks due to superior feature representation empowered
by image-text contrastive learning. However, the instance discrimination method
used by CLIP can hardly encode the semantic structure of training data. To
handle this li... | 2024-07-24T14:54:16Z | Accepted by ECCV2024 | null | 10.1007/978-3-031-73383-3_25 | Multi-label Cluster Discrimination for Visual Representation Learning | ['Xiang An', 'Kaicheng Yang', 'Xiangzi Dai', 'Ziyong Feng', 'Jiankang Deng'] | 2,024 | European Conference on Computer Vision | 7 | 92 | ['Computer Science'] |
2,407.17365 | ViPer: Visual Personalization of Generative Models via Individual
Preference Learning | ['Sogand Salehi', 'Mahdi Shafiei', 'Teresa Yeo', 'Roman Bachmann', 'Amir Zamir'] | ['cs.CV'] | Different users find different images generated for the same prompt
desirable. This gives rise to personalized image generation which involves
creating images aligned with an individual's visual preference. Current
generative models are, however, unpersonalized, as they are tuned to produce
outputs that appeal to a bro... | 2024-07-24T15:42:34Z | Project page at https://viper.epfl.ch/ | null | null | ViPer: Visual Personalization of Generative Models via Individual Preference Learning | ['Sogand Salehi', 'Mahdi Shafiei', 'Teresa Yeo', 'Roman Bachmann', 'Amir Zamir'] | 2,024 | European Conference on Computer Vision | 3 | 33 | ['Computer Science'] |
2,407.17465 | u-$μ$P: The Unit-Scaled Maximal Update Parametrization | ['Charlie Blake', 'Constantin Eichenberg', 'Josef Dean', 'Lukas Balles', 'Luke Y. Prince', 'Björn Deiseroth', 'Andres Felipe Cruz-Salinas', 'Carlo Luschi', 'Samuel Weinbach', 'Douglas Orr'] | ['cs.LG'] | The Maximal Update Parametrization ($\mu$P) aims to make the optimal
hyperparameters (HPs) of a model independent of its size, allowing them to be
swept using a cheap proxy model rather than the full-size target model. We
present a new scheme, u-$\mu$P, which improves upon $\mu$P by combining it with
Unit Scaling, a me... | 2024-07-24T17:58:42Z | 55 pages | null | null | u-μP: The Unit-Scaled Maximal Update Parametrization | ['Charlie Blake', 'C. Eichenberg', 'Josef Dean', 'Lukas Balles', 'L. Y. Prince', 'Bjorn Deiseroth', 'Andres Felipe Cruz Salinas', 'Carlo Luschi', 'Samuel Weinbach', 'Douglas Orr'] | 2,024 | arXiv.org | 10 | 73 | ['Computer Science'] |
2,407.1747 | SV4D: Dynamic 3D Content Generation with Multi-Frame and Multi-View
Consistency | ['Yiming Xie', 'Chun-Han Yao', 'Vikram Voleti', 'Huaizu Jiang', 'Varun Jampani'] | ['cs.CV'] | We present Stable Video 4D (SV4D), a latent video diffusion model for
multi-frame and multi-view consistent dynamic 3D content generation. Unlike
previous methods that rely on separately trained generative models for video
generation and novel view synthesis, we design a unified diffusion model to
generate novel view v... | 2024-07-24T17:59:43Z | Project page: https://sv4d.github.io/ | null | null | null | null | null | null | null | null | null |
2,407.17535 | LAMBDA: A Large Model Based Data Agent | ['Maojun Sun', 'Ruijian Han', 'Binyan Jiang', 'Houduo Qi', 'Defeng Sun', 'Yancheng Yuan', 'Jian Huang'] | ['cs.AI', 'cs.LG', 'cs.SE', '62-04, 62-08, 68T01, 68T09'] | We introduce LArge Model Based Data Agent (LAMBDA), a novel open-source,
code-free multi-agent data analysis system that leverages the power of large
language models. LAMBDA is designed to address data analysis challenges in
data-driven applications through innovatively designed data agents using
natural language. At t... | 2024-07-24T06:26:36Z | 56 pages | null | null | LAMBDA: A Large Model Based Data Agent | ['Maojun Sun', 'Ruijian Han', 'Binyan Jiang', 'Houduo Qi', 'Defeng Sun', 'Yancheng Yuan', 'Jian Huang'] | 2,024 | Journal of the American Statistical Association | 4 | 52 | ['Computer Science'] |
