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2,403.14613 | DreamReward: Text-to-3D Generation with Human Preference | ['Junliang Ye', 'Fangfu Liu', 'Qixiu Li', 'Zhengyi Wang', 'Yikai Wang', 'Xinzhou Wang', 'Yueqi Duan', 'Jun Zhu'] | ['cs.CV', 'cs.CL', 'cs.LG'] | 3D content creation from text prompts has shown remarkable success recently.
However, current text-to-3D methods often generate 3D results that do not align
well with human preferences. In this paper, we present a comprehensive
framework, coined DreamReward, to learn and improve text-to-3D models from
human preference ... | 2024-03-21T17:58:04Z | Project page: https://jamesyjl.github.io/DreamReward | null | null | null | null | null | null | null | null | null |
2,403.14627 | MVSplat: Efficient 3D Gaussian Splatting from Sparse Multi-View Images | ['Yuedong Chen', 'Haofei Xu', 'Chuanxia Zheng', 'Bohan Zhuang', 'Marc Pollefeys', 'Andreas Geiger', 'Tat-Jen Cham', 'Jianfei Cai'] | ['cs.CV'] | We introduce MVSplat, an efficient model that, given sparse multi-view images
as input, predicts clean feed-forward 3D Gaussians. To accurately localize the
Gaussian centers, we build a cost volume representation via plane sweeping,
where the cross-view feature similarities stored in the cost volume can provide
valuabl... | 2024-03-21T17:59:58Z | ECCV2024, Project page: https://donydchen.github.io/mvsplat, Code:
https://github.com/donydchen/mvsplat | null | 10.1007/978-3-031-72664-4_21 | null | null | null | null | null | null | null |
2,403.14645 | Designing Multi-Step Action Models for Enterprise AI Adoption | ['Shreyash Mishra', 'Shrey Shah', 'Rex Pereira'] | ['cs.CY', 'cs.AI', '68T42', 'I.2.1; I.2.8'] | This paper introduces the Multi-Step Action Model (MSAM), a closed-source AI
model designed by Empsing to address challenges hindering AI adoption in
enterprises. Through a holistic examination, this paper explores MSAM's
foundational principles, design architecture, and future trajectory. It
evaluates MSAM's performan... | 2024-02-21T18:37:13Z | 8 pages, 5 figures | null | null | null | null | null | null | null | null | null |
2,403.14715 | Towards Understanding Why Label Smoothing Degrades Selective
Classification and How to Fix It | ['Guoxuan Xia', 'Olivier Laurent', 'Gianni Franchi', 'Christos-Savvas Bouganis'] | ['cs.LG', 'cs.AI', 'cs.CV'] | Label smoothing (LS) is a popular regularisation method for training neural
networks as it is effective in improving test accuracy and is simple to
implement. ``Hard'' one-hot labels are ``smoothed'' by uniformly distributing
probability mass to other classes, reducing overfitting. Prior work has
suggested that in some... | 2024-03-19T06:46:24Z | Published as a conference paper at ICLR 2025 | null | null | null | null | null | null | null | null | null |
2,403.14773 | StreamingT2V: Consistent, Dynamic, and Extendable Long Video Generation
from Text | ['Roberto Henschel', 'Levon Khachatryan', 'Hayk Poghosyan', 'Daniil Hayrapetyan', 'Vahram Tadevosyan', 'Zhangyang Wang', 'Shant Navasardyan', 'Humphrey Shi'] | ['cs.CV', 'cs.AI', 'cs.CL', 'cs.LG', 'cs.MM', 'eess.IV'] | Text-to-video diffusion models enable the generation of high-quality videos
that follow text instructions, making it easy to create diverse and individual
content. However, existing approaches mostly focus on high-quality short video
generation (typically 16 or 24 frames), ending up with hard-cuts when naively
extended... | 2024-03-21T18:27:29Z | https://github.com/Picsart-AI-Research/StreamingT2V | null | null | null | null | null | null | null | null | null |
2,403.14781 | Champ: Controllable and Consistent Human Image Animation with 3D
Parametric Guidance | ['Shenhao Zhu', 'Junming Leo Chen', 'Zuozhuo Dai', 'Qingkun Su', 'Yinghui Xu', 'Xun Cao', 'Yao Yao', 'Hao Zhu', 'Siyu Zhu'] | ['cs.CV'] | In this study, we introduce a methodology for human image animation by
leveraging a 3D human parametric model within a latent diffusion framework to
enhance shape alignment and motion guidance in curernt human generative
techniques. The methodology utilizes the SMPL(Skinned Multi-Person Linear)
model as the 3D human pa... | 2024-03-21T18:52:58Z | null | null | null | null | null | null | null | null | null | null |
2,403.1479 | Latent Diffusion Models for Attribute-Preserving Image Anonymization | ['Luca Piano', 'Pietro Basci', 'Fabrizio Lamberti', 'Lia Morra'] | ['cs.CV', 'cs.AI'] | Generative techniques for image anonymization have great potential to
generate datasets that protect the privacy of those depicted in the images,
while achieving high data fidelity and utility. Existing methods have focused
extensively on preserving facial attributes, but failed to embrace a more
comprehensive perspect... | 2024-03-21T19:09:21Z | null | null | null | null | null | null | null | null | null | null |
2,403.14852 | KeyPoint Relative Position Encoding for Face Recognition | ['Minchul Kim', 'Yiyang Su', 'Feng Liu', 'Anil Jain', 'Xiaoming Liu'] | ['cs.CV'] | In this paper, we address the challenge of making ViT models more robust to
unseen affine transformations. Such robustness becomes useful in various
recognition tasks such as face recognition when image alignment failures occur.
We propose a novel method called KP-RPE, which leverages key points
(e.g.~facial landmarks)... | 2024-03-21T21:56:09Z | To appear in CVPR2024 | null | null | KeyPoint Relative Position Encoding for Face Recognition | ['Minchul Kim', 'Yiyang Su', 'Feng Liu', 'Anil Jain', 'Xiaoming Liu'] | 2,024 | Computer Vision and Pattern Recognition | 10 | 91 | ['Computer Science'] |
2,403.15245 | Reasoning-Enhanced Object-Centric Learning for Videos | ['Jian Li', 'Pu Ren', 'Yang Liu', 'Hao Sun'] | ['cs.CV', 'cs.AI', 'cs.LG'] | Object-centric learning aims to break down complex visual scenes into more
manageable object representations, enhancing the understanding and reasoning
abilities of machine learning systems toward the physical world. Recently,
slot-based video models have demonstrated remarkable proficiency in segmenting
and tracking o... | 2024-03-22T14:41:55Z | null | null | null | Reasoning-Enhanced Object-Centric Learning for Videos | ['Jian Li', 'Pu Ren', 'Yang Liu', 'Hao Sun'] | 2,024 | Knowledge Discovery and Data Mining | 2 | 84 | ['Computer Science'] |
2,403.15246 | FollowIR: Evaluating and Teaching Information Retrieval Models to Follow
Instructions | ['Orion Weller', 'Benjamin Chang', 'Sean MacAvaney', 'Kyle Lo', 'Arman Cohan', 'Benjamin Van Durme', 'Dawn Lawrie', 'Luca Soldaini'] | ['cs.IR', 'cs.CL', 'cs.LG'] | Modern Language Models (LMs) are capable of following long and complex
instructions that enable a large and diverse set of user requests. While
Information Retrieval (IR) models use these LMs as the backbone of their
architectures, virtually none of them allow users to provide detailed
instructions alongside queries, t... | 2024-03-22T14:42:29Z | null | null | null | null | null | null | null | null | null | null |
2,403.15279 | Fundus: A Simple-to-Use News Scraper Optimized for High Quality
Extractions | ['Max Dallabetta', 'Conrad Dobberstein', 'Adrian Breiding', 'Alan Akbik'] | ['cs.CL', 'cs.IR'] | This paper introduces Fundus, a user-friendly news scraper that enables users
to obtain millions of high-quality news articles with just a few lines of code.
Unlike existing news scrapers, we use manually crafted, bespoke content
extractors that are specifically tailored to the formatting guidelines of each
supported o... | 2024-03-22T15:22:06Z | 10 pages, 4 figures, ACL 2024, for a screencast see
https://www.youtube.com/watch?v=9GJExMelhdI | null | null | null | null | null | null | null | null | null |
2,403.15322 | CO-Fun: A German Dataset on Company Outsourcing in Fund Prospectuses for
Named Entity Recognition and Relation Extraction | ['Neda Foroutan', 'Markus Schröder', 'Andreas Dengel'] | ['cs.CL'] | The process of cyber mapping gives insights in relationships among financial
entities and service providers. Centered around the outsourcing practices of
companies within fund prospectuses in Germany, we introduce a dataset
specifically designed for named entity recognition and relation extraction
tasks. The labeling p... | 2024-03-22T16:17:55Z | null | null | null | null | null | null | null | null | null | null |
2,403.15356 | Neural Plasticity-Inspired Multimodal Foundation Model for Earth
Observation | ['Zhitong Xiong', 'Yi Wang', 'Fahong Zhang', 'Adam J. Stewart', 'Joëlle Hanna', 'Damian Borth', 'Ioannis Papoutsis', 'Bertrand Le Saux', 'Gustau Camps-Valls', 'Xiao Xiang Zhu'] | ['cs.CV'] | The development of foundation models has revolutionized our ability to
interpret the Earth's surface using satellite observational data. Traditional
models have been siloed, tailored to specific sensors or data types like
optical, radar, and hyperspectral, each with its own unique characteristics.
