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2,404.12141
MolCRAFT: Structure-Based Drug Design in Continuous Parameter Space
['Yanru Qu', 'Keyue Qiu', 'Yuxuan Song', 'Jingjing Gong', 'Jiawei Han', 'Mingyue Zheng', 'Hao Zhou', 'Wei-Ying Ma']
['q-bio.BM', 'cs.LG']
Generative models for structure-based drug design (SBDD) have shown promising results in recent years. Existing works mainly focus on how to generate molecules with higher binding affinity, ignoring the feasibility prerequisites for generated 3D poses and resulting in false positives. We conduct thorough studies on key...
2024-04-18T12:43:39Z
Accepted to ICML 2024
null
null
MolCRAFT: Structure-Based Drug Design in Continuous Parameter Space
['Yanru Qu', 'Keyue Qiu', 'Yuxuan Song', 'Jingjing Gong', 'Jiawei Han', 'Mingyue Zheng', 'Hao Zhou', 'Wei-Ying Ma']
2,024
International Conference on Machine Learning
20
37
['Biology', 'Computer Science']
2,404.12195
OpenBezoar: Small, Cost-Effective and Open Models Trained on Mixes of Instruction Data
['Chandeepa Dissanayake', 'Lahiru Lowe', 'Sachith Gunasekara', 'Yasiru Ratnayake']
['cs.CL', 'cs.LG']
Instruction fine-tuning pretrained LLMs for diverse downstream tasks has demonstrated remarkable success and has captured the interest of both academics and practitioners. To ensure such fine-tuned LLMs align with human preferences, techniques such as RLHF and DPO have emerged. At the same time, there is increasing int...
2024-04-18T13:57:18Z
25 pages, 27 Figures, 8 Tables
null
null
OpenBezoar: Small, Cost-Effective and Open Models Trained on Mixes of Instruction Data
['Chandeepa Dissanayake', 'Lahiru Lowe', 'Sachith Gunasekara', 'Yasiru Ratnayake']
2,024
arXiv.org
2
38
['Computer Science']
2,404.12224
Length Generalization of Causal Transformers without Position Encoding
['Jie Wang', 'Tao Ji', 'Yuanbin Wu', 'Hang Yan', 'Tao Gui', 'Qi Zhang', 'Xuanjing Huang', 'Xiaoling Wang']
['cs.CL']
Generalizing to longer sentences is important for recent Transformer-based language models. Besides algorithms manipulating explicit position features, the success of Transformers without position encodings (NoPE) provides a new way to overcome the challenge. In this paper, we study the length generalization property o...
2024-04-18T14:38:32Z
null
null
null
Length Generalization of Causal Transformers without Position Encoding
['Jie Wang', 'Tao Ji', 'Yuanbin Wu', 'Hang Yan', 'Tao Gui', 'Qi Zhang', 'Xuanjing Huang', 'Xiaoling Wang']
2,024
Annual Meeting of the Association for Computational Linguistics
23
38
['Computer Science']
2,404.12241
Introducing v0.5 of the AI Safety Benchmark from MLCommons
['Bertie Vidgen', 'Adarsh Agrawal', 'Ahmed M. Ahmed', 'Victor Akinwande', 'Namir Al-Nuaimi', 'Najla Alfaraj', 'Elie Alhajjar', 'Lora Aroyo', 'Trupti Bavalatti', 'Max Bartolo', 'Borhane Blili-Hamelin', 'Kurt Bollacker', 'Rishi Bomassani', 'Marisa Ferrara Boston', 'Siméon Campos', 'Kal Chakra', 'Canyu Chen', 'Cody Colema...
['cs.CL', 'cs.AI']
This paper introduces v0.5 of the AI Safety Benchmark, which has been created by the MLCommons AI Safety Working Group. The AI Safety Benchmark has been designed to assess the safety risks of AI systems that use chat-tuned language models. We introduce a principled approach to specifying and constructing the benchmark,...
2024-04-18T15:01:00Z
null
null
null
null
null
null
null
null
null
null
2,404.12342
Large Language Models in Targeted Sentiment Analysis
['Nicolay Rusnachenko', 'Anton Golubev', 'Natalia Loukachevitch']
['cs.CL']
In this paper we investigate the use of decoder-based generative transformers for extracting sentiment towards the named entities in Russian news articles. We study sentiment analysis capabilities of instruction-tuned large language models (LLMs). We consider the dataset of RuSentNE-2023 in our study. The first group o...
2024-04-18T17:16:16Z
Fine-tuned Flan-T5-xl outperforms the top #1 results of transformer-based classifier in RuSentNE-2023 competition, to appear in Lobachevskii Journal of Mathematics No.8/2024 proceedings
null
null
null
null
null
null
null
null
null
2,404.1239
BLINK: Multimodal Large Language Models Can See but Not Perceive
['Xingyu Fu', 'Yushi Hu', 'Bangzheng Li', 'Yu Feng', 'Haoyu Wang', 'Xudong Lin', 'Dan Roth', 'Noah A. Smith', 'Wei-Chiu Ma', 'Ranjay Krishna']
['cs.CV', 'cs.AI', 'cs.CL']
We introduce Blink, a new benchmark for multimodal language models (LLMs) that focuses on core visual perception abilities not found in other evaluations. Most of the Blink tasks can be solved by humans "within a blink" (e.g., relative depth estimation, visual correspondence, forensics detection, and multi-view reasoni...
2024-04-18T17:59:54Z
Multimodal Benchmark, Project Url: https://zeyofu.github.io/blink/, ECCV 2024
null
null
null
null
null
null
null
null
null
2,404.125
UIClip: A Data-driven Model for Assessing User Interface Design
['Jason Wu', 'Yi-Hao Peng', 'Amanda Li', 'Amanda Swearngin', 'Jeffrey P. Bigham', 'Jeffrey Nichols']
['cs.HC', 'cs.CL', 'cs.CV']
User interface (UI) design is a difficult yet important task for ensuring the usability, accessibility, and aesthetic qualities of applications. In our paper, we develop a machine-learned model, UIClip, for assessing the design quality and visual relevance of a UI given its screenshot and natural language description. ...
2024-04-18T20:43:08Z
null
null
null
null
null
null
null
null
null
null
2,404.12501
SPIdepth: Strengthened Pose Information for Self-supervised Monocular Depth Estimation
['Mykola Lavreniuk']
['cs.CV', 'eess.IV']
Self-supervised monocular depth estimation has garnered considerable attention for its applications in autonomous driving and robotics. While recent methods have made strides in leveraging techniques like the Self Query Layer (SQL) to infer depth from motion, they often overlook the potential of strengthening pose info...
2024-04-18T20:43:33Z
null
null
null
null
null
null
null
null
null
null
2,404.12636
MORepair: Teaching LLMs to Repair Code via Multi-Objective Fine-tuning
['Boyang Yang', 'Haoye Tian', 'Jiadong Ren', 'Hongyu Zhang', 'Jacques Klein', 'Tegawendé F. Bissyandé', 'Claire Le Goues', 'Shunfu Jin']
['cs.SE']
Within the realm of software engineering, specialized tasks on code, such as program repair, present unique challenges, necessitating fine-tuning Large language models~(LLMs) to unlock state-of-the-art performance. Fine-tuning approaches proposed in the literature for LLMs on program repair tasks generally overlook the...
2024-04-19T05:36:21Z
null
null
null
null
null
null
null
null
null
null
2,404.13028
When Life gives you LLMs, make LLM-ADE: Large Language Models with Adaptive Data Engineering
['Stephen Choi', 'William Gazeley']
['cs.CE', 'cs.AI']
This paper presents the LLM-ADE framework, a novel methodology for continued pre-training of large language models (LLMs) that addresses the challenges of catastrophic forgetting and double descent. LLM-ADE employs dynamic architectural adjustments, including selective block freezing and expansion, tailored to specific...
2024-04-19T17:43:26Z
6 pages, 3 tables and 3 figures
null
null
null
null
null
null
null
null
null
2,404.13046
MoVA: Adapting Mixture of Vision Experts to Multimodal Context
['Zhuofan Zong', 'Bingqi Ma', 'Dazhong Shen', 'Guanglu Song', 'Hao Shao', 'Dongzhi Jiang', 'Hongsheng Li', 'Yu Liu']
['cs.CV']
As the key component in multimodal large language models (MLLMs), the ability of the visual encoder greatly affects MLLM's understanding on diverse image content. Although some large-scale pretrained vision encoders such as vision encoders in CLIP and DINOv2 have brought promising performance, we found that there is st...
2024-04-19T17:59:48Z
NeurIPS 2024
null
null
null
null
null
null
null
null
null
2,404.13364
MahaSQuAD: Bridging Linguistic Divides in Marathi Question-Answering
['Ruturaj Ghatage', 'Aditya Kulkarni', 'Rajlaxmi Patil', 'Sharvi Endait', 'Raviraj Joshi']
['cs.CL', 'cs.LG']
Question-answering systems have revolutionized information retrieval, but linguistic and cultural boundaries limit their widespread accessibility. This research endeavors to bridge the gap of the absence of efficient QnA datasets in low-resource languages by translating the English Question Answering Dataset (SQuAD) us...
2024-04-20T12:16:35Z
Accepted at the International Conference on Natural Language Processing (ICON 2023)
null
null
null
null
null
null
null
null
null
2,404.13397
Retrieval-Augmented Generation-based Relation Extraction
['Sefika Efeoglu', 'Adrian Paschke']
['cs.CL', 'cs.AI']
Information Extraction (IE) is a transformative process that converts unstructured text data into a structured format by employing entity and relation extraction (RE) methodologies. The identification of the relation between a pair of entities plays a crucial role within this framework. Despite the existence of various...
2024-04-20T14:42:43Z
Submitted to Semantic Web Journal. Under Review
null
null
Retrieval-Augmented Generation-based Relation Extraction
['Sefika Efeoglu', 'Adrian Paschke']
2,024
arXiv.org
9
32
['Computer Science']
2,404.13686
Hyper-SD: Trajectory Segmented Consistency Model for Efficient Image Synthesis
['Yuxi Ren', 'Xin Xia', 'Yanzuo Lu', 'Jiacheng Zhang', 'Jie Wu', 'Pan Xie', 'Xing Wang', 'Xuefeng Xiao']
['cs.CV']
Recently, a series of diffusion-aware distillation algorithms have emerged to alleviate the computational overhead associated with the multi-step inference process of Diffusion Models (DMs). Current distillation techniques often dichotomize into two distinct aspects: i) ODE Trajectory Preservation; and ii) ODE Trajecto...