2,407.17722 | Text-Driven Neural Collaborative Filtering Model for Paper Source
Tracing | ['Aobo Xu', 'Bingyu Chang', 'Qingpeng Liu', 'Ling Jian'] | ['cs.IR', 'cs.LG'] | Identifying significant references within the complex interrelations of a
citation knowledge graph is challenging, which encompasses connections through
citations, authorship, keywords, and other relational attributes. The Paper
Source Tracing (PST) task seeks to automate the identification of pivotal
references for gi... | 2024-07-25T02:48:56Z | KDD CUP 2024 OAG-Challenges, Paper Source Tracing, Technical Report
of Team AoboSama @ KDD CUP 2024. August 25--29, 2024. Barcelona, Spain | null | null | null | null | null | null | null | null | null |
2,407.17852 | Scaling A Simple Approach to Zero-Shot Speech Recognition | ['Jinming Zhao', 'Vineel Pratap', 'Michael Auli'] | ['cs.CL'] | Despite rapid progress in increasing the language coverage of automatic
speech recognition, the field is still far from covering all languages with a
known writing script. Recent work showed promising results with a zero-shot
approach requiring only a small amount of text data, however, accuracy heavily
depends on the ... | 2024-07-25T08:08:55Z | 9 pages | null | null | Scaling A Simple Approach to Zero-Shot Speech Recognition | ['Jinming Zhao', 'Vineel Pratap', 'Michael Auli'] | 2,024 | IEEE International Conference on Acoustics, Speech, and Signal Processing | 6 | 23 | ['Computer Science'] |
2,407.18054 | LKCell: Efficient Cell Nuclei Instance Segmentation with Large
Convolution Kernels | ['Ziwei Cui', 'Jingfeng Yao', 'Lunbin Zeng', 'Juan Yang', 'Wenyu Liu', 'Xinggang Wang'] | ['eess.IV', 'cs.CV'] | The segmentation of cell nuclei in tissue images stained with the blood dye
hematoxylin and eosin (H$\&$E) is essential for various clinical applications
and analyses. Due to the complex characteristics of cellular morphology, a
large receptive field is considered crucial for generating high-quality
segmentation. Howev... | 2024-07-25T14:07:49Z | null | null | null | null | null | null | null | null | null | null |
2,407.18067 | HVM-1: Large-scale video models pretrained with nearly 5000 hours of
human-like video data | ['A. Emin Orhan'] | ['cs.CV', 'cs.LG', 'cs.NE', 'q-bio.NC'] | We introduce Human-like Video Models (HVM-1), large-scale video models
pretrained with nearly 5000 hours of curated human-like video data (mostly
egocentric, temporally extended, continuous video recordings), using the
spatiotemporal masked autoencoder (ST-MAE) algorithm. We release two 633M
parameter models trained at... | 2024-07-25T14:21:50Z | 10 pages, 5 figures, 1 table; code & models available from
https://github.com/eminorhan/hvm-1 | null | null | null | null | null | null | null | null | null |
2,407.18112 | Keypoint Promptable Re-Identification | ['Vladimir Somers', 'Christophe De Vleeschouwer', 'Alexandre Alahi'] | ['cs.CV'] | Occluded Person Re-Identification (ReID) is a metric learning task that
involves matching occluded individuals based on their appearance. While many
studies have tackled occlusions caused by objects, multi-person occlusions
remain less explored. In this work, we identify and address a critical
challenge overlooked by p... | 2024-07-25T15:20:58Z | null | Proceedings of the 2024 IEEE/CVF European Conference on Computer
Vision (ECCV24) | 10.1007/978-3-031-72986-7_13 | null | null | null | null | null | null | null |
2,407.18125 | Self-supervised pre-training with diffusion model for few-shot landmark