This specialization h... | 2024-03-22T17:11:47Z | 36 pages, 7 figures | null | null | Neural Plasticity-Inspired Multimodal Foundation Model for Earth Observation | ['Zhitong Xiong', 'Yi Wang', 'Fahong Zhang', 'Adam J. Stewart', 'Joelle Hanna', 'Damian Borth', 'Ioannis Papoutsis', 'B. L. Saux', 'G. Camps-Valls', 'Xiao Xiang Zhu'] | 2,024 | null | 18 | 88 | ['Computer Science'] |
2,403.15377 | InternVideo2: Scaling Foundation Models for Multimodal Video
Understanding | ['Yi Wang', 'Kunchang Li', 'Xinhao Li', 'Jiashuo Yu', 'Yinan He', 'Chenting Wang', 'Guo Chen', 'Baoqi Pei', 'Ziang Yan', 'Rongkun Zheng', 'Jilan Xu', 'Zun Wang', 'Yansong Shi', 'Tianxiang Jiang', 'Songze Li', 'Hongjie Zhang', 'Yifei Huang', 'Yu Qiao', 'Yali Wang', 'Limin Wang'] | ['cs.CV'] | We introduce InternVideo2, a new family of video foundation models (ViFM)
that achieve the state-of-the-art results in video recognition, video-text
tasks, and video-centric dialogue. Our core design is a progressive training
approach that unifies the masked video modeling, crossmodal contrastive
learning, and next tok... | 2024-03-22T17:57:42Z | a technical report about video understanding (accepted to ECCV2024) | null | null | null | null | null | null | null | null | null |
2,403.15378 | Long-CLIP: Unlocking the Long-Text Capability of CLIP | ['Beichen Zhang', 'Pan Zhang', 'Xiaoyi Dong', 'Yuhang Zang', 'Jiaqi Wang'] | ['cs.CV'] | Contrastive Language-Image Pre-training (CLIP) has been the cornerstone for
zero-shot classification, text-image retrieval, and text-image generation by
aligning image and text modalities. Despite its widespread adoption, a
significant limitation of CLIP lies in the inadequate length of text input. The
length of the te... | 2024-03-22T17:58:16Z | ECCV 2024. All codes and models are publicly available at
https://github.com/beichenzbc/Long-CLIP | null | null | null | null | null | null | null | null | null |
2,403.15484 | RakutenAI-7B: Extending Large Language Models for Japanese | ['Rakuten Group', 'Aaron Levine', 'Connie Huang', 'Chenguang Wang', 'Eduardo Batista', 'Ewa Szymanska', 'Hongyi Ding', 'Hou Wei Chou', 'Jean-François Pessiot', 'Johanes Effendi', 'Justin Chiu', 'Kai Torben Ohlhus', 'Karan Chopra', 'Keiji Shinzato', 'Koji Murakami', 'Lee Xiong', 'Lei Chen', 'Maki Kubota', 'Maksim Tkache... | ['cs.CL', 'cs.LG'] | We introduce RakutenAI-7B, a suite of Japanese-oriented large language models
that achieve the best performance on the Japanese LM Harness benchmarks among
the open 7B models. Along with the foundation model, we release instruction-
and chat-tuned models, RakutenAI-7B-instruct and RakutenAI-7B-chat
respectively, under ... | 2024-03-21T06:56:07Z | null | null | null | null | null | null | null | null | null | null |
2,403.15705 | SUP-NeRF: A Streamlined Unification of Pose Estimation and NeRF for
Monocular 3D Object Reconstruction | ['Yuliang Guo', 'Abhinav Kumar', 'Cheng Zhao', 'Ruoyu Wang', 'Xinyu Huang', 'Liu Ren'] | ['cs.CV'] | Monocular 3D reconstruction for categorical objects heavily relies on
accurately perceiving each object's pose. While gradient-based optimization in
a NeRF framework updates the initial pose, this paper highlights that
scale-depth ambiguity in monocular object reconstruction causes failures when
the initial pose deviat... | 2024-03-23T03:56:25Z | null | null | null | null | null | null | null | null | null | null |
2,403.15882 | VLUE: A New Benchmark and Multi-task Knowledge Transfer Learning for
Vietnamese Natural Language Understanding | ['Phong Nguyen-Thuan Do', 'Son Quoc Tran', 'Phu Gia Hoang', 'Kiet Van Nguyen', 'Ngan Luu-Thuy Nguyen'] | ['cs.CL'] | The success of Natural Language Understanding (NLU) benchmarks in various
languages, such as GLUE for English, CLUE for Chinese, KLUE for Korean, and
IndoNLU for Indonesian, has facilitated the evaluation of new NLU models across
a wide range of tasks. To establish a standardized set of benchmarks for
Vietnamese NLU, w... | 2024-03-23T16:26:49Z | Accepted at NAACL 2024 (Findings) | null | null | VLUE: A New Benchmark and Multi-task Knowledge Transfer Learning for Vietnamese Natural Language Understanding | ['Phong Nguyen-Thuan Do', 'Son Quoc Tran', 'Phu Gia Hoang', 'Kiet Van Nguyen', 'N. Nguyen'] | 2,024 | NAACL-HLT | 5 | 50 | ['Computer Science'] |
2,403.16008 | CBT-LLM: A Chinese Large Language Model for Cognitive Behavioral
Therapy-based Mental Health Question Answering | ['Hongbin Na'] | ['cs.CL'] | The recent advancements in artificial intelligence highlight the potential of
language models in psychological health support. While models trained on data
from mental health service platform have achieved preliminary success,
challenges persist in areas such as data scarcity, quality, and ensuring a
solid foundation i... | 2024-03-24T04:34:34Z | Accepted at COLING 2024 | null | null | CBT-LLM: A Chinese Large Language Model for Cognitive Behavioral Therapy-based Mental Health Question Answering | ['Hongbin Na'] | 2,024 | International Conference on Language Resources and Evaluation | 17 | 45 | ['Computer Science'] |
2,403.16023 | RPMArt: Towards Robust Perception and Manipulation for Articulated
Objects | ['Junbo Wang', 'Wenhai Liu', 'Qiaojun Yu', 'Yang You', 'Liu Liu', 'Weiming Wang', 'Cewu Lu'] | ['cs.RO', 'cs.AI', 'cs.CV'] | Articulated objects are commonly found in daily life. It is essential that
robots can exhibit robust perception and manipulation skills for articulated
objects in real-world robotic applications. However, existing methods for
articulated objects insufficiently address noise in point clouds and struggle
to bridge the ga... | 2024-03-24T05:55:39Z | 8 pages, 7 figures, accepted by 2024 IEEE/RSJ International
Conference on Intelligent Robots and Systems (IROS 2024), project website at
https://r-pmart.github.io | null | null | null | null | null | null | null | null | null |
2,403.16051 | Segment Anything Model for Road Network Graph Extraction | ['Congrui Hetang', 'Haoru Xue', 'Cindy Le', 'Tianwei Yue', 'Wenping Wang', 'Yihui He'] | ['cs.CV'] | We propose SAM-Road, an adaptation of the Segment Anything Model (SAM) for
extracting large-scale, vectorized road network graphs from satellite imagery.
To predict graph geometry, we formulate it as a dense semantic segmentation
task, leveraging the inherent strengths of SAM. The image encoder of SAM is
fine-tuned to ... | 2024-03-24T07:36:38Z | Accepted by IEEE/CVF Computer Vision and Pattern Recognition
Conference (CVPR) 2024, 2nd Workshop on Scene Graphs and Graph Representation
Learning | null | null | null | null | null | null | null | null | null |
2,403.16158 | Korean Bio-Medical Corpus (KBMC) for Medical Named Entity Recognition | ['Sungjoo Byun', 'Jiseung Hong', 'Sumin Park', 'Dongjun Jang', 'Jean Seo', 'Minseok Kim', 'Chaeyoung Oh', 'Hyopil Shin'] | ['cs.CL'] | Named Entity Recognition (NER) plays a pivotal role in medical Natural
Language Processing (NLP). Yet, there has not been an open-source medical NER
dataset specifically for the Korean language. To address this, we utilized
ChatGPT to assist in constructing the KBMC (Korean Bio-Medical Corpus), which
we are now present... | 2024-03-24T13:51:05Z | null | LREC-COLING 2024 | null | null | null | null | null | null | null | null |
2,403.16443 | CodeS: Natural Language to Code Repository via Multi-Layer Sketch | ['Daoguang Zan', 'Ailun Yu', 'Wei Liu', 'Dong Chen', 'Bo Shen', 'Wei Li', 'Yafen Yao', 'Yongshun Gong', 'Xiaolin Chen', 'Bei Guan', 'Zhiguang Yang', 'Yongji Wang', 'Qianxiang Wang', 'Lizhen Cui'] | ['cs.CL', 'cs.AI', 'cs.SE'] | The impressive performance of large language models (LLMs) on code-related
tasks has shown the potential of fully automated software development. In light
of this, we introduce a new software engineering task, namely Natural Language
to code Repository (NL2Repo). This task aims to generate an entire code
repository fro... | 2024-03-25T06:09:55Z | https://github.com/NL2Code/CodeS | null | null | null | null | null | null | null | null | null |
2,403.16516 | Visually Guided Generative Text-Layout Pre-training for Document
Intelligence | ['Zhiming Mao', 'Haoli Bai', 'Lu Hou', 'Jiansheng Wei', 'Xin Jiang', 'Qun Liu', 'Kam-Fai Wong'] | ['cs.CL', 'cs.CV'] | Prior study shows that pre-training techniques can boost the performance of
visual document understanding (VDU), which typically requires models to gain
abilities to perceive and reason both document texts and layouts (e.g.,
locations of texts and table-cells). To this end, we propose visually guided
generative text-la... | 2024-03-25T08:00:43Z | Accepted to NAACL 2024 main conference. The first version of this
paper was submitted to OpenReview
(https://openreview.net/forum?id=ARtBIBAmNR) in June 2023 | null | null | null | null | null | null | null | null | null |
2,403.16558 | Elysium: Exploring Object-level Perception in Videos via MLLM | ['Han Wang', 'Yanjie Wang', 'Yongjie Ye', 'Yuxiang Nie', 'Can Huang'] | ['cs.CV'] | Multi-modal Large Language Models (MLLMs) have demonstrated their ability to
perceive objects in still images, but their application in video-related tasks,
such as object tracking, remains understudied. This lack of exploration is
primarily due to two key challenges. Firstly, extensive pretraining on
large-scale video... | 2024-03-25T09:17:15Z | null | null | null | Elysium: Exploring Object-level Perception in Videos via MLLM | ['Hang Wang', 'Yanjie Wang', 'Yongjie Ye', 'Yuxiang Nie', 'Can Huang'] | 2,024 | European Conference on Computer Vision | 23 | 80 | ['Computer Science'] |
2,403.16614 | Semantically Enriched Cross-Lingual Sentence Embeddings for
Crisis-related Social Media Texts | ['Rabindra Lamsal', 'Maria Rodriguez Read', 'Shanika Karunasekera'] | ['cs.CL'] | Tasks such as semantic search and clustering on crisis-related social media
texts enhance our comprehension of crisis discourse, aiding decision-making and
targeted interventions. Pre-trained language models have advanced performance
in crisis informatics, but their contextual embeddings lack semantic
meaningfulness. A... | 2024-03-25T10:44:38Z | Accepted to ISCRAM 2024 | null | null | Semantically Enriched Cross-Lingual Sentence Embeddings for Crisis-related Social Media Texts | ['Rabindra Lamsal', 'M. Read', 'S. Karunasekera'] | 2,024 | Proceedings of the International ISCRAM Conference | 2 | 59 | ['Computer Science'] |
2,403.16627 | SDXS: Real-Time One-Step Latent Diffusion Models with Image Conditions | ['Yuda Song', 'Zehao Sun', 'Xuanwu Yin'] | ['cs.CV'] | Recent advancements in diffusion models have positioned them at the forefront
of image generation. Despite their superior performance, diffusion models are
not without drawbacks; they are characterized by complex architectures and
substantial computational demands, resulting in significant latency due to
their iterativ... | 2024-03-25T11:16:23Z | null | null | null | SDXS: Real-Time One-Step Latent Diffusion Models with Image Conditions | ['Yuda Song', 'Zehao Sun', 'Xuanwu Yin'] | 2,024 | arXiv.org | 18 | 62 | ['Computer Science'] |
2,403.17068 | Semantic Ranking for Automated Adversarial Technique Annotation in
Security Text | ['Udesh Kumarasinghe', 'Ahmed Lekssays', 'Husrev Taha Sencar', 'Sabri Boughorbel', 'Charitha Elvitigala', 'Preslav Nakov'] | ['cs.CR'] | We introduce a new method for extracting structured threat behaviors from
threat intelligence text. Our method is based on a multi-stage ranking
architecture that allows jointly optimizing for efficiency and effectiveness.