2024-04-21T15:16:05Z
Accepted by NeurIPS 2024 (Camera-Ready Version). Project Page: https://hyper-sd.github.io/
null
null
null
null
null
null
null
null
null
2,404.13903
Accelerating Image Generation with Sub-path Linear Approximation Model
['Chen Xu', 'Tianhui Song', 'Weixin Feng', 'Xubin Li', 'Tiezheng Ge', 'Bo Zheng', 'Limin Wang']
['cs.CV']
Diffusion models have significantly advanced the state of the art in image, audio, and video generation tasks. However, their applications in practical scenarios are hindered by slow inference speed. Drawing inspiration from the approximation strategies utilized in consistency models, we propose the Sub-path Linear App...
2024-04-22T06:25:17Z
null
null
null
null
null
null
null
null
null
null
2,404.14047
An empirical study of LLaMA3 quantization: from LLMs to MLLMs
['Wei Huang', 'Xingyu Zheng', 'Xudong Ma', 'Haotong Qin', 'Chengtao Lv', 'Hong Chen', 'Jie Luo', 'Xiaojuan Qi', 'Xianglong Liu', 'Michele Magno']
['cs.LG']
The LLaMA family, a collection of foundation language models ranging from 7B to 65B parameters, has become one of the most powerful open-source large language models (LLMs) and the popular LLM backbone of multi-modal large language models (MLLMs), widely used in computer vision and natural language understanding tasks....
2024-04-22T10:03:03Z
null
null
10.1007/s44267-024-00070-x
An empirical study of LLaMA3 quantization: from LLMs to MLLMs
['Wei Huang', 'Xudong Ma', 'Haotong Qin', 'Xingyu Zheng', 'Chengtao Lv', 'Hong Chen', 'Jie Luo', 'Xiaojuan Qi', 'Xianglong Liu', 'Michele Magno']
2,024
Vis. Intell.
42
41
['Computer Science', 'Medicine']
2,404.14215
Text-Tuple-Table: Towards Information Integration in Text-to-Table Generation via Global Tuple Extraction
['Zheye Deng', 'Chunkit Chan', 'Weiqi Wang', 'Yuxi Sun', 'Wei Fan', 'Tianshi Zheng', 'Yauwai Yim', 'Yangqiu Song']
['cs.CL']
The task of condensing large chunks of textual information into concise and structured tables has gained attention recently due to the emergence of Large Language Models (LLMs) and their potential benefit for downstream tasks, such as text summarization and text mining. Previous approaches often generate tables that di...
2024-04-22T14:31:28Z
Accepted to EMNLP 2024
null
null
Text-Tuple-Table: Towards Information Integration in Text-to-Table Generation via Global Tuple Extraction
['Zheye Deng', 'Chunkit Chan', 'Weiqi Wang', 'Yuxi Sun', 'Wei Fan', 'Tianshi ZHENG', 'Yauwai Yim', 'Yangqiu Song']
2,024
Conference on Empirical Methods in Natural Language Processing
15
50
['Computer Science']
2,404.14219
Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone
['Marah Abdin', 'Jyoti Aneja', 'Hany Awadalla', 'Ahmed Awadallah', 'Ammar Ahmad Awan', 'Nguyen Bach', 'Amit Bahree', 'Arash Bakhtiari', 'Jianmin Bao', 'Harkirat Behl', 'Alon Benhaim', 'Misha Bilenko', 'Johan Bjorck', 'Sébastien Bubeck', 'Martin Cai', 'Qin Cai', 'Vishrav Chaudhary', 'Dong Chen', 'Dongdong Chen', 'Weizhu...
['cs.CL', 'cs.AI']
We introduce phi-3-mini, a 3.8 billion parameter language model trained on 3.3 trillion tokens, whose overall performance, as measured by both academic benchmarks and internal testing, rivals that of models such as Mixtral 8x7B and GPT-3.5 (e.g., phi-3-mini achieves 69% on MMLU and 8.38 on MT-bench), despite being smal...
2024-04-22T14:32:33Z
24 pages
null
null
null
null
null
null
null
null
null
2,404.14396
SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation
['Yuying Ge', 'Sijie Zhao', 'Jinguo Zhu', 'Yixiao Ge', 'Kun Yi', 'Lin Song', 'Chen Li', 'Xiaohan Ding', 'Ying Shan']
['cs.CV']
The rapid evolution of multimodal foundation model has demonstrated significant progresses in vision-language understanding and generation, e.g., our previous work SEED-LLaMA. However, there remains a gap between its capability and the real-world applicability, primarily due to the model's limited capacity to effective...
2024-04-22T17:56:09Z
We added benchmark results (without updating models) and ablation study in this version. Project released at: https://github.com/AILab-CVC/SEED-X
null
null
null
null
null
null
null
null
null
2,404.14397
RTP-LX: Can LLMs Evaluate Toxicity in Multilingual Scenarios?
['Adrian de Wynter', 'Ishaan Watts', 'Tua Wongsangaroonsri', 'Minghui Zhang', 'Noura Farra', 'Nektar Ege Altıntoprak', 'Lena Baur', 'Samantha Claudet', 'Pavel Gajdusek', 'Can Gören', 'Qilong Gu', 'Anna Kaminska', 'Tomasz Kaminski', 'Ruby Kuo', 'Akiko Kyuba', 'Jongho Lee', 'Kartik Mathur', 'Petter Merok', 'Ivana Milovan...
['cs.CL', 'cs.CY', 'cs.LG']
Large language models (LLMs) and small language models (SLMs) are being adopted at remarkable speed, although their safety still remains a serious concern. With the advent of multilingual S/LLMs, the question now becomes a matter of scale: can we expand multilingual safety evaluations of these models with the same velo...
2024-04-22T17:56:26Z
AAAI 2025--camera ready + extended abstract
null
10.1609/aaai.v39i27.35011
RTP-LX: Can LLMs Evaluate Toxicity in Multilingual Scenarios?
['Adrian de Wynter', 'Ishaan Watts', 'Nektar Ege Altintoprak', 'Tua Wongsangaroonsri', 'Minghui Zhang', 'Noura Farra', 'Lena Baur', 'Samantha Claudet', 'Pavel Gajdusek', 'Can Gören', 'Qilong Gu', 'Anna Kaminska', 'Tomasz Kaminski', 'Ruby Kuo', 'Akiko Kyuba', 'Jongho Lee', 'Kartik Mathur', 'Petter Merok', 'Ivana Milovan...
2,024
AAAI Conference on Artificial Intelligence
21
31
['Computer Science']
2,404.14406
Hyp-OC: Hyperbolic One Class Classification for Face Anti-Spoofing
['Kartik Narayan', 'Vishal M. Patel']
['cs.CV']
Face recognition technology has become an integral part of modern security systems and user authentication processes. However, these systems are vulnerable to spoofing attacks and can easily be circumvented. Most prior research in face anti-spoofing (FAS) approaches it as a two-class classification task where models ar...
2024-04-22T17:59:18Z
Accepted in FG2024, Project Page - https://kartik-3004.github.io/hyp-oc/
null
null
null
null
null
null
null
null
null
2,404.14461
Competition Report: Finding Universal Jailbreak Backdoors in Aligned LLMs
['Javier Rando', 'Francesco Croce', 'Kryštof Mitka', 'Stepan Shabalin', 'Maksym Andriushchenko', 'Nicolas Flammarion', 'Florian Tramèr']
['cs.CL', 'cs.AI', 'cs.CR', 'cs.LG']
Large language models are aligned to be safe, preventing users from generating harmful content like misinformation or instructions for illegal activities. However, previous work has shown that the alignment process is vulnerable to poisoning attacks. Adversaries can manipulate the safety training data to inject backdoo...
2024-04-22T05:08:53Z
Competition Report
null
null
Competition Report: Finding Universal Jailbreak Backdoors in Aligned LLMs
['Javier Rando', 'Francesco Croce', 'Kryvstof Mitka', 'Stepan Shabalin', 'Maksym Andriushchenko', 'Nicolas Flammarion', 'Florian Tramèr']
2,024
arXiv.org
17
22
['Computer Science']
2,404.14568
UVMap-ID: A Controllable and Personalized UV Map Generative Model
['Weijie Wang', 'Jichao Zhang', 'Chang Liu', 'Xia Li', 'Xingqian Xu', 'Humphrey Shi', 'Nicu Sebe', 'Bruno Lepri']
['cs.CV']
Recently, diffusion models have made significant strides in synthesizing realistic 2D human images based on provided text prompts. Building upon this, researchers have extended 2D text-to-image diffusion models into the 3D domain for generating human textures (UV Maps). However, some important problems about UV Map Gen...
2024-04-22T20:30:45Z
Accepted to ACMMM2024
null
null
UVMap-ID: A Controllable and Personalized UV Map Generative Model
['Weijie Wang', 'Jichao Zhang', 'Chang Liu', 'Xia Li', 'Xingqian Xu', 'Humphrey Shi', 'N. Sebe', 'Bruno Lepri']
2,024
ACM Multimedia
3
58
['Computer Science']
2,404.14619
OpenELM: An Efficient Language Model Family with Open Training and Inference Framework
['Sachin Mehta', 'Mohammad Hossein Sekhavat', 'Qingqing Cao', 'Maxwell Horton', 'Yanzi Jin', 'Chenfan Sun', 'Iman Mirzadeh', 'Mahyar Najibi', 'Dmitry Belenko', 'Peter Zatloukal', 'Mohammad Rastegari']
['cs.CL', 'cs.AI', 'cs.LG']
The reproducibility and transparency of large language models are crucial for advancing open research, ensuring the trustworthiness of results, and enabling investigations into data and model biases, as well as potential risks. To this end, we release OpenELM, a state-of-the-art open language model. OpenELM uses a laye...
2024-04-22T23:12:03Z
Minor corrections
null
null
OpenELM: An Efficient Language Model Family with Open Training and Inference Framework
['Sachin Mehta', 'M. Sekhavat', 'Qingqing Cao', 'Maxwell Horton', 'Yanzi Jin', 'Chenfan Sun', 'Iman Mirzadeh', 'Mahyar Najibi', 'Dmitry Belenko', 'Peter Zatloukal', 'Mohammad Rastegari']
2,024
arXiv.org
62
54
['Computer Science']
2,404.14779
Med42 -- Evaluating Fine-Tuning Strategies for Medical LLMs: Full-Parameter vs. Parameter-Efficient Approaches
['Clément Christophe', 'Praveen K Kanithi', 'Prateek Munjal', 'Tathagata Raha', 'Nasir Hayat', 'Ronnie Rajan', 'Ahmed Al-Mahrooqi', 'Avani Gupta', 'Muhammad Umar Salman', 'Gurpreet Gosal', 'Bhargav Kanakiya', 'Charles Chen', 'Natalia Vassilieva', 'Boulbaba Ben Amor', 'Marco AF Pimentel', 'Shadab Khan']
['cs.CL']
This study presents a comprehensive analysis and comparison of two predominant fine-tuning methodologies - full-parameter fine-tuning and parameter-efficient tuning - within the context of medical Large Language Models (LLMs). We developed and refined a series of LLMs, based on the Llama-2 architecture, specifically de...