detection in x-ray images | ['Roberto Di Via', 'Francesca Odone', 'Vito Paolo Pastore'] | ['cs.CV', 'cs.AI'] | Deep neural networks have been extensively applied in the medical domain for
various tasks, including image classification, segmentation, and landmark
detection. However, their application is often hindered by data scarcity, both
in terms of available annotations and images. This study introduces a novel
application of... | 2024-07-25T15:32:59Z | Accepted at WACV 2025 | null | null | null | null | null | null | null | null | null |
2,407.18245 | VGGHeads: 3D Multi Head Alignment with a Large-Scale Synthetic Dataset | ['Orest Kupyn', 'Eugene Khvedchenia', 'Christian Rupprecht'] | ['cs.CV', 'cs.LG'] | Human head detection, keypoint estimation, and 3D head model fitting are
essential tasks with many applications. However, traditional real-world
datasets often suffer from bias, privacy, and ethical concerns, and they have
been recorded in laboratory environments, which makes it difficult for trained
models to generali... | 2024-07-25T17:58:17Z | null | null | null | VGGHeads: 3D Multi Head Alignment with a Large-Scale Synthetic Dataset | ['Orest Kupyn', 'Eugene Khvedchenia', 'Christian Rupprecht'] | 2,024 | null | 1 | 0 | ['Computer Science'] |
2,407.18443 | HybridDepth: Robust Metric Depth Fusion by Leveraging Depth from Focus
and Single-Image Priors | ['Ashkan Ganj', 'Hang Su', 'Tian Guo'] | ['cs.CV'] | We propose HYBRIDDEPTH, a robust depth estimation pipeline that addresses key
challenges in depth estimation,including scale ambiguity, hardware
heterogeneity, and generalizability. HYBRIDDEPTH leverages focal stack, data
conveniently accessible in common mobile devices, to produce accurate metric
depth maps. By incorp... | 2024-07-26T00:51:52Z | WACV 2025 | null | null | null | null | null | null | null | null | null |
2,407.18743 | Towards Effective and Efficient Continual Pre-training of Large Language
Models | ['Jie Chen', 'Zhipeng Chen', 'Jiapeng Wang', 'Kun Zhou', 'Yutao Zhu', 'Jinhao Jiang', 'Yingqian Min', 'Wayne Xin Zhao', 'Zhicheng Dou', 'Jiaxin Mao', 'Yankai Lin', 'Ruihua Song', 'Jun Xu', 'Xu Chen', 'Rui Yan', 'Zhewei Wei', 'Di Hu', 'Wenbing Huang', 'Ji-Rong Wen'] | ['cs.CL', '68T50', 'I.2.7'] | Continual pre-training (CPT) has been an important approach for adapting
language models to specific domains or tasks. To make the CPT approach more
traceable, this paper presents a technical report for continually pre-training
Llama-3 (8B), which significantly enhances the Chinese language ability and
scientific reaso... | 2024-07-26T13:55:21Z | 16 pages, 10 figures, 16 tables | null | null | null | null | null | null | null | null | null |
2,407.18887 | Embedding And Clustering Your Data Can Improve Contrastive Pretraining | ['Luke Merrick'] | ['cs.LG', 'cs.CL'] | Recent studies of large-scale contrastive pretraining in the text embedding
domain show that using single-source minibatches, rather than mixed-source
minibatches, can substantially improve overall model accuracy. In this work, we
explore extending training data stratification beyond source granularity by
leveraging a ... | 2024-07-26T17:36:40Z | 16 pages, 3 figures, 2 tables | null | null | Embedding And Clustering Your Data Can Improve Contrastive Pretraining | ['Luke Merrick'] | 2,024 | arXiv.org | 5 | 11 | ['Computer Science'] |
2,407.18897 | Small Molecule Optimization with Large Language Models | ['Philipp Guevorguian', 'Menua Bedrosian', 'Tigran Fahradyan', 'Gayane Chilingaryan', 'Hrant Khachatrian', 'Armen Aghajanyan'] | ['cs.LG', 'cs.NE', 'q-bio.QM'] | Recent advancements in large language models have opened new possibilities