Therefore, we believe this problem formulation better aligns with the
real-world nature of the ta... | 2024-03-25T18:03:58Z | null | null | null | Semantic Ranking for Automated Adversarial Technique Annotation in Security Text | ['Udesh Kumarasinghe', 'Ahmed Lekssays', 'H. Sencar', 'Sabri Boughorbel', 'Charitha Elvitigala', 'Preslav Nakov'] | 2,024 | ACM Asia Conference on Computer and Communications Security | 7 | 48 | ['Computer Science'] |
2,403.17297 | InternLM2 Technical Report | ['Zheng Cai', 'Maosong Cao', 'Haojiong Chen', 'Kai Chen', 'Keyu Chen', 'Xin Chen', 'Xun Chen', 'Zehui Chen', 'Zhi Chen', 'Pei Chu', 'Xiaoyi Dong', 'Haodong Duan', 'Qi Fan', 'Zhaoye Fei', 'Yang Gao', 'Jiaye Ge', 'Chenya Gu', 'Yuzhe Gu', 'Tao Gui', 'Aijia Guo', 'Qipeng Guo', 'Conghui He', 'Yingfan Hu', 'Ting Huang', 'Tao... | ['cs.CL', 'cs.AI'] | The evolution of Large Language Models (LLMs) like ChatGPT and GPT-4 has
sparked discussions on the advent of Artificial General Intelligence (AGI).
However, replicating such advancements in open-source models has been
challenging. This paper introduces InternLM2, an open-source LLM that
outperforms its predecessors in... | 2024-03-26T00:53:24Z | null | null | null | InternLM2 Technical Report | ['Zheng Cai', 'Maosong Cao', 'Haojiong Chen', 'Kai Chen', 'Keyu Chen', 'Xin Chen', 'Xun Chen', 'Zehui Chen', 'Zhi Chen', 'Pei Chu', 'Xiao-wen Dong', 'Haodong Duan', 'Qi Fan', 'Zhaoye Fei', 'Yang Gao', 'Jiaye Ge', 'Chenya Gu', 'Yuzhe Gu', 'Tao Gui', 'Aijia Guo', 'Qipeng Guo', 'Conghui He', 'Yingfan Hu', 'Ting Huang', 'T... | 2,024 | arXiv.org | 209 | 0 | ['Computer Science'] |
2,403.17377 | Self-Rectifying Diffusion Sampling with Perturbed-Attention Guidance | ['Donghoon Ahn', 'Hyoungwon Cho', 'Jaewon Min', 'Wooseok Jang', 'Jungwoo Kim', 'SeonHwa Kim', 'Hyun Hee Park', 'Kyong Hwan Jin', 'Seungryong Kim'] | ['cs.CV', 'cs.AI', 'cs.LG'] | Recent studies have demonstrated that diffusion models are capable of
generating high-quality samples, but their quality heavily depends on sampling
guidance techniques, such as classifier guidance (CG) and classifier-free
guidance (CFG). These techniques are often not applicable in unconditional
generation or in vario... | 2024-03-26T04:49:11Z | Project page is available at
https://ku-cvlab.github.io/Perturbed-Attention-Guidance. This version
reflects the ECCV 2024 camera-ready submission | null | null | null | null | null | null | null | null | null |
2,403.17528 | Multilingual Sentence-T5: Scalable Sentence Encoders for Multilingual
Applications | ['Chihiro Yano', 'Akihiko Fukuchi', 'Shoko Fukasawa', 'Hideyuki Tachibana', 'Yotaro Watanabe'] | ['cs.CL'] | Prior work on multilingual sentence embedding has demonstrated that the
efficient use of natural language inference (NLI) data to build
high-performance models can outperform conventional methods. However, the
potential benefits from the recent ``exponential'' growth of language models
with billions of parameters have ... | 2024-03-26T09:31:55Z | Accepted in LREC-COLING 2024 | null | null | null | null | null | null | null | null | null |
2,403.17694 | AniPortrait: Audio-Driven Synthesis of Photorealistic Portrait Animation | ['Huawei Wei', 'Zejun Yang', 'Zhisheng Wang'] | ['cs.CV', 'cs.GR', 'eess.IV'] | In this study, we propose AniPortrait, a novel framework for generating
high-quality animation driven by audio and a reference portrait image. Our
methodology is divided into two stages. Initially, we extract 3D intermediate
representations from audio and project them into a sequence of 2D facial
landmarks. Subsequentl... | 2024-03-26T13:35:02Z | null | null | null | null | null | null | null | null | null | null |
2,403.17834 | Developing Generalist Foundation Models from a Multimodal Dataset for 3D
Computed Tomography | ['Ibrahim Ethem Hamamci', 'Sezgin Er', 'Chenyu Wang', 'Furkan Almas', 'Ayse Gulnihan Simsek', 'Sevval Nil Esirgun', 'Irem Doga', 'Omer Faruk Durugol', 'Weicheng Dai', 'Murong Xu', 'Muhammed Furkan Dasdelen', 'Bastian Wittmann', 'Tamaz Amiranashvili', 'Enis Simsar', 'Mehmet Simsar', 'Emine Bensu Erdemir', 'Abdullah Alan... | ['cs.CV'] | While computer vision has achieved tremendous success with multimodal
encoding and direct textual interaction with images via chat-based large
language models, similar advancements in medical imaging AI, particularly in 3D
imaging, have been limited due to the scarcity of comprehensive datasets. To
address this critica... | 2024-03-26T16:19:56Z | null | null | null | null | null | null | null | null | null | null |
2,403.17848 | ArabicaQA: A Comprehensive Dataset for Arabic Question Answering | ['Abdelrahman Abdallah', 'Mahmoud Kasem', 'Mahmoud Abdalla', 'Mohamed Mahmoud', 'Mohamed Elkasaby', 'Yasser Elbendary', 'Adam Jatowt'] | ['cs.CL', 'cs.IR'] | In this paper, we address the significant gap in Arabic natural language
processing (NLP) resources by introducing ArabicaQA, the first large-scale
dataset for machine reading comprehension and open-domain question answering in
Arabic. This comprehensive dataset, consisting of 89,095 answerable and 3,701
unanswerable q... | 2024-03-26T16:37:54Z | Accepted at SIGIR 2024 | null | null | ArabicaQA: A Comprehensive Dataset for Arabic Question Answering | ['Abdelrahman Abdallah', 'M. Kasem', 'Mahmoud Abdalla', 'Mohamed Mahmoud', 'Mohamed Elkasaby', 'Yasser Elbendary', 'Adam Jatowt'] | 2,024 | Annual International ACM SIGIR Conference on Research and Development in Information Retrieval | 16 | 63 | ['Computer Science'] |
2,403.17887 | The Unreasonable Ineffectiveness of the Deeper Layers | ['Andrey Gromov', 'Kushal Tirumala', 'Hassan Shapourian', 'Paolo Glorioso', 'Daniel A. Roberts'] | ['cs.CL', 'cs.LG', 'stat.ML'] | How is knowledge stored in an LLM's weights? We study this via layer pruning:
if removing a certain layer does not affect model performance in common
question-answering benchmarks, then the weights in that layer are not necessary
for storing the knowledge needed to answer those questions. To find these
unnecessary para... | 2024-03-26T17:20:04Z | 10 + 14 pages, 6 + 5 figures. v2: ICLR camera-ready version;
additional experiments in an extended discussion | null | null | null | null | null | null | null | null | null |
2,403.17889 | Large scale paired antibody language models | ['Henry Kenlay', 'Frédéric A. Dreyer', 'Aleksandr Kovaltsuk', 'Dom Miketa', 'Douglas Pires', 'Charlotte M. Deane'] | ['q-bio.BM', 'cs.LG'] | Antibodies are proteins produced by the immune system that can identify and
neutralise a wide variety of antigens with high specificity and affinity, and
constitute the most successful class of biotherapeutics. With the advent of
next-generation sequencing, billions of antibody sequences have been collected
in recent y... | 2024-03-26T17:21:54Z | 14 pages, 2 figures, 6 tables, model weights available at
https://zenodo.org/doi/10.5281/zenodo.10876908 | null | null | Large scale paired antibody language models | ['Henry Kenlay', 'Frédéric A. Dreyer', 'Aleksandr Kovaltsuk', 'Dom Miketa', 'Douglas E. V. Pires', 'Charlotte M. Deane'] | 2,024 | PLoS Comput. Biol. | 24 | 54 | ['Medicine', 'Computer Science', 'Biology'] |
2,403.17902 | Serpent: Scalable and Efficient Image Restoration via Multi-scale
Structured State Space Models | ['Mohammad Shahab Sepehri', 'Zalan Fabian', 'Mahdi Soltanolkotabi'] | ['eess.IV', 'cs.CV', 'cs.LG', 'I.4.4; I.4.5'] | The landscape of computational building blocks of efficient image restoration
architectures is dominated by a combination of convolutional processing and
various attention mechanisms. However, convolutional filters, while efficient,
are inherently local and therefore struggle with modeling long-range
dependencies in im... | 2024-03-26T17:43:15Z | null | null | null | Serpent: Scalable and Efficient Image Restoration via Multi-scale Structured State Space Models | ['Mohammad Shahab Sepehri', 'Zalan Fabian', 'M. Soltanolkotabi'] | 2,024 | arXiv.org | 5 | 28 | ['Computer Science', 'Engineering'] |
2,403.17921 | The Need for Speed: Pruning Transformers with One Recipe | ['Samir Khaki', 'Konstantinos N. Plataniotis'] | ['cs.LG'] | We introduce the $\textbf{O}$ne-shot $\textbf{P}$runing $\textbf{T}$echnique
for $\textbf{I}$nterchangeable $\textbf{N}$etworks ($\textbf{OPTIN}$) framework
as a tool to increase the efficiency of pre-trained transformer architectures
$\textit{without requiring re-training}$. Recent works have explored improving
transf... | 2024-03-26T17:55:58Z | Accepted in the International Conference on Learning Representations