2024-04-23T06:36:21Z
Published at AAAI 2024 Spring Symposium - Clinical Foundation Models
null
null
Med42 - Evaluating Fine-Tuning Strategies for Medical LLMs: Full-Parameter vs. Parameter-Efficient Approaches
["Cl'ement Christophe", 'P. Kanithi', 'Prateek Munjal', 'Tathagata Raha', 'Nasir Hayat', 'Ronnie Rajan', 'Ahmed Al-Mahrooqi', 'Avani Gupta', 'Muhammad Umar Salman', 'Gurpreet Gosal', 'Bhargav Kanakiya', 'Charles Chen', 'N. Vassilieva', 'B. Amor', 'Marco A. F. Pimentel', 'Shadab Khan']
2,024
arXiv.org
35
36
['Computer Science']
2,404.14966
Mamba3D: Enhancing Local Features for 3D Point Cloud Analysis via State Space Model
['Xu Han', 'Yuan Tang', 'Zhaoxuan Wang', 'Xianzhi Li']
['cs.CV', 'cs.AI', 'cs.LG']
Existing Transformer-based models for point cloud analysis suffer from quadratic complexity, leading to compromised point cloud resolution and information loss. In contrast, the newly proposed Mamba model, based on state space models (SSM), outperforms Transformer in multiple areas with only linear complexity. However,...
2024-04-23T12:20:27Z
ACM MM 2024. Code and weights are available at https://github.com/xhanxu/Mamba3D
null
null
null
null
null
null
null
null
null
2,404.15159
MixLoRA: Enhancing Large Language Models Fine-Tuning with LoRA-based Mixture of Experts
['Dengchun Li', 'Yingzi Ma', 'Naizheng Wang', 'Zhengmao Ye', 'Zhiyuan Cheng', 'Yinghao Tang', 'Yan Zhang', 'Lei Duan', 'Jie Zuo', 'Cal Yang', 'Mingjie Tang']
['cs.CL', 'cs.AI']
Fine-tuning Large Language Models (LLMs) is a common practice to adapt pre-trained models for specific applications. While methods like LoRA have effectively addressed GPU memory constraints during fine-tuning, their performance often falls short, especially in multi-task scenarios. In contrast, Mixture-of-Expert (MoE)...
2024-04-22T02:15:52Z
18 pages, 5 figures
null
null
null
null
null
null
null
null
null
2,404.15217
Towards Large-Scale Training of Pathology Foundation Models
['kaiko. ai', 'Nanne Aben', 'Edwin D. de Jong', 'Ioannis Gatopoulos', 'Nicolas Känzig', 'Mikhail Karasikov', 'Axel Lagré', 'Roman Moser', 'Joost van Doorn', 'Fei Tang']
['cs.CV', 'cs.LG']
Driven by the recent advances in deep learning methods and, in particular, by the development of modern self-supervised learning algorithms, increased interest and efforts have been devoted to build foundation models (FMs) for medical images. In this work, we present our scalable training pipeline for large pathology i...
2024-03-24T21:34:36Z
null
null
null
null
null
null
null
null
null
null
2,404.15254
UniMERNet: A Universal Network for Real-World Mathematical Expression Recognition
['Bin Wang', 'Zhuangcheng Gu', 'Guang Liang', 'Chao Xu', 'Bo Zhang', 'Botian Shi', 'Conghui He']
['cs.CV']
The paper introduces the UniMER dataset, marking the first study on Mathematical Expression Recognition (MER) targeting complex real-world scenarios. The UniMER dataset includes a large-scale training set, UniMER-1M, which offers unprecedented scale and diversity with one million training instances to train high-qualit...
2024-04-23T17:39:27Z
Project Website: https://github.com/opendatalab/UniMERNet
null
null
UniMERNet: A Universal Network for Real-World Mathematical Expression Recognition
['Bin Wang', 'Zhuangcheng Gu', 'Chaochao Xu', 'Bo Zhang', 'Botian Shi', 'Conghui He']
2,024
arXiv.org
13
42
['Computer Science']
2,404.15264
TalkingGaussian: Structure-Persistent 3D Talking Head Synthesis via Gaussian Splatting
['Jiahe Li', 'Jiawei Zhang', 'Xiao Bai', 'Jin Zheng', 'Xin Ning', 'Jun Zhou', 'Lin Gu']
['cs.CV']
Radiance fields have demonstrated impressive performance in synthesizing lifelike 3D talking heads. However, due to the difficulty in fitting steep appearance changes, the prevailing paradigm that presents facial motions by directly modifying point appearance may lead to distortions in dynamic regions. To tackle this c...
2024-04-23T17:55:07Z
Accepted at ECCV 2024. Project page: https://fictionarry.github.io/TalkingGaussian/
null
null
null
null
null
null
null
null
null
2,404.15267
From Parts to Whole: A Unified Reference Framework for Controllable Human Image Generation
['Zehuan Huang', 'Hongxing Fan', 'Lipeng Wang', 'Lu Sheng']
['cs.CV']
Recent advancements in controllable human image generation have led to zero-shot generation using structural signals (e.g., pose, depth) or facial appearance. Yet, generating human images conditioned on multiple parts of human appearance remains challenging. Addressing this, we introduce Parts2Whole, a novel framework ...
2024-04-23T17:56:08Z
null
null
null
null
null
null
null
null
null
null
2,404.15275
ID-Animator: Zero-Shot Identity-Preserving Human Video Generation
['Xuanhua He', 'Quande Liu', 'Shengju Qian', 'Xin Wang', 'Tao Hu', 'Ke Cao', 'Keyu Yan', 'Jie Zhang']
['cs.CV']
Generating high-fidelity human video with specified identities has attracted significant attention in the content generation community. However, existing techniques struggle to strike a balance between training efficiency and identity preservation, either requiring tedious case-by-case fine-tuning or usually missing id...
2024-04-23T17:59:43Z
Project Page: https://id-animator.github.io/
null
null
ID-Animator: Zero-Shot Identity-Preserving Human Video Generation
['Xuanhua He', 'Quande Liu', 'Shengju Qian', 'Xin Wang', 'Tao Hu', 'Ke Cao', 'K. Yan', 'Man Zhou', 'Jie Zhang']
2,024
arXiv.org
50
46
['Computer Science']
2,404.16022
PuLID: Pure and Lightning ID Customization via Contrastive Alignment
['Zinan Guo', 'Yanze Wu', 'Zhuowei Chen', 'Lang Chen', 'Peng Zhang', 'Qian He']
['cs.CV']
We propose Pure and Lightning ID customization (PuLID), a novel tuning-free ID customization method for text-to-image generation. By incorporating a Lightning T2I branch with a standard diffusion one, PuLID introduces both contrastive alignment loss and accurate ID loss, minimizing disruption to the original model and ...
2024-04-24T17:55:33Z
NeurIPS 2024. Codes and models are available at https://github.com/ToTheBeginning/PuLID
null
null
PuLID: Pure and Lightning ID Customization via Contrastive Alignment
['Zinan Guo', 'Yanze Wu', 'Zhuowei Chen', 'Lang Chen', 'Qian He']
2,024
Neural Information Processing Systems
66
53
['Computer Science']
2,404.16035
MaGGIe: Masked Guided Gradual Human Instance Matting
['Chuong Huynh', 'Seoung Wug Oh', 'Abhinav Shrivastava', 'Joon-Young Lee']
['cs.CV', 'cs.AI']
Human matting is a foundation task in image and video processing, where human foreground pixels are extracted from the input. Prior works either improve the accuracy by additional guidance or improve the temporal consistency of a single instance across frames. We propose a new framework MaGGIe, Masked Guided Gradual Hu...
2024-04-24T17:59:53Z
CVPR 2024. Project link: https://maggie-matt.github.io
null
null
MaGGIe: Masked Guided Gradual Human Instance Matting
['Chuong Huynh', 'Seoung Wug Oh', 'Abhinav Shrivastava', 'Joon-Young Lee']
2,024
Computer Vision and Pattern Recognition
8
57
['Computer Science']
2,404.16053
Human Latency Conversational Turns for Spoken Avatar Systems
['Derek Jacoby', 'Tianyi Zhang', 'Aanchan Mohan', 'Yvonne Coady']
['cs.HC', 'cs.AI', 'cs.CL']
A problem with many current Large Language Model (LLM) driven spoken dialogues is the response time. Some efforts such as Groq address this issue by lightning fast processing of the LLM, but we know from the cognitive psychology literature that in human-to-human dialogue often responses occur prior to the speaker compl...
2024-04-11T20:20:48Z
null
null
null
null
null
null
null
null
null
null
2,404.16375
List Items One by One: A New Data Source and Learning Paradigm for Multimodal LLMs
['An Yan', 'Zhengyuan Yang', 'Junda Wu', 'Wanrong Zhu', 'Jianwei Yang', 'Linjie Li', 'Kevin Lin', 'Jianfeng Wang', 'Julian McAuley', 'Jianfeng Gao', 'Lijuan Wang']
['cs.CV', 'cs.AI', 'cs.CL']
Set-of-Mark (SoM) Prompting unleashes the visual grounding capability of GPT-4V, by enabling the model to associate visual objects with tags inserted on the image. These tags, marked with alphanumerics, can be indexed via text tokens for easy reference. Despite the extraordinary performance from GPT-4V, we observe that...
2024-04-25T07:29:17Z
published at COLM-2024
null
null
null
null
null
null
null
null
null
2,404.16621
Hippocrates: An Open-Source Framework for Advancing Large Language Models in Healthcare
['Emre Can Acikgoz', 'Osman Batur İnce', 'Rayene Bench', 'Arda Anıl Boz', 'İlker Kesen', 'Aykut Erdem', 'Erkut Erdem']
['cs.LG', 'cs.AI', 'cs.CL']
The integration of Large Language Models (LLMs) into healthcare promises to transform medical diagnostics, research, and patient care. Yet, the progression of medical LLMs faces obstacles such as complex training requirements, rigorous evaluation demands, and the dominance of proprietary models that restrict academic e...
2024-04-25T14:06:37Z
null
null
null
Hippocrates: An Open-Source Framework for Advancing Large Language Models in Healthcare
['Emre Can Acikgoz', 'Osman Batur .Ince', 'Rayene Bench', 'Arda Anil Boz', '.Ilker Kesen', 'Aykut Erdem', 'Erkut Erdem']
2,024
arXiv.org
10
44
['Computer Science']
2,404.16645
Tele-FLM Technical Report
['Xiang Li', 'Yiqun Yao', 'Xin Jiang', 'Xuezhi Fang', 'Chao Wang', 'Xinzhang Liu', 'Zihan Wang', 'Yu Zhao', 'Xin Wang', 'Yuyao Huang', 'Shuangyong Song', 'Yongxiang Li', 'Zheng Zhang', 'Bo Zhao', 'Aixin Sun', 'Yequan Wang', 'Zhongjiang He', 'Zhongyuan Wang', 'Xuelong Li', 'Tiejun Huang']
['cs.CL', 'cs.AI']
Large language models (LLMs) have showcased profound capabilities in language understanding and generation, facilitating a wide array of applications. However, there is a notable paucity of detailed, open-sourced methodologies on efficiently scaling LLMs beyond 50 billion parameters with minimum trial-and-error cost an...