for generative molecular drug design. We present Chemlactica and Chemma, two
language models fine-tuned on a novel corpus of 110M molecules with computed
properties, totaling 40B tokens. These models demonstrate strong performance in
generating ... | 2024-07-26T17:51:33Z | null | null | null | null | null | null | null | null | null | null |
2,407.19487 | RLCoder: Reinforcement Learning for Repository-Level Code Completion | ['Yanlin Wang', 'Yanli Wang', 'Daya Guo', 'Jiachi Chen', 'Ruikai Zhang', 'Yuchi Ma', 'Zibin Zheng'] | ['cs.SE'] | Repository-level code completion aims to generate code for unfinished code
snippets within the context of a specified repository. Existing approaches
mainly rely on retrieval-augmented generation strategies due to limitations in
input sequence length. However, traditional lexical-based retrieval methods
like BM25 strug... | 2024-07-28T12:47:20Z | To appear at ICSE 2025 | 47th International Conference on Software Engineering (ICSE 2025) | null | RLCoder: Reinforcement Learning for Repository-Level Code Completion | ['Yanlin Wang', 'Yanlin Wang', 'Daya Guo', 'Jiachi Chen', 'Ruikai Zhang', 'Yuchi Ma', 'Zibin Zheng'] | 2,024 | International Conference on Software Engineering | 28 | 90 | ['Computer Science'] |
2,407.19527 | Open Sentence Embeddings for Portuguese with the Serafim PT* encoders
family | ['Luís Gomes', 'António Branco', 'João Silva', 'João Rodrigues', 'Rodrigo Santos'] | ['cs.CL'] | Sentence encoder encode the semantics of their input, enabling key downstream
applications such as classification, clustering, or retrieval. In this paper,
we present Serafim PT*, a family of open-source sentence encoders for
Portuguese with various sizes, suited to different hardware/compute budgets.
Each model exhibi... | 2024-07-28T16:34:25Z | null | null | null | null | null | null | null | null | null | null |
2,407.19544 | Deep Generative Models-Assisted Automated Labeling for Electron
Microscopy Images Segmentation | ['Wenhao Yuan', 'Bingqing Yao', 'Shengdong Tan', 'Fengqi You', 'Qian He'] | ['cond-mat.mtrl-sci', 'eess.IV'] | The rapid advancement of deep learning has facilitated the automated
processing of electron microscopy (EM) big data stacks. However, designing a
framework that eliminates manual labeling and adapts to domain gaps remains
challenging. Current research remains entangled in the dilemma of pursuing
complete automation whi... | 2024-07-28T17:35:24Z | null | null | null | null | null | null | null | null | null | null |
2,407.19584 | SaulLM-54B & SaulLM-141B: Scaling Up Domain Adaptation for the Legal
Domain | ['Pierre Colombo', 'Telmo Pires', 'Malik Boudiaf', 'Rui Melo', 'Dominic Culver', 'Sofia Morgado', 'Etienne Malaboeuf', 'Gabriel Hautreux', 'Johanne Charpentier', 'Michael Desa'] | ['cs.CL'] | In this paper, we introduce SaulLM-54B and SaulLM-141B, two large language
models (LLMs) tailored for the legal sector. These models, which feature
architectures of 54 billion and 141 billion parameters, respectively, are based
on the Mixtral architecture. The development of SaulLM-54B and SaulLM-141B is
guided by larg... | 2024-07-28T20:50:53Z | null | null | null | null | null | null | null | null | null | null |
2,407.196 | You shall know a piece by the company it keeps. Chess plays as a data
for word2vec models | ['Boris Orekhov'] | ['cs.CL', 'cs.AI'] | In this paper, I apply linguistic methods of analysis to non-linguistic data,
chess plays, metaphorically equating one with the other and seeking analogies.
Chess game notations are also a kind of text, and one can consider the records
of moves or positions of pieces as words and statements in a certain language.