(ICLR) 2024 | null | null | null | null | null | null | null | null | null |
2,403.18025 | Improving Pre-trained Language Model Sensitivity via Mask Specific
losses: A case study on Biomedical NER | ['Micheal Abaho', 'Danushka Bollegala', 'Gary Leeming', 'Dan Joyce', 'Iain E Buchan'] | ['cs.CL', 'cs.AI', 'cs.IR', 'cs.LG'] | Adapting language models (LMs) to novel domains is often achieved through
fine-tuning a pre-trained LM (PLM) on domain-specific data. Fine-tuning
introduces new knowledge into an LM, enabling it to comprehend and efficiently
perform a target domain task. Fine-tuning can however be inadvertently
insensitive if it ignore... | 2024-03-26T18:23:16Z | Paper alrerady accepted for publishing by the NAACL 2024 conference
(main conference paper) | null | null | null | null | null | null | null | null | null |
2,403.1814 | Juru: Legal Brazilian Large Language Model from Reputable Sources | ['Roseval Malaquias Junior', 'Ramon Pires', 'Roseli Romero', 'Rodrigo Nogueira'] | ['cs.CL', 'cs.AI'] | The high computational cost associated with pretraining large language models
limits their research. Two strategies have emerged to address this issue:
domain specialization and pretraining with high-quality data. To explore these
strategies, we specialized the Sabi\'a-2 Small model with 1.9 billion unique
tokens from ... | 2024-03-26T22:54:12Z | null | null | null | Juru: Legal Brazilian Large Language Model from Reputable Sources | ['Roseval Malaquias Junior', 'Ramon Pires', 'R. Romero', 'Rodrigo Nogueira'] | 2,024 | arXiv.org | 0 | 24 | ['Computer Science'] |
2,403.18187 | LayoutFlow: Flow Matching for Layout Generation | ['Julian Jorge Andrade Guerreiro', 'Naoto Inoue', 'Kento Masui', 'Mayu Otani', 'Hideki Nakayama'] | ['cs.CV'] | Finding a suitable layout represents a crucial task for diverse applications
in graphic design. Motivated by simpler and smoother sampling trajectories, we
explore the use of Flow Matching as an alternative to current diffusion-based
layout generation models. Specifically, we propose LayoutFlow, an efficient
flow-based... | 2024-03-27T01:40:21Z | Accepted to ECCV 2024, Project Page:
https://julianguerreiro.github.io/layoutflow/ | null | null | null | null | null | null | null | null | null |
2,403.18277 | BlendX: Complex Multi-Intent Detection with Blended Patterns | ['Yejin Yoon', 'Jungyeon Lee', 'Kangsan Kim', 'Chanhee Park', 'Taeuk Kim'] | ['cs.CL'] | Task-oriented dialogue (TOD) systems are commonly designed with the
presumption that each utterance represents a single intent. However, this
assumption may not accurately reflect real-world situations, where users
frequently express multiple intents within a single utterance. While there is
an emerging interest in mul... | 2024-03-27T06:13:04Z | Accepted to LREC-COLING2024 | null | null | BlendX: Complex Multi-Intent Detection with Blended Patterns | ['Yejin Yoon', 'Jungyeon Lee', 'Kangsan Kim', 'Chanhee Park', 'Taeuk Kim'] | 2,024 | International Conference on Language Resources and Evaluation | 4 | 21 | ['Computer Science'] |
2,403.18338 | mALBERT: Is a Compact Multilingual BERT Model Still Worth It? | ['Christophe Servan', 'Sahar Ghannay', 'Sophie Rosset'] | ['cs.AI'] | Within the current trend of Pretained Language Models (PLM), emerge more and
more criticisms about the ethical andecological impact of such models. In this
article, considering these critical remarks, we propose to focus on
smallermodels, such as compact models like ALBERT, which are more ecologically
virtuous than the... | 2024-03-27T08:25:28Z | The 2024 Joint International Conference on Computational Linguistics,
Language Resources and Evaluation, May 2024, Torino, Italy | null | null | mALBERT: Is a Compact Multilingual BERT Model Still Worth It? | ['Christophe Servan', 'Sahar Ghannay', 'Sophie Rosset'] | 2,024 | International Conference on Language Resources and Evaluation | 1 | 35 | ['Computer Science'] |
2,403.18421 | BioMedLM: A 2.7B Parameter Language Model Trained On Biomedical Text | ['Elliot Bolton', 'Abhinav Venigalla', 'Michihiro Yasunaga', 'David Hall', 'Betty Xiong', 'Tony Lee', 'Roxana Daneshjou', 'Jonathan Frankle', 'Percy Liang', 'Michael Carbin', 'Christopher D. Manning'] | ['cs.CL', 'cs.AI'] | Models such as GPT-4 and Med-PaLM 2 have demonstrated impressive performance
on a wide variety of biomedical NLP tasks. However, these models have hundreds
of billions of parameters, are computationally expensive to run, require users
to send their input data over the internet, and are trained on unknown data
sources. ... | 2024-03-27T10:18:21Z | 23 pages | null | null | BioMedLM: A 2.7B Parameter Language Model Trained On Biomedical Text | ['Elliot Bolton', 'Abhinav Venigalla', 'Michihiro Yasunaga', 'David Hall', 'Betty Xiong', 'Tony Lee', 'R. Daneshjou', 'Jonathan Frankle', 'Percy Liang', 'Michael Carbin', 'Christopher D. Manning'] | 2,024 | arXiv.org | 64 | 66 | ['Computer Science'] |
2,403.18647 | SDSAT: Accelerating LLM Inference through Speculative Decoding with
Semantic Adaptive Tokens | ['Chengbo Liu', 'Yong Zhu'] | ['cs.CL'] | We propose an acceleration scheme for large language models (LLMs) through
Speculative Decoding with Semantic Adaptive Tokens (SDSAT). The primary
objective of this design is to enhance the LLM model's ability to generate
draft tokens more accurately without compromising the model's accuracy. The
core strategies involv... | 2024-03-27T14:54:27Z | 12 pages, 7 figures | null | null | SDSAT: Accelerating LLM Inference through Speculative Decoding with Semantic Adaptive Tokens | ['Chengbo Liu', 'Yong Zhu'] | 2,024 | arXiv.org | 0 | 20 | ['Computer Science'] |
2,403.18769 | Improved Neural Protoform Reconstruction via Reflex Prediction | ['Liang Lu', 'Jingzhi Wang', 'David R. Mortensen'] | ['cs.CL'] | Protolanguage reconstruction is central to historical linguistics. The
comparative method, one of the most influential theoretical and methodological
frameworks in the history of the language sciences, allows linguists to infer
protoforms (reconstructed ancestral words) from their reflexes (related modern
words) based ... | 2024-03-27T17:13:38Z | Accepted to LREC-COLING 2024 | null | null | null | null | null | null | null | null | null |
2,403.18814 | Mini-Gemini: Mining the Potential of Multi-modality Vision Language
Models | ['Yanwei Li', 'Yuechen Zhang', 'Chengyao Wang', 'Zhisheng Zhong', 'Yixin Chen', 'Ruihang Chu', 'Shaoteng Liu', 'Jiaya Jia'] | ['cs.CV', 'cs.AI', 'cs.CL'] | In this work, we introduce Mini-Gemini, a simple and effective framework
enhancing multi-modality Vision Language Models (VLMs). Despite the
advancements in VLMs facilitating basic visual dialog and reasoning, a
performance gap persists compared to advanced models like GPT-4 and Gemini. We
try to narrow the gap by mini... | 2024-03-27T17:59:04Z | Code and models are available at
https://github.com/dvlab-research/MiniGemini | null | null | null | null | null | null | null | null | null |
2,403.19154 | STaR-GATE: Teaching Language Models to Ask Clarifying Questions | ['Chinmaya Andukuri', 'Jan-Philipp Fränken', 'Tobias Gerstenberg', 'Noah D. Goodman'] | ['cs.CL', 'cs.AI'] | When prompting language models to complete a task, users often leave
important aspects unsaid. While asking questions could resolve this ambiguity
(GATE; Li et al., 2023), models often struggle to ask good questions. We
explore a language model's ability to self-improve (STaR; Zelikman et al.,
2022) by rewarding the mo... | 2024-03-28T05:35:22Z | null | null | null | null | null | null | null | null | null | null |
2,403.1927 | sDPO: Don't Use Your Data All at Once | ['Dahyun Kim', 'Yungi Kim', 'Wonho Song', 'Hyeonwoo Kim', 'Yunsu Kim', 'Sanghoon Kim', 'Chanjun Park'] | ['cs.CL', 'cs.AI'] | As development of large language models (LLM) progresses, aligning them with
human preferences has become increasingly important. We propose stepwise DPO
(sDPO), an extension of the recently popularized direct preference optimization
(DPO) for alignment tuning. This approach involves dividing the available
preference d... | 2024-03-28T09:56:04Z | null | null | null | sDPO: Don't Use Your Data All at Once | ['Dahyun Kim', 'Yungi Kim', 'Wonho Song', 'Hyeonwoo Kim', 'Yunsu Kim', 'Sanghoon Kim', 'Chanjun Park'] | 2,024 | arXiv.org | 35 | 31 | ['Computer Science'] |
2,403.19318 | TableLLM: Enabling Tabular Data Manipulation by LLMs in Real Office