2024-04-25T14:34:47Z
null
null
null
Tele-FLM Technical Report
['Xiang Li', 'Yiqun Yao', 'Xin Jiang', 'Xuezhi Fang', 'Chao Wang', 'Xinzhan Liu', 'Zihan Wang', 'Yu Zhao', 'Xin Wang', 'Yuyao Huang', 'Shuangyong Song', 'Yongxiang Li', 'Zheng Zhang', 'Bo Zhao', 'Aixin Sun', 'Yequan Wang', 'Zhongjiang He', 'Zhongyuan Wang', 'Xuelong Li', 'Tiejun Huang']
2,024
arXiv.org
4
78
['Computer Science']
2,404.1671
LayerSkip: Enabling Early Exit Inference and Self-Speculative Decoding
['Mostafa Elhoushi', 'Akshat Shrivastava', 'Diana Liskovich', 'Basil Hosmer', 'Bram Wasti', 'Liangzhen Lai', 'Anas Mahmoud', 'Bilge Acun', 'Saurabh Agarwal', 'Ahmed Roman', 'Ahmed A Aly', 'Beidi Chen', 'Carole-Jean Wu']
['cs.CL', 'cs.AI', 'cs.LG']
We present LayerSkip, an end-to-end solution to speed-up inference of large language models (LLMs). First, during training we apply layer dropout, with low dropout rates for earlier layers and higher dropout rates for later layers, and an early exit loss where all transformer layers share the same exit. Second, during ...
2024-04-25T16:20:23Z
ACL 2024
null
10.18653/v1/2024.acl-long.681
LayerSkip: Enabling Early Exit Inference and Self-Speculative Decoding
['Mostafa Elhoushi', 'Akshat Shrivastava', 'Diana Liskovich', 'Basil Hosmer', 'Bram Wasti', 'Liangzhen Lai', 'Anas Mahmoud', 'Bilge Acun', 'Saurabh Agarwal', 'Ahmed Roman', 'Ahmed Aly', 'Beidi Chen', 'Carole-Jean Wu']
2,024
Annual Meeting of the Association for Computational Linguistics
110
62
['Computer Science']
2,404.16767
REBEL: Reinforcement Learning via Regressing Relative Rewards
['Zhaolin Gao', 'Jonathan D. Chang', 'Wenhao Zhan', 'Owen Oertell', 'Gokul Swamy', 'Kianté Brantley', 'Thorsten Joachims', 'J. Andrew Bagnell', 'Jason D. Lee', 'Wen Sun']
['cs.LG', 'cs.CL', 'cs.CV']
While originally developed for continuous control problems, Proximal Policy Optimization (PPO) has emerged as the work-horse of a variety of reinforcement learning (RL) applications, including the fine-tuning of generative models. Unfortunately, PPO requires multiple heuristics to enable stable convergence (e.g. value ...
2024-04-25T17:20:45Z
New experimental results on general chat
null
null
null
null
null
null
null
null
null
2,404.16771
ConsistentID: Portrait Generation with Multimodal Fine-Grained Identity Preserving
['Jiehui Huang', 'Xiao Dong', 'Wenhui Song', 'Zheng Chong', 'Zhenchao Tang', 'Jun Zhou', 'Yuhao Cheng', 'Long Chen', 'Hanhui Li', 'Yiqiang Yan', 'Shengcai Liao', 'Xiaodan Liang']
['cs.CV', 'cs.AI']
Diffusion-based technologies have made significant strides, particularly in personalized and customized facialgeneration. However, existing methods face challenges in achieving high-fidelity and detailed identity (ID)consistency, primarily due to insufficient fine-grained control over facial areas and the lack of a com...
2024-04-25T17:23:43Z
Project page: https://ssugarwh.github.io/consistentid.github.io/
null
null
null
null
null
null
null
null
null
2,404.16792
Model Extrapolation Expedites Alignment
['Chujie Zheng', 'Ziqi Wang', 'Heng Ji', 'Minlie Huang', 'Nanyun Peng']
['cs.LG', 'cs.AI', 'cs.CL']
Given the high computational cost of preference alignment training of large language models (LLMs), exploring efficient methods to reduce the training overhead remains an important and compelling research problem. Motivated by the observation that alignment training typically involves only small parameter changes witho...
2024-04-25T17:39:50Z
ACL 2025
null
null
null
null
null
null
null
null
null
2,404.16811
Make Your LLM Fully Utilize the Context
['Shengnan An', 'Zexiong Ma', 'Zeqi Lin', 'Nanning Zheng', 'Jian-Guang Lou']
['cs.CL', 'cs.AI']
While many contemporary large language models (LLMs) can process lengthy input, they still struggle to fully utilize information within the long context, known as the lost-in-the-middle challenge. We hypothesize that it stems from insufficient explicit supervision during the long-context training, which fails to emphas...
2024-04-25T17:55:14Z
19 pages, 7 figures, 3 tables, 9 examples
null
null
null
null
null
null
null
null
null
2,404.16816
IndicGenBench: A Multilingual Benchmark to Evaluate Generation Capabilities of LLMs on Indic Languages
['Harman Singh', 'Nitish Gupta', 'Shikhar Bharadwaj', 'Dinesh Tewari', 'Partha Talukdar']
['cs.CL']
As large language models (LLMs) see increasing adoption across the globe, it is imperative for LLMs to be representative of the linguistic diversity of the world. India is a linguistically diverse country of 1.4 Billion people. To facilitate research on multilingual LLM evaluation, we release IndicGenBench - the larges...
2024-04-25T17:57:36Z
ACL 2024
null
null
IndicGenBench: A Multilingual Benchmark to Evaluate Generation Capabilities of LLMs on Indic Languages
['Harman Singh', 'Nitish Gupta', 'Shikhar Bharadwaj', 'Dinesh Tewari', 'Partha Talukdar']
2,024
Annual Meeting of the Association for Computational Linguistics
28
46
['Computer Science']
2,404.16821
How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suites
['Zhe Chen', 'Weiyun Wang', 'Hao Tian', 'Shenglong Ye', 'Zhangwei Gao', 'Erfei Cui', 'Wenwen Tong', 'Kongzhi Hu', 'Jiapeng Luo', 'Zheng Ma', 'Ji Ma', 'Jiaqi Wang', 'Xiaoyi Dong', 'Hang Yan', 'Hewei Guo', 'Conghui He', 'Botian Shi', 'Zhenjiang Jin', 'Chao Xu', 'Bin Wang', 'Xingjian Wei', 'Wei Li', 'Wenjian Zhang', 'Bo Z...
['cs.CV']
In this report, we introduce InternVL 1.5, an open-source multimodal large language model (MLLM) to bridge the capability gap between open-source and proprietary commercial models in multimodal understanding. We introduce three simple improvements: (1) Strong Vision Encoder: we explored a continuous learning strategy f...
2024-04-25T17:59:19Z
Technical report
null
null
null
null
null
null
null
null
null
2,404.16994
PLLaVA : Parameter-free LLaVA Extension from Images to Videos for Video Dense Captioning
['Lin Xu', 'Yilin Zhao', 'Daquan Zhou', 'Zhijie Lin', 'See Kiong Ng', 'Jiashi Feng']
['cs.CV']
Vision-language pre-training has significantly elevated performance across a wide range of image-language applications. Yet, the pre-training process for video-related tasks demands exceptionally large computational and data resources, which hinders the progress of video-language models. This paper investigates a strai...
2024-04-25T19:29:55Z
null
null
null
null
null
null
null
null
null
null
2,404.1714
Small Language Models Need Strong Verifiers to Self-Correct Reasoning
['Yunxiang Zhang', 'Muhammad Khalifa', 'Lajanugen Logeswaran', 'Jaekyeom Kim', 'Moontae Lee', 'Honglak Lee', 'Lu Wang']
['cs.CL']
Self-correction has emerged as a promising solution to boost the reasoning performance of large language models (LLMs), where LLMs refine their solutions using self-generated critiques that pinpoint the errors. This work explores whether small (<= 13B) language models (LMs) have the ability of self-correction on reason...
2024-04-26T03:41:28Z
ACL Findings 2024 - Camera Ready
null
null
null
null
null
null
null
null
null
2,404.17336
Introducing cosmosGPT: Monolingual Training for Turkish Language Models
['H. Toprak Kesgin', 'M. Kaan Yuce', 'Eren Dogan', 'M. Egemen Uzun', 'Atahan Uz', 'H. Emre Seyrek', 'Ahmed Zeer', 'M. Fatih Amasyali']
['cs.CL', 'cs.AI']
The number of open source language models that can produce Turkish is increasing day by day, as in other languages. In order to create the basic versions of such models, the training of multilingual models is usually continued with Turkish corpora. The alternative is to train the model with only Turkish corpora. In thi...
2024-04-26T11:34:11Z
null
null
null
null
null
null
null
null
null
null
2,404.1736
UniRGB-IR: A Unified Framework for Visible-Infrared Semantic Tasks via Adapter Tuning
['Maoxun Yuan', 'Bo Cui', 'Tianyi Zhao', 'Jiayi Wang', 'Shan Fu', 'Xue Yang', 'Xingxing Wei']
['cs.CV']
Semantic analysis on visible (RGB) and infrared (IR) images has gained significant attention due to their enhanced accuracy and robustness under challenging conditions including low-illumination and adverse weather. However, due to the lack of pre-trained foundation models on the large-scale infrared image datasets, ex...
2024-04-26T12:21:57Z
null
null
null
null
null
null
null
null
null
null
2,404.17733
Building a Large Japanese Web Corpus for Large Language Models
['Naoaki Okazaki', 'Kakeru Hattori', 'Hirai Shota', 'Hiroki Iida', 'Masanari Ohi', 'Kazuki Fujii', 'Taishi Nakamura', 'Mengsay Loem', 'Rio Yokota', 'Sakae Mizuki']
['cs.CL', 'cs.AI']
Open Japanese large language models (LLMs) have been trained on the Japanese portions of corpora such as CC-100, mC4, and OSCAR. However, these corpora were not created for the quality of Japanese texts. This study builds a large Japanese web corpus by extracting and refining text from the Common Crawl archive (21 snap...
