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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2,405.05241 | BenthicNet: A global compilation of seafloor images for deep learning
applications | ['Scott C. Lowe', 'Benjamin Misiuk', 'Isaac Xu', 'Shakhboz Abdulazizov', 'Amit R. Baroi', 'Alex C. Bastos', 'Merlin Best', 'Vicki Ferrini', 'Ariell Friedman', 'Deborah Hart', 'Ove Hoegh-Guldberg', 'Daniel Ierodiaconou', 'Julia Mackin-McLaughlin', 'Kathryn Markey', 'Pedro S. Menandro', 'Jacquomo Monk', 'Shreya Nemani', ... | ['cs.CV', 'cs.LG'] | Advances in underwater imaging enable collection of extensive seafloor image
datasets necessary for monitoring important benthic ecosystems. The ability to
collect seafloor imagery has outpaced our capacity to analyze it, hindering
mobilization of this crucial environmental information. Machine learning
approaches prov... | 2024-05-08T17:37:57Z | null | Sci Data 12, 230 (2025) | 10.1038/s41597-025-04491-1 | null | null | null | null | null | null | null |
2,405.05374 | Arctic-Embed: Scalable, Efficient, and Accurate Text Embedding Models | ['Luke Merrick', 'Danmei Xu', 'Gaurav Nuti', 'Daniel Campos'] | ['cs.CL', 'cs.AI', 'cs.IR'] | This report describes the training dataset creation and recipe behind the
family of \texttt{arctic-embed} text embedding models (a set of five models
ranging from 22 to 334 million parameters with weights open-sourced under an
Apache-2 license). At the time of their release, each model achieved
state-of-the-art retriev... | 2024-05-08T19:05:18Z | 17 pages, 11 Figures, 9 tables | null | null | null | null | null | null | null | null | null |
2,405.05376 | Kreyòl-MT: Building MT for Latin American, Caribbean and Colonial
African Creole Languages | ['Nathaniel R. Robinson', 'Raj Dabre', 'Ammon Shurtz', 'Rasul Dent', 'Onenamiyi Onesi', 'Claire Bizon Monroc', 'Loïc Grobol', 'Hasan Muhammad', 'Ashi Garg', 'Naome A. Etori', 'Vijay Murari Tiyyala', 'Olanrewaju Samuel', 'Matthew Dean Stutzman', 'Bismarck Bamfo Odoom', 'Sanjeev Khudanpur', 'Stephen D. Richardson', 'Kent... | ['cs.CL'] | A majority of language technologies are tailored for a small number of
high-resource languages, while relatively many low-resource languages are
neglected. One such group, Creole languages, have long been marginalized in
academic study, though their speakers could benefit from machine translation
(MT). These languages ... | 2024-05-08T19:06:19Z | NAACL 2024 | null | null | null | null | null | null | null | null | null |
2,405.05378 | "They are uncultured": Unveiling Covert Harms and Social Threats in LLM
Generated Conversations | ['Preetam Prabhu Srikar Dammu', 'Hayoung Jung', 'Anjali Singh', 'Monojit Choudhury', 'Tanushree Mitra'] | ['cs.CL', 'cs.AI', 'cs.CY', 'cs.HC', 'cs.LG'] | Large language models (LLMs) have emerged as an integral part of modern
societies, powering user-facing applications such as personal assistants and
enterprise applications like recruitment tools. Despite their utility, research
indicates that LLMs perpetuate systemic biases. Yet, prior works on LLM harms
predominantly... | 2024-05-08T19:08:45Z | null | null | null | null | null | null | null | null | null | null |
2,405.05852 | Pre-trained Text-to-Image Diffusion Models Are Versatile Representation
Learners for Control | ['Gunshi Gupta', 'Karmesh Yadav', 'Yarin Gal', 'Dhruv Batra', 'Zsolt Kira', 'Cong Lu', 'Tim G. J. Rudner'] | ['cs.CV', 'cs.AI', 'cs.CL', 'cs.LG', 'cs.RO', 'stat.ML'] | Embodied AI agents require a fine-grained understanding of the physical world
mediated through visual and language inputs. Such capabilities are difficult to
learn solely from task-specific data. This has led to the emergence of
pre-trained vision-language models as a tool for transferring representations
learned from ... | 2024-05-09T15:39:54Z | null | null | null | null | null | null | null | null | null | null |