Usage Scenarios | ['Xiaokang Zhang', 'Sijia Luo', 'Bohan Zhang', 'Zeyao Ma', 'Jing Zhang', 'Yang Li', 'Guanlin Li', 'Zijun Yao', 'Kangli Xu', 'Jinchang Zhou', 'Daniel Zhang-Li', 'Jifan Yu', 'Shu Zhao', 'Juanzi Li', 'Jie Tang'] | ['cs.CL'] | We introduce TableLLM, a robust large language model (LLM) with 8 billion
parameters, purpose-built for proficiently handling tabular data manipulation
tasks, whether they are embedded within documents or spreadsheets, catering to
real-world office scenarios. We propose a distant supervision method for
training, which ... | 2024-03-28T11:21:12Z | https://tablellm.github.io/ | null | null | TableLLM: Enabling Tabular Data Manipulation by LLMs in Real Office Usage Scenarios | ['Xiaokang Zhang', 'Jing Zhang', 'Zeyao Ma', 'Yang Li', 'Bohan Zhang', 'Guanlin Li', 'Zijun Yao', 'Kangli Xu', 'Jinchang Zhou', 'Daniel Zhang-Li', 'Jifan Yu', 'Shu Zhao', 'Juan-Zi Li', 'Jie Tang'] | 2,024 | arXiv.org | 37 | 53 | ['Computer Science'] |
2,403.19522 | Model Stock: All we need is just a few fine-tuned models | ['Dong-Hwan Jang', 'Sangdoo Yun', 'Dongyoon Han'] | ['cs.LG', 'cs.CV'] | This paper introduces an efficient fine-tuning method for large pre-trained
models, offering strong in-distribution (ID) and out-of-distribution (OOD)
performance. Breaking away from traditional practices that need a multitude of
fine-tuned models for averaging, our approach employs significantly fewer
models to achiev... | 2024-03-28T15:57:20Z | Code at https://github.com/naver-ai/model-stock | null | null | Model Stock: All we need is just a few fine-tuned models | ['Dong-Hwan Jang', 'Sangdoo Yun', 'Dongyoon Han'] | 2,024 | European Conference on Computer Vision | 45 | 35 | ['Computer Science'] |
2,403.19559 | Improving Adversarial Data Collection by Supporting Annotators: Lessons
from GAHD, a German Hate Speech Dataset | ['Janis Goldzycher', 'Paul Röttger', 'Gerold Schneider'] | ['cs.CL'] | Hate speech detection models are only as good as the data they are trained
on. Datasets sourced from social media suffer from systematic gaps and biases,
leading to unreliable models with simplistic decision boundaries. Adversarial
datasets, collected by exploiting model weaknesses, promise to fix this
problem. However... | 2024-03-28T16:44:14Z | Accepted at NAACL 2024 (main conference) | null | null | null | null | null | null | null | null | null |
2,403.19588 | DenseNets Reloaded: Paradigm Shift Beyond ResNets and ViTs | ['Donghyun Kim', 'Byeongho Heo', 'Dongyoon Han'] | ['cs.CV', 'cs.LG', 'cs.NE'] | This paper revives Densely Connected Convolutional Networks (DenseNets) and
reveals the underrated effectiveness over predominant ResNet-style
architectures. We believe DenseNets' potential was overlooked due to untouched
training methods and traditional design elements not fully revealing their
capabilities. Our pilot... | 2024-03-28T17:12:39Z | ECCV 2024. Code at https://github.com/naver-ai/rdnet | null | null | null | null | null | null | null | null | null |
2,403.19654 | RSMamba: Remote Sensing Image Classification with State Space Model | ['Keyan Chen', 'Bowen Chen', 'Chenyang Liu', 'Wenyuan Li', 'Zhengxia Zou', 'Zhenwei Shi'] | ['cs.CV'] | Remote sensing image classification forms the foundation of various
understanding tasks, serving a crucial function in remote sensing image
interpretation. The recent advancements of Convolutional Neural Networks (CNNs)
and Transformers have markedly enhanced classification accuracy. Nonetheless,
remote sensing scene c... | 2024-03-28T17:59:49Z | null | null | null | null | null | null | null | null | null | null |
2,403.19655 | GaussianCube: A Structured and Explicit Radiance Representation for 3D
Generative Modeling | ['Bowen Zhang', 'Yiji Cheng', 'Jiaolong Yang', 'Chunyu Wang', 'Feng Zhao', 'Yansong Tang', 'Dong Chen', 'Baining Guo'] | ['cs.CV'] | We introduce a radiance representation that is both structured and fully
explicit and thus greatly facilitates 3D generative modeling. Existing radiance
representations either require an implicit feature decoder, which significantly
degrades the modeling power of the representation, or are spatially
unstructured, makin... | 2024-03-28T17:59:50Z | NIPS 2024 camera-ready version; Project page:
https://gaussiancube.github.io/ | null | null | null | null | null | null | null | null | null |
2,403.19887 | Jamba: A Hybrid Transformer-Mamba Language Model | ['Opher Lieber', 'Barak Lenz', 'Hofit Bata', 'Gal Cohen', 'Jhonathan Osin', 'Itay Dalmedigos', 'Erez Safahi', 'Shaked Meirom', 'Yonatan Belinkov', 'Shai Shalev-Shwartz', 'Omri Abend', 'Raz Alon', 'Tomer Asida', 'Amir Bergman', 'Roman Glozman', 'Michael Gokhman', 'Avashalom Manevich', 'Nir Ratner', 'Noam Rozen', 'Erez S... | ['cs.CL', 'cs.LG'] | We present Jamba, a new base large language model based on a novel hybrid
Transformer-Mamba mixture-of-experts (MoE) architecture. Specifically, Jamba
interleaves blocks of Transformer and Mamba layers, enjoying the benefits of
both model families. MoE is added in some of these layers to increase model
capacity while k... | 2024-03-28T23:55:06Z | Webpage: https://www.ai21.com/jamba | null | null | Jamba: A Hybrid Transformer-Mamba Language Model | ['Opher Lieber', 'Barak Lenz', 'Hofit Bata', 'Gal Cohen', 'Jhonathan Osin', 'Itay Dalmedigos', 'Erez Safahi', 'S. Meirom', 'Yonatan Belinkov', 'Shai Shalev-Shwartz', 'Omri Abend', 'Raz Alon', 'Tomer Asida', 'Amir Bergman', 'Roman Glozman', 'Michael Gokhman', 'Avshalom Manevich', 'Nir Ratner', 'N. Rozen', 'Erez Shwartz'... | 2,024 | arXiv.org | 229 | 56 | ['Computer Science'] |
2,403.19924 | SceneTracker: Long-term Scene Flow Estimation Network | ['Bo Wang', 'Jian Li', 'Yang Yu', 'Li Liu', 'Zhenping Sun', 'Dewen Hu'] | ['cs.CV'] | Considering that scene flow estimation has the capability of the spatial
domain to focus but lacks the coherence of the temporal domain, this study
proposes long-term scene flow estimation (LSFE), a comprehensive task that can
simultaneously capture the fine-grained and long-term 3D motion in an online
manner. We intro... | 2024-03-29T02:22:54Z | null | IEEE Transactions on Pattern Analysis and Machine Intelligence
(TPAMI), 2025 | 10.1109/TPAMI.2025.3572489 | null | null | null | null | null | null | null |
2,403.19967 | Rewrite the Stars | ['Xu Ma', 'Xiyang Dai', 'Yue Bai', 'Yizhou Wang', 'Yun Fu'] | ['cs.CV'] | Recent studies have drawn attention to the untapped potential of the "star
operation" (element-wise multiplication) in network design. While intuitive
explanations abound, the foundational rationale behind its application remains
largely unexplored. Our study attempts to reveal the star operation's ability
to map input... | 2024-03-29T04:10:07Z | Accepted by CVPR 2024. Codes are made publically available at
https://github.com/ma-xu/Rewrite-the-Stars | null | null | null | null | null | null | null | null | null |
2,403.2018 | Measuring Taiwanese Mandarin Language Understanding | ['Po-Heng Chen', 'Sijia Cheng', 'Wei-Lin Chen', 'Yen-Ting Lin', 'Yun-Nung Chen'] | ['cs.CL'] | The evaluation of large language models (LLMs) has drawn substantial
attention in the field recently. This work focuses on evaluating LLMs in a
Chinese context, specifically, for Traditional Chinese which has been largely
underrepresented in existing benchmarks. We present TMLU, a holistic evaluation
suit tailored for ... | 2024-03-29T13:56:21Z | Preprint. Under review | null | null | null | null | null | null | null | null | null |
2,403.20208 | Unleashing the Potential of Large Language Models for Predictive Tabular
Tasks in Data Science | ['Yazheng Yang', 'Yuqi Wang', 'Yaxuan Li', 'Sankalok Sen', 'Lei Li', 'Qi Liu'] | ['cs.LG', 'cs.AI'] | In the domain of data science, the predictive tasks of classification,
regression, and imputation of missing values are commonly encountered
challenges associated with tabular data. This research endeavors to apply Large
Language Models (LLMs) towards addressing these predictive tasks. Despite their
proficiency in comp... | 2024-03-29T14:41:21Z | 10 pages | null | null | null | null | null | null | null | null | null |
2,403.20266 | Latxa: An Open Language Model and Evaluation Suite for Basque | ['Julen Etxaniz', 'Oscar Sainz', 'Naiara Perez', 'Itziar Aldabe', 'German Rigau', 'Eneko Agirre', 'Aitor Ormazabal', 'Mikel Artetxe', 'Aitor Soroa'] | ['cs.CL', 'cs.AI', 'cs.LG'] | We introduce Latxa, a family of large language models for Basque ranging from
7 to 70 billion parameters. Latxa is based on Llama 2, which we continue
pretraining on a new Basque corpus comprising 4.3M documents and 4.2B tokens.