2024-04-27T00:02:45Z
17 pages
null
null
Building a Large Japanese Web Corpus for Large Language Models
['Naoaki Okazaki', 'Kakeru Hattori', 'Hirai Shota', 'Hiroki Iida', 'Masanari Ohi', 'Kazuki Fujii', 'Taishi Nakamura', 'Mengsay Loem', 'Rio Yokota', 'Sakae Mizuki']
2,024
arXiv.org
7
48
['Computer Science']
2,404.1779
Continual Pre-Training for Cross-Lingual LLM Adaptation: Enhancing Japanese Language Capabilities
['Kazuki Fujii', 'Taishi Nakamura', 'Mengsay Loem', 'Hiroki Iida', 'Masanari Ohi', 'Kakeru Hattori', 'Hirai Shota', 'Sakae Mizuki', 'Rio Yokota', 'Naoaki Okazaki']
['cs.CL', 'cs.AI']
Cross-lingual continual pre-training of large language models (LLMs) initially trained on English corpus allows us to leverage the vast amount of English language resources and reduce the pre-training cost. In this study, we constructed Swallow, an LLM with enhanced Japanese capability, by extending the vocabulary of L...
2024-04-27T06:07:55Z
null
null
null
null
null
null
null
null
null
null
2,404.18212
Paint by Inpaint: Learning to Add Image Objects by Removing Them First
['Navve Wasserman', 'Noam Rotstein', 'Roy Ganz', 'Ron Kimmel']
['cs.CV', 'cs.AI']
Image editing has advanced significantly with the introduction of text-conditioned diffusion models. Despite this progress, seamlessly adding objects to images based on textual instructions without requiring user-provided input masks remains a challenge. We address this by leveraging the insight that removing objects (...
2024-04-28T15:07:53Z
null
null
null
Paint by Inpaint: Learning to Add Image Objects by Removing Them First
['Navve Wasserman', 'Noam Rotstein', 'Roy Ganz', 'Ron Kimmel']
2,024
arXiv.org
16
71
['Computer Science']
2,404.18443
BMRetriever: Tuning Large Language Models as Better Biomedical Text Retrievers
['Ran Xu', 'Wenqi Shi', 'Yue Yu', 'Yuchen Zhuang', 'Yanqiao Zhu', 'May D. Wang', 'Joyce C. Ho', 'Chao Zhang', 'Carl Yang']
['cs.CL', 'cs.AI', 'cs.IR', 'q-bio.QM']
Developing effective biomedical retrieval models is important for excelling at knowledge-intensive biomedical tasks but still challenging due to the deficiency of sufficient publicly annotated biomedical data and computational resources. We present BMRetriever, a series of dense retrievers for enhancing biomedical retr...
2024-04-29T05:40:08Z
Accepted to EMNLP 2024. The model and data are uploaded to \url{https://github.com/ritaranx/BMRetriever}
EMNLP 2024
null
BMRetriever: Tuning Large Language Models as Better Biomedical Text Retrievers
['Ran Xu', 'Wenqi Shi', 'Yue Yu', 'Yuchen Zhuang', 'Yanqiao Zhu', 'M. D. Wang', 'Joyce C. Ho', 'Chao Zhang', 'Carl Yang']
2,024
Conference on Empirical Methods in Natural Language Processing
25
98
['Computer Science', 'Biology']
2,404.18585
FREB-TQA: A Fine-Grained Robustness Evaluation Benchmark for Table Question Answering
['Wei Zhou', 'Mohsen Mesgar', 'Heike Adel', 'Annemarie Friedrich']
['cs.CL']
Table Question Answering (TQA) aims at composing an answer to a question based on tabular data. While prior research has shown that TQA models lack robustness, understanding the underlying cause and nature of this issue remains predominantly unclear, posing a significant obstacle to the development of robust TQA system...
2024-04-29T10:55:08Z
Accepted at NAACL 2024
null
null
FREB-TQA: A Fine-Grained Robustness Evaluation Benchmark for Table Question Answering
['Wei Zhou', 'Mohsen Mesgar', 'Heike Adel', 'Annemarie Friedrich']
2,024
North American Chapter of the Association for Computational Linguistics
9
29
['Computer Science']
2,404.18591
FashionSD-X: Multimodal Fashion Garment Synthesis using Latent Diffusion
['Abhishek Kumar Singh', 'Ioannis Patras']
['cs.CV', 'cs.AI']
The rapid evolution of the fashion industry increasingly intersects with technological advancements, particularly through the integration of generative AI. This study introduces a novel generative pipeline designed to transform the fashion design process by employing latent diffusion models. Utilizing ControlNet and Lo...
2024-04-26T14:59:42Z
9 pages, 8 figures
null
null
FashionSD-X: Multimodal Fashion Garment Synthesis using Latent Diffusion
['Abhishek Kumar Singh', 'Ioannis Patras']
2,024
arXiv.org
4
0
['Computer Science']
2,404.18796
Replacing Judges with Juries: Evaluating LLM Generations with a Panel of Diverse Models
['Pat Verga', 'Sebastian Hofstatter', 'Sophia Althammer', 'Yixuan Su', 'Aleksandra Piktus', 'Arkady Arkhangorodsky', 'Minjie Xu', 'Naomi White', 'Patrick Lewis']
['cs.CL', 'cs.AI']
As Large Language Models (LLMs) have become more advanced, they have outpaced our abilities to accurately evaluate their quality. Not only is finding data to adequately probe particular model properties difficult, but evaluating the correctness of a model's freeform generation alone is a challenge. To address this, man...
2024-04-29T15:33:23Z
null
null
null
null
null
null
null
null
null
null
2,404.18824
Benchmarking Benchmark Leakage in Large Language Models
['Ruijie Xu', 'Zengzhi Wang', 'Run-Ze Fan', 'Pengfei Liu']
['cs.CL', 'cs.AI', 'cs.LG']
Amid the expanding use of pre-training data, the phenomenon of benchmark dataset leakage has become increasingly prominent, exacerbated by opaque training processes and the often undisclosed inclusion of supervised data in contemporary Large Language Models (LLMs). This issue skews benchmark effectiveness and fosters p...
2024-04-29T16:05:36Z
30 pages; Homepage: https://gair-nlp.github.io/benbench
null
null
Benchmarking Benchmark Leakage in Large Language Models
['Ruijie Xu', 'Zengzhi Wang', 'Run-Ze Fan', 'Pengfei Liu']
2,024
arXiv.org
54
63
['Computer Science']
2,404.18873
OpenStreetView-5M: The Many Roads to Global Visual Geolocation
['Guillaume Astruc', 'Nicolas Dufour', 'Ioannis Siglidis', 'Constantin Aronssohn', 'Nacim Bouia', 'Stephanie Fu', 'Romain Loiseau', 'Van Nguyen Nguyen', 'Charles Raude', 'Elliot Vincent', 'Lintao XU', 'Hongyu Zhou', 'Loic Landrieu']
['cs.CV', 'cs.AI']
Determining the location of an image anywhere on Earth is a complex visual task, which makes it particularly relevant for evaluating computer vision algorithms. Yet, the absence of standard, large-scale, open-access datasets with reliably localizable images has limited its potential. To address this issue, we introduce...
2024-04-29T17:06:44Z
CVPR 2024
null
null
null
null
null
null
null
null
null
2,404.18896
Overcoming Knowledge Barriers: Online Imitation Learning from Visual Observation with Pretrained World Models
['Xingyuan Zhang', 'Philip Becker-Ehmck', 'Patrick van der Smagt', 'Maximilian Karl']
['cs.LG']
Pretraining and finetuning models has become increasingly popular in decision-making. But there are still serious impediments in Imitation Learning from Observation (ILfO) with pretrained models. This study identifies two primary obstacles: the Embodiment Knowledge Barrier (EKB) and the Demonstration Knowledge Barrier ...
2024-04-29T17:33:52Z
Accepted at TMLR
null
null
null
null
null
null
null
null
null
2,404.19205
TableVQA-Bench: A Visual Question Answering Benchmark on Multiple Table Domains
['Yoonsik Kim', 'Moonbin Yim', 'Ka Yeon Song']
['cs.CV', 'cs.AI']
In this paper, we establish a benchmark for table visual question answering, referred to as the TableVQA-Bench, derived from pre-existing table question-answering (QA) and table structure recognition datasets. It is important to note that existing datasets have not incorporated images or QA pairs, which are two crucial...
2024-04-30T02:05:18Z
Technical Report
null
null
null
null
null
null
null
null
null
2,404.19296
Octopus v4: Graph of language models
['Wei Chen', 'Zhiyuan Li']
['cs.CL']
Language models have been effective in a wide range of applications, yet the most sophisticated models are often proprietary. For example, GPT-4 by OpenAI and various models by Anthropic are expensive and consume substantial energy. In contrast, the open-source community has produced competitive models, like Llama3. Fu...
2024-04-30T06:55:45Z
null
null
null
null
null
null
null
null
null
null
2,404.19737
Better & Faster Large Language Models via Multi-token Prediction
['Fabian Gloeckle', 'Badr Youbi Idrissi', 'Baptiste Rozière', 'David Lopez-Paz', 'Gabriel Synnaeve']
['cs.CL']
Large language models such as GPT and Llama are trained with a next-token prediction loss. In this work, we suggest that training language models to predict multiple future tokens at once results in higher sample efficiency. More specifically, at each position in the training corpus, we ask the model to predict the fol...
2024-04-30T17:33:57Z
null
null
null
Better & Faster Large Language Models via Multi-token Prediction
['Fabian Gloeckle', 'Badr Youbi Idrissi', 'Baptiste Rozière', 'David Lopez-Paz', 'Gabriele Synnaeve']
2,024
International Conference on Machine Learning
121
54
['Computer Science']
2,404.19756
KAN: Kolmogorov-Arnold Networks
['Ziming Liu', 'Yixuan Wang', 'Sachin Vaidya', 'Fabian Ruehle', 'James Halverson', 'Marin Soljačić', 'Thomas Y. Hou', 'Max Tegmark']
['cs.LG', 'cond-mat.dis-nn', 'cs.AI', 'stat.ML']
Inspired by the Kolmogorov-Arnold representation theorem, we propose Kolmogorov-Arnold Networks (KANs) as promising alternatives to Multi-Layer Perceptrons (MLPs). While MLPs have fixed activation functions on nodes ("neurons"), KANs have learnable activation functions on edges ("weights"). KANs have no linear weights ...