In th... | 2024-07-28T22:12:36Z | 14 pages, 7 figures | null | null | You shall know a piece by the company it keeps. Chess plays as a data for word2vec models | ['Boris Orekhov'] | 2,024 | arXiv.org | 0 | 23 | ['Computer Science'] |
2,407.19669 | mGTE: Generalized Long-Context Text Representation and Reranking Models
for Multilingual Text Retrieval | ['Xin Zhang', 'Yanzhao Zhang', 'Dingkun Long', 'Wen Xie', 'Ziqi Dai', 'Jialong Tang', 'Huan Lin', 'Baosong Yang', 'Pengjun Xie', 'Fei Huang', 'Meishan Zhang', 'Wenjie Li', 'Min Zhang'] | ['cs.CL', 'cs.IR'] | We present systematic efforts in building long-context multilingual text
representation model (TRM) and reranker from scratch for text retrieval. We
first introduce a text encoder (base size) enhanced with RoPE and unpadding,
pre-trained in a native 8192-token context (longer than 512 of previous
multilingual encoders)... | 2024-07-29T03:12:28Z | Camera-ready version of EMNLP 2024: Industry Track | null | null | mGTE: Generalized Long-Context Text Representation and Reranking Models for Multilingual Text Retrieval | ['Xin Zhang', 'Yanzhao Zhang', 'Dingkun Long', 'Wen Xie', 'Ziqi Dai', 'Jialong Tang', 'Huan Lin', 'Baosong Yang', 'Pengjun Xie', 'Fei Huang', 'Meishan Zhang', 'Wenjie Li', 'Min Zhang'] | 2,024 | Conference on Empirical Methods in Natural Language Processing | 109 | 90 | ['Computer Science'] |
2,407.19672 | SeaLLMs 3: Open Foundation and Chat Multilingual Large Language Models
for Southeast Asian Languages | ['Wenxuan Zhang', 'Hou Pong Chan', 'Yiran Zhao', 'Mahani Aljunied', 'Jianyu Wang', 'Chaoqun Liu', 'Yue Deng', 'Zhiqiang Hu', 'Weiwen Xu', 'Yew Ken Chia', 'Xin Li', 'Lidong Bing'] | ['cs.CL'] | Large Language Models (LLMs) have shown remarkable abilities across various
tasks, yet their development has predominantly centered on high-resource
languages like English and Chinese, leaving low-resource languages underserved.
To address this disparity, we present SeaLLMs 3, the latest iteration of the
SeaLLMs model ... | 2024-07-29T03:26:22Z | null | null | null | null | null | null | null | null | null | null |
2,407.19705 | CollectiveSFT: Scaling Large Language Models for Chinese Medical
Benchmark with Collective Instructions in Healthcare | ['Jingwei Zhu', 'Minghuan Tan', 'Min Yang', 'Ruixue Li', 'Hamid Alinejad-Rokny'] | ['cs.CL', 'cs.AI'] | The rapid progress in Large Language Models (LLMs) has prompted the creation
of numerous benchmarks to evaluate their capabilities.This study focuses on the
Comprehensive Medical Benchmark in Chinese (CMB), showcasing how dataset
diversity and distribution in supervised fine-tuning (SFT) may enhance LLM
performance.Rem... | 2024-07-29T05:00:48Z | Technical Report | null | null | null | null | null | null | null | null | null |
2,407.20072 | Generative Diffusion Model Bootstraps Zero-shot Classification of Fetal
Ultrasound Images In Underrepresented African Populations | ['Fangyijie Wang', 'Kevin Whelan', 'Guénolé Silvestre', 'Kathleen M. Curran'] | ['eess.IV'] | Developing robust deep learning models for fetal ultrasound image analysis
requires comprehensive, high-quality datasets to effectively learn informative
data representations within the domain. However, the scarcity of labelled
ultrasound images poses substantial challenges, especially in low-resource
settings. To tack... | 2024-07-29T14:57:29Z | Accepted at MICCAI 2024 workshop PIPPI | null | null | null | null | null | null | null | null | null |
2,407.20171 | Diffusion Feedback Helps CLIP See Better | ['Wenxuan Wang', 'Quan Sun', 'Fan Zhang', 'Yepeng Tang', 'Jing Liu', 'Xinlong Wang'] | ['cs.CV'] | Contrastive Language-Image Pre-training (CLIP), which excels at abstracting