Addressing the scarcity of high-quality benchmarks for Basque, we further
introduce 4 multi... | 2024-03-29T16:16:48Z | ACL 2024 | Proceedings of the 62nd Annual Meeting of the Association for
Computational Linguistics (Volume 1: Long Papers), pages 14952--14972. 2024 | null | null | null | null | null | null | null | null |
2,403.20271 | Draw-and-Understand: Leveraging Visual Prompts to Enable MLLMs to
Comprehend What You Want | ['Weifeng Lin', 'Xinyu Wei', 'Ruichuan An', 'Peng Gao', 'Bocheng Zou', 'Yulin Luo', 'Siyuan Huang', 'Shanghang Zhang', 'Hongsheng Li'] | ['cs.CV'] | In this paper, we present the Draw-and-Understand framework, exploring how to
integrate visual prompting understanding capabilities into Multimodal Large
Language Models (MLLMs). Visual prompts allow users to interact through
multi-modal instructions, enhancing the models' interactivity and fine-grained
image comprehen... | 2024-03-29T16:26:20Z | 30 pages, 8 figures, 15 tables | null | null | null | null | null | null | null | null | null |
2,403.20327 | Gecko: Versatile Text Embeddings Distilled from Large Language Models | ['Jinhyuk Lee', 'Zhuyun Dai', 'Xiaoqi Ren', 'Blair Chen', 'Daniel Cer', 'Jeremy R. Cole', 'Kai Hui', 'Michael Boratko', 'Rajvi Kapadia', 'Wen Ding', 'Yi Luan', 'Sai Meher Karthik Duddu', 'Gustavo Hernandez Abrego', 'Weiqiang Shi', 'Nithi Gupta', 'Aditya Kusupati', 'Prateek Jain', 'Siddhartha Reddy Jonnalagadda', 'Ming-... | ['cs.CL', 'cs.AI'] | We present Gecko, a compact and versatile text embedding model. Gecko
achieves strong retrieval performance by leveraging a key idea: distilling
knowledge from large language models (LLMs) into a retriever. Our two-step
distillation process begins with generating diverse, synthetic paired data
using an LLM. Next, we fu... | 2024-03-29T17:56:40Z | 18 pages | null | null | null | null | null | null | null | null | null |
2,404.00086 | DVIS-DAQ: Improving Video Segmentation via Dynamic Anchor Queries | ['Yikang Zhou', 'Tao Zhang', 'Shunping Ji', 'Shuicheng Yan', 'Xiangtai Li'] | ['cs.CV'] | Modern video segmentation methods adopt object queries to perform inter-frame
association and demonstrate satisfactory performance in tracking continuously
appearing objects despite large-scale motion and transient occlusion. However,
they all underperform on newly emerging and disappearing objects that are
common in t... | 2024-03-29T17:58:50Z | Accepted by ECCV-2024 | null | null | null | null | null | null | null | null | null |
2,404.00376 | Small Language Models Learn Enhanced Reasoning Skills from Medical
Textbooks | ['Hyunjae Kim', 'Hyeon Hwang', 'Jiwoo Lee', 'Sihyeon Park', 'Dain Kim', 'Taewhoo Lee', 'Chanwoong Yoon', 'Jiwoong Sohn', 'Donghee Choi', 'Jaewoo Kang'] | ['cs.CL'] | While recent advancements in commercial large language models (LM) have shown
promising results in medical tasks, their closed-source nature poses
significant privacy and security concerns, hindering their widespread use in
the medical field. Despite efforts to create open-source models, their limited
parameters often ... | 2024-03-30T14:09:00Z | Added new LLaMA-3-based models and experiments on NEJM case
challenges | null | null | null | null | null | null | null | null | null |
2,404.00474 | Linguistic Calibration of Long-Form Generations | ['Neil Band', 'Xuechen Li', 'Tengyu Ma', 'Tatsunori Hashimoto'] | ['cs.LG', 'cs.AI', 'cs.CL', 'stat.ML'] | Language models (LMs) may lead their users to make suboptimal downstream
decisions when they confidently hallucinate. This issue can be mitigated by
having the LM verbally convey the probability that its claims are correct, but
existing models cannot produce long-form text with calibrated confidence
statements. Through... | 2024-03-30T20:47:55Z | ICML 2024. Code available at
https://github.com/tatsu-lab/linguistic_calibration | null | null | null | null | null | null | null | null | null |
2,404.00482 | Cross-lingual Named Entity Corpus for Slavic Languages | ['Jakub Piskorski', 'Michał Marcińczuk', 'Roman Yangarber'] | ['cs.CL', 'cs.AI', 'cs.LG'] | This paper presents a corpus manually annotated with named entities for six
Slavic languages - Bulgarian, Czech, Polish, Slovenian, Russian, and Ukrainian.
This work is the result of a series of shared tasks, conducted in 2017-2023 as
a part of the Workshops on Slavic Natural Language Processing. The corpus
consists of... | 2024-03-30T22:20:08Z | Published in LREC-COLING 2024 - The 2024 Joint International
Conference on Computational Linguistics, Language Resources and Evaluation | null | null | Cross-lingual Named Entity Corpus for Slavic Languages | ['Jakub Piskorski', "Michal Marci'nczuk", 'R. Yangarber'] | 2,024 | International Conference on Language Resources and Evaluation | 0 | 57 | ['Computer Science'] |
2,404.00495 | Configurable Safety Tuning of Language Models with Synthetic Preference
Data | ['Victor Gallego'] | ['cs.CL', 'cs.AI'] | State-of-the-art language model fine-tuning techniques, such as Direct
Preference Optimization (DPO), restrict user control by hard-coding predefined
behaviors into the model. To address this, we propose a novel method,
Configurable Safety Tuning (CST), that augments DPO using synthetic preference
data to facilitate fl... | 2024-03-30T23:28:05Z | null | null | null | null | null | null | null | null | null | null |
2,404.0053 | Comparing Bad Apples to Good Oranges: Aligning Large Language Models via
Joint Preference Optimization | ['Hritik Bansal', 'Ashima Suvarna', 'Gantavya Bhatt', 'Nanyun Peng', 'Kai-Wei Chang', 'Aditya Grover'] | ['cs.CL', 'cs.AI', 'cs.LG'] | A common technique for aligning large language models (LLMs) relies on
acquiring human preferences by comparing multiple generations conditioned on a
fixed context. This method, however, relies solely on pairwise comparisons,
where the generations are evaluated within an identical context. While
effective to such condi... | 2024-03-31T02:05:40Z | 22 pages, 16 figures, 7 tables | null | null | Comparing Bad Apples to Good Oranges: Aligning Large Language Models via Joint Preference Optimization | ['Hritik Bansal', 'Ashima Suvarna', 'Gantavya Bhatt', 'Nanyun Peng', 'Kai-Wei Chang', 'Aditya Grover'] | 2,024 | arXiv.org | 11 | 61 | ['Computer Science'] |
2,404.00578 | M3D: Advancing 3D Medical Image Analysis with Multi-Modal Large Language
Models | ['Fan Bai', 'Yuxin Du', 'Tiejun Huang', 'Max Q. -H. Meng', 'Bo Zhao'] | ['cs.CV'] | Medical image analysis is essential to clinical diagnosis and treatment,
which is increasingly supported by multi-modal large language models (MLLMs).
However, previous research has primarily focused on 2D medical images, leaving
3D images under-explored, despite their richer spatial information. This paper
aims to adv... | 2024-03-31T06:55:12Z | MLLM, 3D medical image analysis | null | null | null | null | null | null | null | null | null |
2,404.00604 | Extensive Self-Contrast Enables Feedback-Free Language Model Alignment | ['Xiao Liu', 'Xixuan Song', 'Yuxiao Dong', 'Jie Tang'] | ['cs.CL', 'cs.AI', 'cs.LG'] | Reinforcement learning from human feedback (RLHF) has been a central
technique for recent large language model (LLM) alignment. However, its heavy
dependence on costly human or LLM-as-Judge preference feedback could stymie its
wider applications. In this work, we introduce Self-Contrast, a feedback-free
large language ... | 2024-03-31T08:30:15Z | null | null | null | null | null | null | null | null | null | null |
2,404.0061 | RQ-RAG: Learning to Refine Queries for Retrieval Augmented Generation | ['Chi-Min Chan', 'Chunpu Xu', 'Ruibin Yuan', 'Hongyin Luo', 'Wei Xue', 'Yike Guo', 'Jie Fu'] | ['cs.CL'] | Large Language Models (LLMs) exhibit remarkable capabilities but are prone to
generating inaccurate or hallucinatory responses. This limitation stems from
their reliance on vast pretraining datasets, making them susceptible to errors
in unseen scenarios. To tackle these challenges, Retrieval-Augmented Generation
(RAG) ... | 2024-03-31T08:58:54Z | null | null | null | null | null | null | null | null | null | null |
2,404.00685 | Scaling Properties of Speech Language Models | ['Santiago Cuervo', 'Ricard Marxer'] | ['eess.AS', 'cs.AI', 'cs.CL', 'cs.NE'] | Speech Language Models (SLMs) aim to learn language from raw audio, without
textual resources. Despite significant advances, our current models exhibit
weak syntax and semantic abilities. However, if the scaling properties of
neural language models hold for the speech modality, these abilities will
improve as the amoun... | 2024-03-31T13:30:12Z | null | null | 10.18653/v1/2024.emnlp-main.21 | Scaling Properties of Speech Language Models | ['Santiago Cuervo', 'R. Marxer'] | 2,024 | Conference on Empirical Methods in Natural Language Processing | 11 | 28 | ['Computer Science', 'Engineering'] |
2,404.00722 | DRCT: Saving Image Super-resolution away from Information Bottleneck | ['Chih-Chung Hsu', 'Chia-Ming Lee', 'Yi-Shiuan Chou'] | ['cs.CV', 'cs.AI'] | In recent years, Vision Transformer-based approaches for low-level vision
tasks have achieved widespread success. Unlike CNN-based models, Transformers
are more adept at capturing long-range dependencies, enabling the
reconstruction of images utilizing non-local information. In the domain of
super-resolution, Swin-tran... | 2024-03-31T15:34:45Z | Accepted by CVPRW2024, NTIRE Image Super-resolution (x4) | null | null | DRCT: Saving Image Super-Resolution away from Information Bottleneck | ['Chih-Chung Hsu', 'Chia-Ming Lee', 'Yi-Shiuan Chou'] | 2,024 | 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) | 38 | 64 | ['Computer Science'] |
2,404.00862 | Bailong: Bilingual Transfer Learning based on QLoRA and Zip-tie
Embedding | ['Lung-Chuan Chen', 'Zong-Ru Li'] | ['cs.CL', 'cs.AI'] | Large language models (LLMs) have demonstrated exceptional performance in
various NLP applications. However, the majority of existing open-source LLMs
are pre-trained primarily on English data and little part of other languages.