2024-04-30T17:58:29Z
Accepted by International Conference on Learning Representations (ICLR) 2025 (conference version: https://openreview.net/forum?id=Ozo7qJ5vZi). Codes are available at https://github.com/KindXiaoming/pykan
null
null
KAN: Kolmogorov-Arnold Networks
['Ziming Liu', 'Yixuan Wang', 'Sachin Vaidya', 'Fabian Ruehle', 'James Halverson', 'Marin Soljacic', 'Thomas Y. Hou', 'Max Tegmark']
2,024
International Conference on Learning Representations
602
151
['Computer Science', 'Physics', 'Mathematics']
2,405.00134
Transforming Dutch: Debiasing Dutch Coreference Resolution Systems for Non-binary Pronouns
['Goya van Boven', 'Yupei Du', 'Dong Nguyen']
['cs.CL', 'cs.AI', 'I.2.7']
Gender-neutral pronouns are increasingly being introduced across Western languages. Recent evaluations have however demonstrated that English NLP systems are unable to correctly process gender-neutral pronouns, with the risk of erasing and misgendering non-binary individuals. This paper examines a Dutch coreference res...
2024-04-30T18:31:19Z
22 pages, 2 figures. Accepted at the 2024 ACM Conference on Fairness, Accountability, and Transparency (FAccT '24)
null
10.1145/3630106.3659049
Transforming Dutch: Debiasing Dutch Coreference Resolution Systems for Non-binary Pronouns
['Goya van Boven', 'Yupei Du', 'Dong Nguyen']
2,024
Conference on Fairness, Accountability and Transparency
1
54
['Computer Science']
2,405.00145
GUing: A Mobile GUI Search Engine using a Vision-Language Model
['Jialiang Wei', 'Anne-Lise Courbis', 'Thomas Lambolais', 'Binbin Xu', 'Pierre Louis Bernard', 'Gérard Dray', 'Walid Maalej']
['cs.SE', 'cs.CV']
Graphical User Interfaces (GUIs) are central to app development projects. App developers may use the GUIs of other apps as a means of requirements refinement and rapid prototyping or as a source of inspiration for designing and improving their own apps. Recent research has thus suggested retrieving relevant GUI designs...
2024-04-30T18:42:18Z
Accepted to ACM Transactions on Software Engineering and Methodology (TOSEM)
null
10.1145/3702993
null
null
null
null
null
null
null
2,405.002
In-Context Learning with Long-Context Models: An In-Depth Exploration
['Amanda Bertsch', 'Maor Ivgi', 'Emily Xiao', 'Uri Alon', 'Jonathan Berant', 'Matthew R. Gormley', 'Graham Neubig']
['cs.CL']
As model context lengths continue to increase, the number of demonstrations that can be provided in-context approaches the size of entire training datasets. We study the behavior of in-context learning (ICL) at this extreme scale on multiple datasets and models. We show that, for many datasets with large label spaces, ...
2024-04-30T21:06:52Z
32 pages; NAACL 2025 camera-ready
null
null
In-Context Learning with Long-Context Models: An In-Depth Exploration
['Amanda Bertsch', 'Maor Ivgi', 'Uri Alon', 'Jonathan Berant', 'Matthew R. Gormley', 'Graham Neubig']
2,024
North American Chapter of the Association for Computational Linguistics
79
69
['Computer Science']
2,405.00208
A Primer on the Inner Workings of Transformer-based Language Models
['Javier Ferrando', 'Gabriele Sarti', 'Arianna Bisazza', 'Marta R. Costa-jussà']
['cs.CL']
The rapid progress of research aimed at interpreting the inner workings of advanced language models has highlighted a need for contextualizing the insights gained from years of work in this area. This primer provides a concise technical introduction to the current techniques used to interpret the inner workings of Tran...
2024-04-30T21:20:17Z
null
null
null
A Primer on the Inner Workings of Transformer-based Language Models
['Javier Ferrando', 'Gabriele Sarti', 'Arianna Bisazza', 'M. Costa-jussà']
2,024
arXiv.org
50
0
['Computer Science']
2,405.00332
A Careful Examination of Large Language Model Performance on Grade School Arithmetic
['Hugh Zhang', 'Jeff Da', 'Dean Lee', 'Vaughn Robinson', 'Catherine Wu', 'Will Song', 'Tiffany Zhao', 'Pranav Raja', 'Charlotte Zhuang', 'Dylan Slack', 'Qin Lyu', 'Sean Hendryx', 'Russell Kaplan', 'Michele Lunati', 'Summer Yue']
['cs.CL', 'cs.AI', 'cs.LG']
Large language models (LLMs) have achieved impressive success on many benchmarks for mathematical reasoning. However, there is growing concern that some of this performance actually reflects dataset contamination, where data closely resembling benchmark questions leaks into the training data, instead of true reasoning ...
2024-05-01T05:52:05Z
2024 NeurIPS Camera Ready (Datasets and Benchmarks Track)
null
null
null
null
null
null
null
null
null
2,405.00675
Self-Play Preference Optimization for Language Model Alignment
['Yue Wu', 'Zhiqing Sun', 'Huizhuo Yuan', 'Kaixuan Ji', 'Yiming Yang', 'Quanquan Gu']
['cs.LG', 'cs.AI', 'cs.CL', 'stat.ML']
Standard reinforcement learning from human feedback (RLHF) approaches relying on parametric models like the Bradley-Terry model fall short in capturing the intransitivity and irrationality in human preferences. Recent advancements suggest that directly working with preference probabilities can yield a more accurate ref...
2024-05-01T17:59:20Z
27 pages, 4 figures, 5 tables
null
null
Self-Play Preference Optimization for Language Model Alignment
['Yue Wu', 'Zhiqing Sun', 'Huizhuo Yuan', 'Kaixuan Ji', 'Yiming Yang', 'Quanquan Gu']
2,024
International Conference on Learning Representations
145
59
['Computer Science', 'Mathematics']
2,405.0074
Modeling Caption Diversity in Contrastive Vision-Language Pretraining
['Samuel Lavoie', 'Polina Kirichenko', 'Mark Ibrahim', 'Mahmoud Assran', 'Andrew Gordon Wilson', 'Aaron Courville', 'Nicolas Ballas']
['cs.CV', 'cs.AI', 'cs.CL', 'cs.LG']
There are a thousand ways to caption an image. Contrastive Language Pretraining (CLIP) on the other hand, works by mapping an image and its caption to a single vector -- limiting how well CLIP-like models can represent the diverse ways to describe an image. In this work, we introduce Llip, Latent Language Image Pretrai...
2024-04-30T01:19:18Z
14 pages, 8 figures, 7 tables, to be published at ICML2024
null
null
Modeling Caption Diversity in Contrastive Vision-Language Pretraining
['Samuel Lavoie', 'P. Kirichenko', 'Mark Ibrahim', 'Mahmoud Assran', 'Andrew Gordon Wilson', 'Aaron Courville', 'Nicolas Ballas']
2,024
International Conference on Machine Learning
23
63
['Computer Science']
2,405.00828
WIBA: What Is Being Argued? A Comprehensive Approach to Argument Mining
['Arman Irani', 'Ju Yeon Park', 'Kevin Esterling', 'Michalis Faloutsos']
['cs.CL']
We propose WIBA, a novel framework and suite of methods that enable the comprehensive understanding of "What Is Being Argued" across contexts. Our approach develops a comprehensive framework that detects: (a) the existence, (b) the topic, and (c) the stance of an argument, correctly accounting for the logical dependenc...
2024-05-01T19:31:13Z
8 pages, 2 figures, submitted to The 16th International Conference on Advances in Social Networks Analysis and Mining (ASONAM) '24
null
null
null
null
null
null
null
null
null
2,405.00934
Benchmarking Representations for Speech, Music, and Acoustic Events
['Moreno La Quatra', 'Alkis Koudounas', 'Lorenzo Vaiani', 'Elena Baralis', 'Luca Cagliero', 'Paolo Garza', 'Sabato Marco Siniscalchi']
['eess.AS', 'cs.LG', 'cs.SD']
Limited diversity in standardized benchmarks for evaluating audio representation learning (ARL) methods may hinder systematic comparison of current methods' capabilities. We present ARCH, a comprehensive benchmark for evaluating ARL methods on diverse audio classification domains, covering acoustic events, music, and s...
2024-05-02T01:24:53Z
null
null
10.1109/ICASSPW62465.2024.10625960
Benchmarking Representations for Speech, Music, and Acoustic Events
['Moreno La Quatra', 'Alkis Koudounas', 'Lorenzo Vaiani', 'Elena Baralis', 'Luca Cagliero', 'Paolo Garza', 'Sabato Marco Siniscalchi']
2,024
2024 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW)
13
36
['Computer Science', 'Engineering']
2,405.00977
Distillation for Multilingual Information Retrieval
['Eugene Yang', 'Dawn Lawrie', 'James Mayfield']
['cs.IR', 'cs.CL']
Recent work in cross-language information retrieval (CLIR), where queries and documents are in different languages, has shown the benefit of the Translate-Distill framework that trains a cross-language neural dual-encoder model using translation and distillation. However, Translate-Distill only supports a single docume...
2024-05-02T03:30:03Z
6 pages, 1 figure, accepted at SIGIR 2024 as short paper
null
10.1145/3626772.3657955
null
null
null
null
null
null
null
2,405.00997
The IgboAPI Dataset: Empowering Igbo Language Technologies through Multi-dialectal Enrichment
['Chris Chinenye Emezue', 'Ifeoma Okoh', 'Chinedu Mbonu', 'Chiamaka Chukwuneke', 'Daisy Lal', 'Ignatius Ezeani', 'Paul Rayson', 'Ijemma Onwuzulike', 'Chukwuma Okeke', 'Gerald Nweya', 'Bright Ogbonna', 'Chukwuebuka Oraegbunam', 'Esther Chidinma Awo-Ndubuisi', 'Akudo Amarachukwu Osuagwu', 'Obioha Nmezi']
['cs.CL']
The Igbo language is facing a risk of becoming endangered, as indicated by a 2025 UNESCO study. This highlights the need to develop language technologies for Igbo to foster communication, learning and preservation. To create robust, impactful, and widely adopted language technologies for Igbo, it is essential to incorp...
2024-05-02T04:27:35Z
Accepted to the LREC-COLING 2024 conference
null
null
null
null
null
null
null
null
null
2,405.01413
MiniGPT-3D: Efficiently Aligning 3D Point Clouds with Large Language Models using 2D Priors
['Yuan Tang', 'Xu Han', 'Xianzhi Li', 'Qiao Yu', 'Yixue Hao', 'Long Hu', 'Min Chen']
['cs.CV', 'cs.AI', 'cs.CL', 'cs.LG']
Large 2D vision-language models (2D-LLMs) have gained significant attention by bridging Large Language Models (LLMs) with images using a simple projector. Inspired by their success, large 3D point cloud-language models (3D-LLMs) also integrate point clouds into LLMs. However, directly aligning point clouds with LLM req...