open-world representations across domains and modalities, has become a
foundation for a variety of vision and multimodal tasks. However, recent
studies reveal that CLIP has severe visual shortcomings, such as which can
hardly distinguish orient... | 2024-07-29T17:00:09Z | null | null | null | null | null | null | null | null | null | null |
2,407.20175 | Towards Localized Fine-Grained Control for Facial Expression Generation | ['Tuomas Varanka', 'Huai-Qian Khor', 'Yante Li', 'Mengting Wei', 'Hanwei Kung', 'Nicu Sebe', 'Guoying Zhao'] | ['cs.CV'] | Generative models have surged in popularity recently due to their ability to
produce high-quality images and video. However, steering these models to
produce images with specific attributes and precise control remains
challenging. Humans, particularly their faces, are central to content
generation due to their ability ... | 2024-07-25T18:29:48Z | null | null | null | null | null | null | null | null | null | null |
2,407.20179 | Theia: Distilling Diverse Vision Foundation Models for Robot Learning | ['Jinghuan Shang', 'Karl Schmeckpeper', 'Brandon B. May', 'Maria Vittoria Minniti', 'Tarik Kelestemur', 'David Watkins', 'Laura Herlant'] | ['cs.RO', 'cs.AI', 'cs.CV', 'cs.LG'] | Vision-based robot policy learning, which maps visual inputs to actions,
necessitates a holistic understanding of diverse visual tasks beyond
single-task needs like classification or segmentation. Inspired by this, we
introduce Theia, a vision foundation model for robot learning that distills
multiple off-the-shelf vis... | 2024-07-29T17:08:21Z | CoRL 2024 | null | null | Theia: Distilling Diverse Vision Foundation Models for Robot Learning | ['Jinghuan Shang', 'Karl Schmeckpeper', 'Brandon B. May', 'M. Minniti', 'Tarik Kelestemur', 'David Watkins', 'Laura Herlant'] | 2,024 | Conference on Robot Learning | 24 | 74 | ['Computer Science'] |
2,407.20229 | Improving 2D Feature Representations by 3D-Aware Fine-Tuning | ['Yuanwen Yue', 'Anurag Das', 'Francis Engelmann', 'Siyu Tang', 'Jan Eric Lenssen'] | ['cs.CV'] | Current visual foundation models are trained purely on unstructured 2D data,
limiting their understanding of 3D structure of objects and scenes. In this
work, we show that fine-tuning on 3D-aware data improves the quality of
emerging semantic features. We design a method to lift semantic 2D features
into an efficient 3... | 2024-07-29T17:59:21Z | ECCV 2024. Project page: https://ywyue.github.io/FiT3D | null | null | Improving 2D Feature Representations by 3D-Aware Fine-Tuning | ['Yuanwen Yue', 'Anurag Das', 'Francis Engelmann', 'Siyu Tang', 'J. E. Lenssen'] | 2,024 | European Conference on Computer Vision | 28 | 68 | ['Computer Science'] |
2,407.20267 | A Large Encoder-Decoder Family of Foundation Models For Chemical
Language | ['Eduardo Soares', 'Victor Shirasuna', 'Emilio Vital Brazil', 'Renato Cerqueira', 'Dmitry Zubarev', 'Kristin Schmidt'] | ['cs.LG', 'cs.AI', 'physics.chem-ph'] | Large-scale pre-training methodologies for chemical language models represent
a breakthrough in cheminformatics. These methods excel in tasks such as
property prediction and molecule generation by learning contextualized
representations of input tokens through self-supervised learning on large
unlabeled corpora. Typica... | 2024-07-24T20:30:39Z | 14 pages, 3 figures, 14 tables | null | null | null | null | null | null | null | null | null |
2,407.20294 | A Bayesian Flow Network Framework for Chemistry Tasks | ['Nianze Tao', 'Minori Abe'] | ['cs.LG', 'cs.AI', 'physics.chem-ph'] | In this work, we introduce ChemBFN, a language model that handles chemistry
tasks based on Bayesian flow networks working on discrete data. A new accuracy
schedule is proposed to improve the sampling quality by significantly reducing