This deficiency in multilingual training data results in suboptimal performance
when applie... | 2024-04-01T02:04:44Z | null | null | null | null | null | null | null | null | null | null |
2,404.00878 | TryOn-Adapter: Efficient Fine-Grained Clothing Identity Adaptation for
High-Fidelity Virtual Try-On | ['Jiazheng Xing', 'Chao Xu', 'Yijie Qian', 'Yang Liu', 'Guang Dai', 'Baigui Sun', 'Yong Liu', 'Jingdong Wang'] | ['cs.CV'] | Virtual try-on focuses on adjusting the given clothes to fit a specific
person seamlessly while avoiding any distortion of the patterns and textures of
the garment. However, the clothing identity uncontrollability and training
inefficiency of existing diffusion-based methods, which struggle to maintain
the identity eve... | 2024-04-01T03:15:41Z | null | null | null | TryOn-Adapter: Efficient Fine-Grained Clothing Identity Adaptation for High-Fidelity Virtual Try-On | ['Jiazheng Xing', 'Chao Xu', 'Yijie Qian', 'Yang Liu', 'Guang Dai', 'Baigui Sun', 'Yong Liu', 'Jingdong Wang'] | 2,024 | International Journal of Computer Vision | 1 | 58 | ['Computer Science'] |
2,404.00989 | 360+x: A Panoptic Multi-modal Scene Understanding Dataset | ['Hao Chen', 'Yuqi Hou', 'Chenyuan Qu', 'Irene Testini', 'Xiaohan Hong', 'Jianbo Jiao'] | ['cs.CV', 'cs.AI', 'cs.MM', 'cs.SD', 'eess.AS'] | Human perception of the world is shaped by a multitude of viewpoints and
modalities. While many existing datasets focus on scene understanding from a
certain perspective (e.g. egocentric or third-person views), our dataset offers
a panoptic perspective (i.e. multiple viewpoints with multiple data
modalities). Specifica... | 2024-04-01T08:34:42Z | CVPR 2024 (Oral Presentation), Project page:
https://x360dataset.github.io/ | The IEEE/CVF Computer Vision and Pattern Recognition Conference
(CVPR) 2024 | null | null | null | null | null | null | null | null |
2,404.00995 | PosterLlama: Bridging Design Ability of Langauge Model to Contents-Aware
Layout Generation | ['Jaejung Seol', 'Seojun Kim', 'Jaejun Yoo'] | ['cs.CV'] | Visual layout plays a critical role in graphic design fields such as
advertising, posters, and web UI design. The recent trend towards content-aware
layout generation through generative models has shown promise, yet it often
overlooks the semantic intricacies of layout design by treating it as a simple
numerical optimi... | 2024-04-01T08:46:35Z | ECCV 2024 | null | null | null | null | null | null | null | null | null |
2,404.01089 | Texture-Preserving Diffusion Models for High-Fidelity Virtual Try-On | ['Xu Yang', 'Changxing Ding', 'Zhibin Hong', 'Junhao Huang', 'Jin Tao', 'Xiangmin Xu'] | ['cs.CV', 'cs.AI'] | Image-based virtual try-on is an increasingly important task for online
shopping. It aims to synthesize images of a specific person wearing a specified
garment. Diffusion model-based approaches have recently become popular, as they
are excellent at image synthesis tasks. However, these approaches usually
employ additio... | 2024-04-01T12:43:22Z | CVPR 2024 | null | null | null | null | null | null | null | null | null |
2,404.01094 | HairFastGAN: Realistic and Robust Hair Transfer with a Fast
Encoder-Based Approach | ['Maxim Nikolaev', 'Mikhail Kuznetsov', 'Dmitry Vetrov', 'Aibek Alanov'] | ['cs.CV'] | Our paper addresses the complex task of transferring a hairstyle from a
reference image to an input photo for virtual hair try-on. This task is
challenging due to the need to adapt to various photo poses, the sensitivity of
hairstyles, and the lack of objective metrics. The current state of the art
hairstyle transfer m... | 2024-04-01T12:59:49Z | null | null | null | HairFastGAN: Realistic and Robust Hair Transfer with a Fast Encoder-Based Approach | ['Maxim Nikolaev', 'Mikhail Kuznetsov', 'Dmitry P. Vetrov', 'Aibek Alanov'] | 2,024 | Neural Information Processing Systems | 6 | 44 | ['Computer Science'] |
2,404.01133 | CityGaussian: Real-time High-quality Large-Scale Scene Rendering with
Gaussians | ['Yang Liu', 'He Guan', 'Chuanchen Luo', 'Lue Fan', 'Naiyan Wang', 'Junran Peng', 'Zhaoxiang Zhang'] | ['cs.CV'] | The advancement of real-time 3D scene reconstruction and novel view synthesis
has been significantly propelled by 3D Gaussian Splatting (3DGS). However,
effectively training large-scale 3DGS and rendering it in real-time across
various scales remains challenging. This paper introduces CityGaussian
(CityGS), which emplo... | 2024-04-01T14:24:40Z | Accepted by ECCV2024; Project Page:
https://dekuliutesla.github.io/citygs/ | null | null | CityGaussian: Real-time High-quality Large-Scale Scene Rendering with Gaussians | ['Yang Liu', 'He Guan', 'Chuanchen Luo', 'Lue Fan', 'Junran Peng', 'Zhaoxiang Zhang'] | 2,024 | European Conference on Computer Vision | 90 | 50 | ['Computer Science'] |
2,404.01197 | Getting it Right: Improving Spatial Consistency in Text-to-Image Models | ['Agneet Chatterjee', 'Gabriela Ben Melech Stan', 'Estelle Aflalo', 'Sayak Paul', 'Dhruba Ghosh', 'Tejas Gokhale', 'Ludwig Schmidt', 'Hannaneh Hajishirzi', 'Vasudev Lal', 'Chitta Baral', 'Yezhou Yang'] | ['cs.CV'] | One of the key shortcomings in current text-to-image (T2I) models is their
inability to consistently generate images which faithfully follow the spatial
relationships specified in the text prompt. In this paper, we offer a
comprehensive investigation of this limitation, while also developing datasets
and methods that s... | 2024-04-01T15:55:25Z | Accepted to ECCV 2024. Project Page : https://spright-t2i.github.io/ | null | null | null | null | null | null | null | null | null |
2,404.01258 | Direct Preference Optimization of Video Large Multimodal Models from
Language Model Reward | ['Ruohong Zhang', 'Liangke Gui', 'Zhiqing Sun', 'Yihao Feng', 'Keyang Xu', 'Yuanhan Zhang', 'Di Fu', 'Chunyuan Li', 'Alexander Hauptmann', 'Yonatan Bisk', 'Yiming Yang'] | ['cs.CV', 'cs.AI'] | Preference modeling techniques, such as direct preference optimization (DPO),
has shown effective in enhancing the generalization abilities of large language
model (LLM). However, in tasks involving video instruction-following, providing
informative feedback, especially for detecting hallucinations in generated
respons... | 2024-04-01T17:28:16Z | null | null | null | null | null | null | null | null | null | null |
2,404.01291 | Evaluating Text-to-Visual Generation with Image-to-Text Generation | ['Zhiqiu Lin', 'Deepak Pathak', 'Baiqi Li', 'Jiayao Li', 'Xide Xia', 'Graham Neubig', 'Pengchuan Zhang', 'Deva Ramanan'] | ['cs.CV', 'cs.AI', 'cs.CL', 'cs.LG', 'cs.MM'] | Despite significant progress in generative AI, comprehensive evaluation
remains challenging because of the lack of effective metrics and standardized
benchmarks. For instance, the widely-used CLIPScore measures the alignment
between a (generated) image and text prompt, but it fails to produce reliable
scores for comple... | 2024-04-01T17:58:06Z | We open-source our data, model, and code at:
https://github.com/linzhiqiu/t2v_metrics ; Project page:
https://linzhiqiu.github.io/papers/vqascore | null | null | Evaluating Text-to-Visual Generation with Image-to-Text Generation | ['Zhiqiu Lin', 'Deepak Pathak', 'Baiqi Li', 'Jiayao Li', 'Xide Xia', 'Graham Neubig', 'Pengchuan Zhang', 'Deva Ramanan'] | 2,024 | European Conference on Computer Vision | 171 | 89 | ['Computer Science'] |
2,404.01292 | Measuring Style Similarity in Diffusion Models | ['Gowthami Somepalli', 'Anubhav Gupta', 'Kamal Gupta', 'Shramay Palta', 'Micah Goldblum', 'Jonas Geiping', 'Abhinav Shrivastava', 'Tom Goldstein'] | ['cs.CV', 'cs.LG'] | Generative models are now widely used by graphic designers and artists. Prior
works have shown that these models remember and often replicate content from
their training data during generation. Hence as their proliferation increases,
it has become important to perform a database search to determine whether the
properti... | 2024-04-01T17:58:30Z | null | null | null | Measuring Style Similarity in Diffusion Models | ['Gowthami Somepalli', 'Anubhav Gupta', 'Kamal K. Gupta', 'Shramay Palta', 'Micah Goldblum', 'Jonas Geiping', 'Abhinav Shrivastava', 'Tom Goldstein'] | 2,024 | arXiv.org | 42 | 67 | ['Computer Science'] |
2,404.01294 | CosmicMan: A Text-to-Image Foundation Model for Humans | ['Shikai Li', 'Jianglin Fu', 'Kaiyuan Liu', 'Wentao Wang', 'Kwan-Yee Lin', 'Wayne Wu'] | ['cs.CV'] | We present CosmicMan, a text-to-image foundation model specialized for
generating high-fidelity human images. Unlike current general-purpose
foundation models that are stuck in the dilemma of inferior quality and
text-image misalignment for humans, CosmicMan enables generating
photo-realistic human images with meticulo... | 2024-04-01T17:59:05Z | Accepted by CVPR 2024. The supplementary material is included.