2024-05-02T16:04:30Z
17 pages, 9 figures
null
null
MiniGPT-3D: Efficiently Aligning 3D Point Clouds with Large Language Models using 2D Priors
['Yuan Tang', 'Xu Han', 'Xianzhi Li', 'Qiao Yu', 'Yixue Hao', 'Long Hu', 'Min Chen']
2,024
ACM Multimedia
20
60
['Computer Science']
2,405.0147
WildChat: 1M ChatGPT Interaction Logs in the Wild
['Wenting Zhao', 'Xiang Ren', 'Jack Hessel', 'Claire Cardie', 'Yejin Choi', 'Yuntian Deng']
['cs.CL']
Chatbots such as GPT-4 and ChatGPT are now serving millions of users. Despite their widespread use, there remains a lack of public datasets showcasing how these tools are used by a population of users in practice. To bridge this gap, we offered free access to ChatGPT for online users in exchange for their affirmative, ...
2024-05-02T17:00:02Z
accepted by ICLR 2024
null
null
null
null
null
null
null
null
null
2,405.01474
Understanding Figurative Meaning through Explainable Visual Entailment
['Arkadiy Saakyan', 'Shreyas Kulkarni', 'Tuhin Chakrabarty', 'Smaranda Muresan']
['cs.CL', 'cs.AI', 'cs.CV']
Large Vision-Language Models (VLMs) have demonstrated strong capabilities in tasks requiring a fine-grained understanding of literal meaning in images and text, such as visual question-answering or visual entailment. However, there has been little exploration of the capabilities of these models when presented with imag...
2024-05-02T17:07:25Z
NAACL 2025 Main Conference
null
null
Understanding Figurative Meaning through Explainable Visual Entailment
['Arkadiy Saakyan', 'Shreyas Kulkarni', 'Tuhin Chakrabarty', 'S. Muresan']
2,024
North American Chapter of the Association for Computational Linguistics
3
65
['Computer Science']
2,405.01481
NeMo-Aligner: Scalable Toolkit for Efficient Model Alignment
['Gerald Shen', 'Zhilin Wang', 'Olivier Delalleau', 'Jiaqi Zeng', 'Yi Dong', 'Daniel Egert', 'Shengyang Sun', 'Jimmy Zhang', 'Sahil Jain', 'Ali Taghibakhshi', 'Markel Sanz Ausin', 'Ashwath Aithal', 'Oleksii Kuchaiev']
['cs.CL', 'cs.AI', 'cs.LG']
Aligning Large Language Models (LLMs) with human values and preferences is essential for making them helpful and safe. However, building efficient tools to perform alignment can be challenging, especially for the largest and most competent LLMs which often contain tens or hundreds of billions of parameters. We create N...
2024-05-02T17:13:40Z
16 pages, 4 figures, Accepted to COLM 2024
null
null
NeMo-Aligner: Scalable Toolkit for Efficient Model Alignment
['Gerald Shen', 'Zhilin Wang', 'Olivier Delalleau', 'Jiaqi Zeng', 'Yi Dong', 'Daniel Egert', 'Shengyang Sun', 'Jimmy Zhang', 'Sahil Jain', 'Ali Taghibakhshi', 'Markel Sanz Ausin', 'Ashwath Aithal', 'Oleksii Kuchaiev']
2,024
arXiv.org
15
38
['Computer Science']
2,405.01483
MANTIS: Interleaved Multi-Image Instruction Tuning
['Dongfu Jiang', 'Xuan He', 'Huaye Zeng', 'Cong Wei', 'Max Ku', 'Qian Liu', 'Wenhu Chen']
['cs.CV', 'cs.AI', 'cs.CL']
Large multimodal models (LMMs) have shown great results in single-image vision language tasks. However, their abilities to solve multi-image visual language tasks is yet to be improved. The existing LMMs like OpenFlamingo, Emu2, and Idefics gain their multi-image ability through pre-training on hundreds of millions of ...
2024-05-02T17:14:57Z
13 pages, 3 figures, 13 tables
Transactions on Machine Learning Research 2024
null
MANTIS: Interleaved Multi-Image Instruction Tuning
['Dongfu Jiang', 'Xuan He', 'Huaye Zeng', 'Cong Wei', 'Max W.F. Ku', 'Qian Liu', 'Wenhu Chen']
2,024
Trans. Mach. Learn. Res.
125
72
['Computer Science']
2,405.01535
Prometheus 2: An Open Source Language Model Specialized in Evaluating Other Language Models
['Seungone Kim', 'Juyoung Suk', 'Shayne Longpre', 'Bill Yuchen Lin', 'Jamin Shin', 'Sean Welleck', 'Graham Neubig', 'Moontae Lee', 'Kyungjae Lee', 'Minjoon Seo']
['cs.CL']
Proprietary LMs such as GPT-4 are often employed to assess the quality of responses from various LMs. However, concerns including transparency, controllability, and affordability strongly motivate the development of open-source LMs specialized in evaluations. On the other hand, existing open evaluator LMs exhibit criti...
2024-05-02T17:59:35Z
EMNLP 2024 (Main Conference)
null
null
Prometheus 2: An Open Source Language Model Specialized in Evaluating Other Language Models
['Seungone Kim', 'Juyoung Suk', 'Shayne Longpre', 'Bill Yuchen Lin', 'Jamin Shin', 'S. Welleck', 'Graham Neubig', 'Moontae Lee', 'Kyungjae Lee', 'Minjoon Seo']
2,024
Conference on Empirical Methods in Natural Language Processing
205
45
['Computer Science']
2,405.01886
Aloe: A Family of Fine-tuned Open Healthcare LLMs
['Ashwin Kumar Gururajan', 'Enrique Lopez-Cuena', 'Jordi Bayarri-Planas', 'Adrian Tormos', 'Daniel Hinjos', 'Pablo Bernabeu-Perez', 'Anna Arias-Duart', 'Pablo Agustin Martin-Torres', 'Lucia Urcelay-Ganzabal', 'Marta Gonzalez-Mallo', 'Sergio Alvarez-Napagao', 'Eduard Ayguadé-Parra', 'Ulises Cortés Dario Garcia-Gasulla']
['cs.CL', 'cs.AI']
As the capabilities of Large Language Models (LLMs) in healthcare and medicine continue to advance, there is a growing need for competitive open-source models that can safeguard public interest. With the increasing availability of highly competitive open base models, the impact of continued pre-training is increasingly...
2024-05-03T07:14:07Z
Five appendix
null
null
null
null
null
null
null
null
null
2,405.01924
Semi-Parametric Retrieval via Binary Bag-of-Tokens Index
['Jiawei Zhou', 'Li Dong', 'Furu Wei', 'Lei Chen']
['cs.CL', 'cs.AI', 'cs.IR']
Information retrieval has transitioned from standalone systems into essential components across broader applications, with indexing efficiency, cost-effectiveness, and freshness becoming increasingly critical yet often overlooked. In this paper, we introduce SemI-parametric Disentangled Retrieval (SiDR), a bi-encoder r...
2024-05-03T08:34:13Z
null
null
null
null
null
null
null
null
null
null
2,405.02246
What matters when building vision-language models?
['Hugo Laurençon', 'Léo Tronchon', 'Matthieu Cord', 'Victor Sanh']
['cs.CV', 'cs.AI']
The growing interest in vision-language models (VLMs) has been driven by improvements in large language models and vision transformers. Despite the abundance of literature on this subject, we observe that critical decisions regarding the design of VLMs are often not justified. We argue that these unsupported decisions ...
2024-05-03T17:00:00Z
null
null
null
What matters when building vision-language models?
['Hugo Laurençon', 'Léo Tronchon', 'Matthieu Cord', 'Victor Sanh']
2,024
Neural Information Processing Systems
177
156
['Computer Science']
2,405.02296
Möbius Transform for Mitigating Perspective Distortions in Representation Learning
['Prakash Chandra Chhipa', 'Meenakshi Subhash Chippa', 'Kanjar De', 'Rajkumar Saini', 'Marcus Liwicki', 'Mubarak Shah']
['cs.CV']
Perspective distortion (PD) causes unprecedented changes in shape, size, orientation, angles, and other spatial relationships of visual concepts in images. Precisely estimating camera intrinsic and extrinsic parameters is a challenging task that prevents synthesizing perspective distortion. Non-availability of dedicate...
2024-03-07T15:39:00Z
Accepted to European Conference on Computer Vision(ECCV2024). project page- https://prakashchhipa.github.io/projects/mpd
null
null
Möbius Transform for Mitigating Perspective Distortions in Representation Learning
['Prakash Chandra Chhipa', 'Meenakshi Subhash Chippa', 'Kanjar De', 'Rajkumar Saini', 'Marcus Liwicki', 'Mubarak Shah']
2,024
European Conference on Computer Vision
1
64
['Computer Science']
2,405.0273
U-DiTs: Downsample Tokens in U-Shaped Diffusion Transformers
['Yuchuan Tian', 'Zhijun Tu', 'Hanting Chen', 'Jie Hu', 'Chao Xu', 'Yunhe Wang']
['cs.CV']
Diffusion Transformers (DiTs) introduce the transformer architecture to diffusion tasks for latent-space image generation. With an isotropic architecture that chains a series of transformer blocks, DiTs demonstrate competitive performance and good scalability; but meanwhile, the abandonment of U-Net by DiTs and their f...
2024-05-04T18:27:29Z
12 pages, 5 figures
NeurIPS 2024 Poster
null
null
null
null
null
null
null
null
2,405.03162
Advancing Multimodal Medical Capabilities of Gemini
['Lin Yang', 'Shawn Xu', 'Andrew Sellergren', 'Timo Kohlberger', 'Yuchen Zhou', 'Ira Ktena', 'Atilla Kiraly', 'Faruk Ahmed', 'Farhad Hormozdiari', 'Tiam Jaroensri', 'Eric Wang', 'Ellery Wulczyn', 'Fayaz Jamil', 'Theo Guidroz', 'Chuck Lau', 'Siyuan Qiao', 'Yun Liu', 'Akshay Goel', 'Kendall Park', 'Arnav Agharwal', 'Nick...
['cs.CV', 'cs.AI', 'cs.CL', 'cs.LG']
Many clinical tasks require an understanding of specialized data, such as medical images and genomics, which is not typically found in general-purpose large multimodal models. Building upon Gemini's multimodal models, we develop several models within the new Med-Gemini family that inherit core capabilities of Gemini an...
2024-05-06T04:44:22Z
null
null
null
null
null
null
null
null
null
null
2,405.03328
Enhancing Spatiotemporal Disease Progression Models via Latent Diffusion and Prior Knowledge
['Lemuel Puglisi', 'Daniel C. Alexander', 'Daniele Ravì']
['cs.CV', 'cs.AI']
In this work, we introduce Brain Latent Progression (BrLP), a novel spatiotemporal disease progression model based on latent diffusion. BrLP is designed to predict the evolution of diseases at the individual level on 3D brain MRIs. Existing deep generative models developed for this task are primarily data-driven and fa...