the reconstruction loss. We show evidence that our method is appropriate for
generatin... | 2024-07-28T04:46:32Z | 7 figures, 12 tables, 27 pages | null | 10.1021/acs.jcim.4c01792 | null | null | null | null | null | null | null |
2,407.20311 | Physics of Language Models: Part 2.1, Grade-School Math and the Hidden
Reasoning Process | ['Tian Ye', 'Zicheng Xu', 'Yuanzhi Li', 'Zeyuan Allen-Zhu'] | ['cs.AI', 'cs.CL', 'cs.LG'] | Recent advances in language models have demonstrated their capability to
solve mathematical reasoning problems, achieving near-perfect accuracy on
grade-school level math benchmarks like GSM8K. In this paper, we formally study
how language models solve these problems. We design a series of controlled
experiments to add... | 2024-07-29T17:52:40Z | video appeared in ICML 2024 tutorial | null | null | Physics of Language Models: Part 2.1, Grade-School Math and the Hidden Reasoning Process | ['Tian Ye', 'Zicheng Xu', 'Yuanzhi Li', 'Zeyuan Allen-Zhu'] | 2,024 | International Conference on Learning Representations | 59 | 0 | ['Computer Science'] |
2,407.20445 | Futga: Towards Fine-grained Music Understanding through
Temporally-enhanced Generative Augmentation | ['Junda Wu', 'Zachary Novack', 'Amit Namburi', 'Jiaheng Dai', 'Hao-Wen Dong', 'Zhouhang Xie', 'Carol Chen', 'Julian McAuley'] | ['cs.SD', 'cs.AI', 'cs.LG', 'eess.AS'] | Existing music captioning methods are limited to generating concise global
descriptions of short music clips, which fail to capture fine-grained musical
characteristics and time-aware musical changes. To address these limitations,
we propose FUTGA, a model equipped with fined-grained music understanding
capabilities th... | 2024-07-29T22:53:32Z | 6 pages | null | null | FUTGA: Towards Fine-grained Music Understanding through Temporally-enhanced Generative Augmentation | ['Junda Wu', 'Zachary Novack', 'Amit Namburi', 'Jiaheng Dai', 'Hao-Wen Dong', 'Zhouhang Xie', 'Carol Chen', 'Julian McAuley'] | 2,024 | NLP4MUSA | 2 | 31 | ['Computer Science', 'Engineering'] |
2,407.20455 | Learning Feature-Preserving Portrait Editing from Generated Pairs | ['Bowei Chen', 'Tiancheng Zhi', 'Peihao Zhu', 'Shen Sang', 'Jing Liu', 'Linjie Luo'] | ['cs.CV'] | Portrait editing is challenging for existing techniques due to difficulties
in preserving subject features like identity. In this paper, we propose a
training-based method leveraging auto-generated paired data to learn desired
editing while ensuring the preservation of unchanged subject features.
Specifically, we desig... | 2024-07-29T23:19:42Z | null | null | null | null | null | null | null | null | null | null |
2,407.20581 | Knesset-DictaBERT: A Hebrew Language Model for Parliamentary Proceedings | ['Gili Goldin', 'Shuly Wintner'] | ['cs.CL', '68T50'] | We present Knesset-DictaBERT, a large Hebrew language model fine-tuned on the
Knesset Corpus, which comprises Israeli parliamentary proceedings. The model is
based on the DictaBERT architecture and demonstrates significant improvements
in understanding parliamentary language according to the MLM task. We provide a
deta... | 2024-07-30T06:29:01Z | 3 pages, 1 table | null | null | null | null | null | null | null | null | null |
2,407.20584 | Pruning Large Language Models with Semi-Structural Adaptive Sparse
Training | ['Weiyu Huang', 'Yuezhou Hu', 'Guohao Jian', 'Jun Zhu', 'Jianfei Chen'] | ['cs.CL', 'cs.AI'] | The remarkable success of Large Language Models (LLMs) relies heavily on
their substantial scale, which poses significant challenges during model
deployment in terms of latency and memory consumption. Recently, numerous
studies have attempted to compress LLMs using one-shot pruning methods.