Project Page: https://cosmicman-cvpr2024.github.io | null | null | null | null | null | null | null | null | null |
2,404.013 | NeRF-MAE: Masked AutoEncoders for Self-Supervised 3D Representation
Learning for Neural Radiance Fields | ['Muhammad Zubair Irshad', 'Sergey Zakharov', 'Vitor Guizilini', 'Adrien Gaidon', 'Zsolt Kira', 'Rares Ambrus'] | ['cs.CV', 'cs.AI', 'cs.LG'] | Neural fields excel in computer vision and robotics due to their ability to
understand the 3D visual world such as inferring semantics, geometry, and
dynamics. Given the capabilities of neural fields in densely representing a 3D
scene from 2D images, we ask the question: Can we scale their self-supervised
pretraining, ... | 2024-04-01T17:59:55Z | Accepted to ECCV 2024. Project Page: https://nerf-mae.github.io/ | null | null | null | null | null | null | null | null | null |
2,404.01331 | LLaVA-Gemma: Accelerating Multimodal Foundation Models with a Compact
Language Model | ['Musashi Hinck', 'Matthew L. Olson', 'David Cobbley', 'Shao-Yen Tseng', 'Vasudev Lal'] | ['cs.CL', 'cs.AI'] | We train a suite of multimodal foundation models (MMFM) using the popular
LLaVA framework with the recently released Gemma family of large language
models (LLMs). Of particular interest is the 2B parameter Gemma model, which
provides opportunities to construct capable small-scale MMFMs. In line with
findings from other... | 2024-03-29T21:32:50Z | CVPR 2024, MMFM workshop. Authors 1 and 2 contributed equally. Models
available at https://huggingface.co/intel/llava-gemma-2b/ and
https://huggingface.co/intel/llava-gemma-7b/ Training code at
https://github.com/IntelLabs/multimodal_cognitive_ai/tree/main/LLaVA-Gemma | null | null | null | null | null | null | null | null | null |
2,404.01549 | Octopus: On-device language model for function calling of software APIs | ['Wei Chen', 'Zhiyuan Li', 'Mingyuan Ma'] | ['cs.CL', 'cs.SE'] | In the rapidly evolving domain of artificial intelligence, Large Language
Models (LLMs) play a crucial role due to their advanced text processing and
generation abilities. This study introduces a new strategy aimed at harnessing
on-device LLMs in invoking software APIs. We meticulously compile a dataset
derived from so... | 2024-04-02T01:29:28Z | null | null | null | Octopus: On-device language model for function calling of software APIs | ['Wei Chen', 'Zhiyuan Li', 'Mingyuan Ma'] | 2,024 | North American Chapter of the Association for Computational Linguistics | 16 | 69 | ['Computer Science'] |
2,404.01647 | EDTalk: Efficient Disentanglement for Emotional Talking Head Synthesis | ['Shuai Tan', 'Bin Ji', 'Mengxiao Bi', 'Ye Pan'] | ['cs.CV'] | Achieving disentangled control over multiple facial motions and accommodating
diverse input modalities greatly enhances the application and entertainment of
the talking head generation. This necessitates a deep exploration of the
decoupling space for facial features, ensuring that they a) operate
independently without ... | 2024-04-02T05:32:39Z | 22 pages, 15 figures | null | null | null | null | null | null | null | null | null |
2,404.01657 | Release of Pre-Trained Models for the Japanese Language | ['Kei Sawada', 'Tianyu Zhao', 'Makoto Shing', 'Kentaro Mitsui', 'Akio Kaga', 'Yukiya Hono', 'Toshiaki Wakatsuki', 'Koh Mitsuda'] | ['cs.CL', 'cs.AI', 'cs.CV', 'cs.LG', 'eess.AS'] | AI democratization aims to create a world in which the average person can
utilize AI techniques. To achieve this goal, numerous research institutes have
attempted to make their results accessible to the public. In particular, large
pre-trained models trained on large-scale data have shown unprecedented
potential, and t... | 2024-04-02T05:59:43Z | 9 pages, 1 figure, 5 tables, accepted for LREC-COLING 2024. Models
are publicly available at https://huggingface.co/rinna | null | null | null | null | null | null | null | null | null |
2,404.01744 | Octopus v2: On-device language model for super agent | ['Wei Chen', 'Zhiyuan Li'] | ['cs.CL'] | Language models have shown effectiveness in a variety of software
applications, particularly in tasks related to automatic workflow. These models
possess the crucial ability to call functions, which is essential in creating
AI agents. Despite the high performance of large-scale language models in cloud
environments, th... | 2024-04-02T09:01:32Z | null | null | null | null | null | null | null | null | null | null |
2,404.01856 | Poro 34B and the Blessing of Multilinguality | ['Risto Luukkonen', 'Jonathan Burdge', 'Elaine Zosa', 'Aarne Talman', 'Ville Komulainen', 'Väinö Hatanpää', 'Peter Sarlin', 'Sampo Pyysalo'] | ['cs.CL'] | The pretraining of state-of-the-art large language models now requires
trillions of words of text, which is orders of magnitude more than available
for the vast majority of languages. While including text in more than one
language is an obvious way to acquire more pretraining data, multilinguality is
often seen as a cu... | 2024-04-02T11:34:12Z | null | null | null | null | null | null | null | null | null | null |
2,404.01911 | VLRM: Vision-Language Models act as Reward Models for Image Captioning | ['Maksim Dzabraev', 'Alexander Kunitsyn', 'Andrei Ivaniuta'] | ['cs.CV'] | In this work, we present an unsupervised method for enhancing an image
captioning model (in our case, BLIP2) using reinforcement learning and
vision-language models like CLIP and BLIP2-ITM as reward models. The RL-tuned
model is able to generate longer and more comprehensive descriptions. Our model
reaches impressive 0... | 2024-04-02T12:57:22Z | null | null | null | null | null | null | null | null | null | null |
2,404.0206 | Long-context LLMs Struggle with Long In-context Learning | ['Tianle Li', 'Ge Zhang', 'Quy Duc Do', 'Xiang Yue', 'Wenhu Chen'] | ['cs.CL', 'cs.AI'] | Large Language Models (LLMs) have made significant strides in handling long
sequences. Some models like Gemini could even to be capable of dealing with
millions of tokens. However, their performance evaluation has largely been
confined to metrics like perplexity and synthetic tasks, which may not fully
capture their tr... | 2024-04-02T15:59:11Z | null | null | null | null | null | null | null | null | null | null |
2,404.02078 | Advancing LLM Reasoning Generalists with Preference Trees | ['Lifan Yuan', 'Ganqu Cui', 'Hanbin Wang', 'Ning Ding', 'Xingyao Wang', 'Jia Deng', 'Boji Shan', 'Huimin Chen', 'Ruobing Xie', 'Yankai Lin', 'Zhenghao Liu', 'Bowen Zhou', 'Hao Peng', 'Zhiyuan Liu', 'Maosong Sun'] | ['cs.AI', 'cs.CL', 'cs.LG'] | We introduce Eurus, a suite of large language models (LLMs) optimized for
reasoning. Finetuned from Mistral-7B and CodeLlama-70B, Eurus models achieve
state-of-the-art results among open-source models on a diverse set of
benchmarks covering mathematics, code generation, and logical reasoning
problems. Notably, Eurus-70... | 2024-04-02T16:25:30Z | Models and data are available at https://github.com/OpenBMB/Eurus | null | null | null | null | null | null | null | null | null |
2,404.02132 | ViTamin: Designing Scalable Vision Models in the Vision-Language Era | ['Jieneng Chen', 'Qihang Yu', 'Xiaohui Shen', 'Alan Yuille', 'Liang-Chieh Chen'] | ['cs.CV'] | Recent breakthroughs in vision-language models (VLMs) start a new page in the
vision community. The VLMs provide stronger and more generalizable feature
embeddings compared to those from ImageNet-pretrained models, thanks to the
training on the large-scale Internet image-text pairs. However, despite the
amazing achieve... | 2024-04-02T17:40:29Z | CVPR 2024; https://github.com/Beckschen/ViTamin | null | null | ViTamin: Designing Scalable Vision Models in the Vision-Language Era | ['Jieneng Chen', 'Qihang Yu', 'Xiaohui Shen', 'Alan L. Yuille', 'Liang-Chieh Chen'] | 2,024 | Computer Vision and Pattern Recognition | 29 | 172 | ['Computer Science'] |
2,404.02258 | Mixture-of-Depths: Dynamically allocating compute in transformer-based
language models | ['David Raposo', 'Sam Ritter', 'Blake Richards', 'Timothy Lillicrap', 'Peter Conway Humphreys', 'Adam Santoro'] | ['cs.LG', 'cs.CL'] | Transformer-based language models spread FLOPs uniformly across input
sequences. In this work we demonstrate that transformers can instead learn to
dynamically allocate FLOPs (or compute) to specific positions in a sequence,
optimising the allocation along the sequence for different layers across the
model depth. Our m... | 2024-04-02T19:28:11Z | null | null | null | Mixture-of-Depths: Dynamically allocating compute in transformer-based language models | ['David Raposo', 'Sam Ritter', 'Blake Richards', 'T. Lillicrap', 'Peter Humphreys', 'Adam Santoro'] | 2,024 | arXiv.org | 89 | 19 | ['Computer Science'] |
2,404.02406 | Exploring Backdoor Vulnerabilities of Chat Models | ['Yunzhuo Hao', 'Wenkai Yang', 'Yankai Lin'] | ['cs.CR', 'cs.AI', 'cs.CL'] | Recent researches have shown that Large Language Models (LLMs) are
susceptible to a security threat known as Backdoor Attack. The backdoored model
will behave well in normal cases but exhibit malicious behaviours on inputs
inserted with a specific backdoor trigger. Current backdoor studies on LLMs
predominantly focus o... | 2024-04-03T02:16:53Z | Code and data are available at
https://github.com/hychaochao/Chat-Models-Backdoor-Attacking | null | null | null | null | null | null | null | null | null |
2,404.02543 | Unbiased Learning to Rank Meets Reality: Lessons from Baidu's
Large-Scale Search Dataset | ['Philipp Hager', 'Romain Deffayet', 'Jean-Michel Renders', 'Onno Zoeter', 'Maarten de Rijke'] | ['cs.IR', 'cs.AI'] | Unbiased learning-to-rank (ULTR) is a well-established framework for learning
from user clicks, which are often biased by the ranker collecting the data.
While theoretically justified and extensively tested in simulation, ULTR
techniques lack empirical validation, especially on modern search engines. The
Baidu-ULTR dat... | 2024-04-03T08:00:46Z | null | null | 10.1145/3626772.3657892 | null | null | null | null | null | null | null |
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