2024-05-06T10:07:16Z
null
null
10.1007/978-3-031-72069-7_17
null
null
null
null
null
null
null
2,405.0352
Is Sora a World Simulator? A Comprehensive Survey on General World Models and Beyond
['Zheng Zhu', 'Xiaofeng Wang', 'Wangbo Zhao', 'Chen Min', 'Nianchen Deng', 'Min Dou', 'Yuqi Wang', 'Botian Shi', 'Kai Wang', 'Chi Zhang', 'Yang You', 'Zhaoxiang Zhang', 'Dawei Zhao', 'Liang Xiao', 'Jian Zhao', 'Jiwen Lu', 'Guan Huang']
['cs.CV']
General world models represent a crucial pathway toward achieving Artificial General Intelligence (AGI), serving as the cornerstone for various applications ranging from virtual environments to decision-making systems. Recently, the emergence of the Sora model has attained significant attention due to its remarkable si...
2024-05-06T14:37:07Z
This survey will be regularly updated at: https://github.com/GigaAI-research/General-World-Models-Survey
null
null
null
null
null
null
null
null
null
2,405.03548
MAmmoTH2: Scaling Instructions from the Web
['Xiang Yue', 'Tuney Zheng', 'Ge Zhang', 'Wenhu Chen']
['cs.CL']
Instruction tuning improves the reasoning abilities of large language models (LLMs), with data quality and scalability being the crucial factors. Most instruction tuning data come from human crowd-sourcing or GPT-4 distillation. We propose a paradigm to efficiently harvest 10 million naturally existing instruction data...
2024-05-06T15:11:38Z
null
null
null
null
null
null
null
null
null
null
2,405.03553
AlphaMath Almost Zero: Process Supervision without Process
['Guoxin Chen', 'Minpeng Liao', 'Chengxi Li', 'Kai Fan']
['cs.CL', 'cs.AI']
Although recent advancements in large language models (LLMs) have significantly improved their performance on various tasks, they still face challenges with complex and symbolic multi-step reasoning, particularly in mathematical reasoning. To bolster the mathematical reasoning capabilities of LLMs, most existing effort...
2024-05-06T15:20:30Z
Camera ready version for NeurIPS 2024
null
null
null
null
null
null
null
null
null
2,405.03594
Enabling High-Sparsity Foundational Llama Models with Efficient Pretraining and Deployment
['Abhinav Agarwalla', 'Abhay Gupta', 'Alexandre Marques', 'Shubhra Pandit', 'Michael Goin', 'Eldar Kurtic', 'Kevin Leong', 'Tuan Nguyen', 'Mahmoud Salem', 'Dan Alistarh', 'Sean Lie', 'Mark Kurtz']
['cs.CL', 'cs.AI']
Large language models (LLMs) have revolutionized Natural Language Processing (NLP), but their size creates computational bottlenecks. We introduce a novel approach to create accurate, sparse foundational versions of performant LLMs that achieve full accuracy recovery for fine-tuning tasks at up to 70% sparsity. We achi...
2024-05-06T16:03:32Z
null
null
null
null
null
null
null
null
null
null
2,405.04299
ViewFormer: Exploring Spatiotemporal Modeling for Multi-View 3D Occupancy Perception via View-Guided Transformers
['Jinke Li', 'Xiao He', 'Chonghua Zhou', 'Xiaoqiang Cheng', 'Yang Wen', 'Dan Zhang']
['cs.CV']
3D occupancy, an advanced perception technology for driving scenarios, represents the entire scene without distinguishing between foreground and background by quantifying the physical space into a grid map. The widely adopted projection-first deformable attention, efficient in transforming image features into 3D repres...
2024-05-07T13:15:07Z
null
null
null
ViewFormer: Exploring Spatiotemporal Modeling for Multi-View 3D Occupancy Perception via View-Guided Transformers
['Jinke Li', 'Xiao He', 'Chonghua Zhou', 'Xiaoqiang Cheng', 'Yang Wen', 'Dan Zhang']
2,024
European Conference on Computer Vision
16
42
['Computer Science']
2,405.04324
Granite Code Models: A Family of Open Foundation Models for Code Intelligence
['Mayank Mishra', 'Matt Stallone', 'Gaoyuan Zhang', 'Yikang Shen', 'Aditya Prasad', 'Adriana Meza Soria', 'Michele Merler', 'Parameswaran Selvam', 'Saptha Surendran', 'Shivdeep Singh', 'Manish Sethi', 'Xuan-Hong Dang', 'Pengyuan Li', 'Kun-Lung Wu', 'Syed Zawad', 'Andrew Coleman', 'Matthew White', 'Mark Lewis', 'Raju Pa...
['cs.AI', 'cs.CL', 'cs.SE']
Large Language Models (LLMs) trained on code are revolutionizing the software development process. Increasingly, code LLMs are being integrated into software development environments to improve the productivity of human programmers, and LLM-based agents are beginning to show promise for handling complex tasks autonomou...
2024-05-07T13:50:40Z
Corresponding Authors: Rameswar Panda, Ruchir Puri; Equal Contributors: Mayank Mishra, Matt Stallone, Gaoyuan Zhang
null
null
null
null
null
null
null
null
null
2,405.04434
DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model
['DeepSeek-AI', 'Aixin Liu', 'Bei Feng', 'Bin Wang', 'Bingxuan Wang', 'Bo Liu', 'Chenggang Zhao', 'Chengqi Dengr', 'Chong Ruan', 'Damai Dai', 'Daya Guo', 'Dejian Yang', 'Deli Chen', 'Dongjie Ji', 'Erhang Li', 'Fangyun Lin', 'Fuli Luo', 'Guangbo Hao', 'Guanting Chen', 'Guowei Li', 'H. Zhang', 'Hanwei Xu', 'Hao Yang', 'H...
['cs.CL', 'cs.AI']
We present DeepSeek-V2, a strong Mixture-of-Experts (MoE) language model characterized by economical training and efficient inference. It comprises 236B total parameters, of which 21B are activated for each token, and supports a context length of 128K tokens. DeepSeek-V2 adopts innovative architectures including Multi-...
2024-05-07T15:56:43Z
null
null
null
null
null
null
null
null
null
null
2,405.04517
xLSTM: Extended Long Short-Term Memory
['Maximilian Beck', 'Korbinian Pöppel', 'Markus Spanring', 'Andreas Auer', 'Oleksandra Prudnikova', 'Michael Kopp', 'Günter Klambauer', 'Johannes Brandstetter', 'Sepp Hochreiter']
['cs.LG', 'cs.AI', 'stat.ML']
In the 1990s, the constant error carousel and gating were introduced as the central ideas of the Long Short-Term Memory (LSTM). Since then, LSTMs have stood the test of time and contributed to numerous deep learning success stories, in particular they constituted the first Large Language Models (LLMs). However, the adv...
2024-05-07T17:50:21Z
Code available at https://github.com/NX-AI/xlstm
null
null
null
null
null
null
null
null
null
2,405.04532
QServe: W4A8KV4 Quantization and System Co-design for Efficient LLM Serving
['Yujun Lin', 'Haotian Tang', 'Shang Yang', 'Zhekai Zhang', 'Guangxuan Xiao', 'Chuang Gan', 'Song Han']
['cs.CL', 'cs.AI', 'cs.LG', 'cs.PF']
Quantization can accelerate large language model (LLM) inference. Going beyond INT8 quantization, the research community is actively exploring even lower precision, such as INT4. Nonetheless, state-of-the-art INT4 quantization techniques only accelerate low-batch, edge LLM inference, failing to deliver performance gain...
2024-05-07T17:59:30Z
The first three authors contribute equally to this project and are listed in the alphabetical order. Yujun Lin leads the quantization algorithm, Haotian Tang and Shang Yang lead the GPU kernels and the serving system. Code is available at https://github.com/mit-han-lab/omniserve
null
null
QServe: W4A8KV4 Quantization and System Co-design for Efficient LLM Serving
['Yujun Lin', 'Haotian Tang', 'Shang Yang', 'Zhekai Zhang', 'Guangxuan Xiao', 'Chuang Gan', 'Song Han']
2,024
arXiv.org
98
43
['Computer Science']
2,405.0476
Large Language Models for Cyber Security: A Systematic Literature Review
['Hanxiang Xu', 'Shenao Wang', 'Ningke Li', 'Kailong Wang', 'Yanjie Zhao', 'Kai Chen', 'Ting Yu', 'Yang Liu', 'Haoyu Wang']
['cs.CR', 'cs.AI']
The rapid advancement of Large Language Models (LLMs) has opened up new opportunities for leveraging artificial intelligence in various domains, including cybersecurity. As the volume and sophistication of cyber threats continue to grow, there is an increasing need for intelligent systems that can automatically detect ...
2024-05-08T02:09:17Z
56 pages,6 figures
null
null
Large Language Models for Cyber Security: A Systematic Literature Review
['Hanxiang Xu', 'Shenao Wang', 'Ningke Li', 'Kailong Wang', 'Yanjie Zhao', 'Kai Chen', 'Ting Yu', 'Yang Liu', 'Haoyu Wang']
2,024
arXiv.org
43
230
['Computer Science']
2,405.04828
ChuXin: 1.6B Technical Report
['Xiaomin Zhuang', 'Yufan Jiang', 'Qiaozhi He', 'Zhihua Wu']
['cs.CL']
In this report, we present ChuXin, an entirely open-source language model with a size of 1.6 billion parameters. Unlike the majority of works that only open-sourced the model weights and architecture, we have made everything needed to train a model available, including the training data, the training process, and the e...
2024-05-08T05:54:44Z
Technical Report
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2,405.04912
GP-MoLFormer: A Foundation Model For Molecular Generation
['Jerret Ross', 'Brian Belgodere', 'Samuel C. Hoffman', 'Vijil Chenthamarakshan', 'Jiri Navratil', 'Youssef Mroueh', 'Payel Das']
['q-bio.BM', 'cs.LG', 'physics.chem-ph']
Transformer-based models trained on large and general purpose datasets consisting of molecular strings have recently emerged as a powerful tool for successfully modeling various structure-property relations. Inspired by this success, we extend the paradigm of training chemical language transformers on large-scale chemi...
2024-04-04T16:20:06Z
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2,405.05008
ADELIE: Aligning Large Language Models on Information Extraction
['Yunjia Qi', 'Hao Peng', 'Xiaozhi Wang', 'Bin Xu', 'Lei Hou', 'Juanzi Li']
['cs.CL']
Large language models (LLMs) usually fall short on information extraction (IE) tasks and struggle to follow the complex instructions of IE tasks. This primarily arises from LLMs not being aligned with humans, as mainstream alignment datasets typically do not include IE data. In this paper, we introduce ADELIE (Aligning...
2024-05-08T12:24:52Z
Accepted at EMNLP 2024. Camera-ready version
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