However, these methods often... | 2024-07-30T06:33:44Z | Accepted at AAAI25 | null | null | null | null | null | null | null | null | null |
2,407.20729 | Adapting Safe-for-Work Classifier for Malaysian Language Text: Enhancing
Alignment in LLM-Ops Framework | ['Aisyah Razak', 'Ariff Nazhan', 'Kamarul Adha', 'Wan Adzhar Faiq Adzlan', 'Mas Aisyah Ahmad', 'Ammar Azman'] | ['cs.CL'] | As large language models (LLMs) become increasingly integrated into
operational workflows (LLM-Ops), there is a pressing need for effective
guardrails to ensure safe and aligned interactions, including the ability to
detect potentially unsafe or inappropriate content across languages. However,
existing safe-for-work cl... | 2024-07-30T10:51:51Z | null | null | null | Adapting Safe-for-Work Classifier for Malaysian Language Text: Enhancing Alignment in LLM-Ops Framework | ['Aisyah Razak', 'Ariff Nazhan', 'Kamarul Adha', 'Wan Adzhar Faiq Adzlan', 'Mas Aisyah Ahmad', 'Ammar Azman'] | 2,024 | arXiv.org | 0 | 9 | ['Computer Science'] |
2,407.20743 | Meltemi: The first open Large Language Model for Greek | ['Leon Voukoutis', 'Dimitris Roussis', 'Georgios Paraskevopoulos', 'Sokratis Sofianopoulos', 'Prokopis Prokopidis', 'Vassilis Papavasileiou', 'Athanasios Katsamanis', 'Stelios Piperidis', 'Vassilis Katsouros'] | ['cs.CL'] | We describe the development and capabilities of Meltemi 7B, the first open
Large Language Model for the Greek language. Meltemi 7B has 7 billion
parameters and is trained on a 40 billion token Greek corpus. For the
development of Meltemi 7B, we adapt Mistral, by continuous pretraining on the
Greek Corpus. Meltemi 7B co... | 2024-07-30T11:22:52Z | null | null | null | Meltemi: The first open Large Language Model for Greek | ['Leon Voukoutis', 'Dimitris Roussis', 'Georgios Paraskevopoulos', 'Sokratis Sofianopoulos', 'Prokopis Prokopidis', 'Vassilis Papavasileiou', 'Athanasios Katsamanis', 'Stelios Piperidis', 'V. Katsouros'] | 2,024 | arXiv.org | 9 | 50 | ['Computer Science'] |
2,407.2075 | JaColBERTv2.5: Optimising Multi-Vector Retrievers to Create
State-of-the-Art Japanese Retrievers with Constrained Resources | ['Benjamin Clavié'] | ['cs.IR', 'cs.AI', 'cs.CL'] | Neural Information Retrieval has advanced rapidly in high-resource languages,
but progress in lower-resource ones such as Japanese has been hindered by data
scarcity, among other challenges. Consequently, multilingual models have
dominated Japanese retrieval, despite their computational inefficiencies and
inability to ... | 2024-07-30T11:42:19Z | null | null | null | null | null | null | null | null | null | null |
2,407.21054 | Sentiment Reasoning for Healthcare | ['Khai-Nguyen Nguyen', 'Khai Le-Duc', 'Bach Phan Tat', 'Duy Le', 'Long Vo-Dang', 'Truong-Son Hy'] | ['cs.CL', 'cs.AI', 'cs.LG', 'cs.SD', 'eess.AS'] | Transparency in AI healthcare decision-making is crucial. By incorporating
rationales to explain reason for each predicted label, users could understand
Large Language Models (LLMs)'s reasoning to make better decision. In this work,
we introduce a new task - Sentiment Reasoning - for both speech and text
modalities, an... | 2024-07-24T12:07:54Z | ACL 2025 (Oral) | null | null | null | null | null | null | null | null | null |
2,407.21139 | Enhancing Semantic Similarity Understanding in Arabic NLP with Nested
Embedding Learning | ['Omer Nacar', 'Anis Koubaa'] | ['cs.CL'] | This work presents a novel framework for training Arabic nested embedding
models through Matryoshka Embedding Learning, leveraging multilingual,
Arabic-specific, and English-based models, to highlight the power of nested
embeddings models in various Arabic NLP downstream tasks. Our innovative
contribution includes the ... | 2024-07-30T19:03:03Z | null | null | null | null | null | null | null | null | null | null |
2,407.2124 | FCN4Flare: Fully Convolution Neural Networks for Flare Detection | ['Ming-Hui Jia', 'A-Li Luo', 'Bo Qiu'] | ['astro-ph.SR', 'astro-ph.EP', 'astro-ph.IM'] | Stellar flares offer invaluable insights into stellar magnetic activity and
exoplanetary environments. Automated flare detection enables exploiting vast
photometric datasets from missions like Kepler. This paper presents FCN4Flare,
a deep learning approach using fully convolutional networks (FCN) for precise
point-to-p... | 2024-07-30T23:15:47Z | 14 pages, 7 figures, accepted by MNRAS | null | null | null | null | null | null | null | null | null |
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