2,405.05945 | Lumina-T2X: Transforming Text into Any Modality, Resolution, and
Duration via Flow-based Large Diffusion Transformers | ['Peng Gao', 'Le Zhuo', 'Dongyang Liu', 'Ruoyi Du', 'Xu Luo', 'Longtian Qiu', 'Yuhang Zhang', 'Chen Lin', 'Rongjie Huang', 'Shijie Geng', 'Renrui Zhang', 'Junlin Xi', 'Wenqi Shao', 'Zhengkai Jiang', 'Tianshuo Yang', 'Weicai Ye', 'He Tong', 'Jingwen He', 'Yu Qiao', 'Hongsheng Li'] | ['cs.CV'] | Sora unveils the potential of scaling Diffusion Transformer for generating
photorealistic images and videos at arbitrary resolutions, aspect ratios, and
durations, yet it still lacks sufficient implementation details. In this
technical report, we introduce the Lumina-T2X family - a series of Flow-based
Large Diffusion ... | 2024-05-09T17:35:16Z | Technical Report; Code at: https://github.com/Alpha-VLLM/Lumina-T2X | null | null | Lumina-T2X: Transforming Text into Any Modality, Resolution, and Duration via Flow-based Large Diffusion Transformers | ['Peng Gao', 'Le Zhuo', 'Ziyi Lin', 'Chris Liu', 'Junsong Chen', 'Ruoyi Du', 'Enze Xie', 'Xu Luo', 'Longtian Qiu', 'Yuhang Zhang', 'Chen Lin', 'Rongjie Huang', 'Shijie Geng', 'Renrui Zhang', 'Junlin Xi', 'Wenqi Shao', 'Zhengkai Jiang', 'Tianshuo Yang', 'Weicai Ye', 'He Tong', 'Jingwen He', 'Y. Qiao', 'Hongsheng Li'] | 2,024 | arXiv.org | 91 | 164 | ['Computer Science'] |
2,405.05999 | LLMPot: Dynamically Configured LLM-based Honeypot for Industrial
Protocol and Physical Process Emulation | ['Christoforos Vasilatos', 'Dunia J. Mahboobeh', 'Hithem Lamri', 'Manaar Alam', 'Michail Maniatakos'] | ['cs.CR', 'cs.LG'] | Industrial Control Systems (ICS) are extensively used in critical
infrastructures ensuring efficient, reliable, and continuous operations.
However, their increasing connectivity and addition of advanced features make
them vulnerable to cyber threats, potentially leading to severe disruptions in
essential services. In t... | 2024-05-09T09:37:22Z | null | null | null | LLMPot: Dynamically Configured LLM-based Honeypot for Industrial Protocol and Physical Process Emulation | ['Christoforos Vasilatos', 'D. Mahboobeh', 'Hithem Lamri', 'Manaar Alam', 'Michail Maniatakos'] | 2,024 | null | 4 | 71 | ['Computer Science'] |
2,405.06067 | HMT: Hierarchical Memory Transformer for Efficient Long Context Language
Processing | ['Zifan He', 'Yingqi Cao', 'Zongyue Qin', 'Neha Prakriya', 'Yizhou Sun', 'Jason Cong'] | ['cs.CL', 'cs.LG'] | Transformer-based large language models (LLM) have been widely used in
language processing applications. However, due to the memory constraints of the
devices, most of them restrict the context window. Even though recurrent models
in previous works can memorize past tokens to enable unlimited context and
maintain effec... | 2024-05-09T19:32:49Z | NAACL 2025 Main Conference | null | null | null | null | null | null | null | null | null |
2,405.06239 | SaudiBERT: A Large Language Model Pretrained on Saudi Dialect Corpora | ['Faisal Qarah'] | ['cs.CL', 'cs.AI'] | In this paper, we introduce SaudiBERT, a monodialect Arabic language model
pretrained exclusively on Saudi dialectal text. To demonstrate the model's
effectiveness, we compared SaudiBERT with six different multidialect Arabic
language models across 11 evaluation datasets, which are divided into two
groups: sentiment an... | 2024-05-10T04:22:54Z | null | null | null | null | null | null | null | null | null | null |
2,405.06461 | SketchDream: Sketch-based Text-to-3D Generation and Editing | ['Feng-Lin Liu', 'Hongbo Fu', 'Yu-Kun Lai', 'Lin Gao'] | ['cs.GR'] | Existing text-based 3D generation methods generate attractive results but
lack detailed geometry control. Sketches, known for their conciseness and
expressiveness, have contributed to intuitive 3D modeling but are confined to
producing texture-less mesh models within predefined categories. Integrating
sketch and text s... | 2024-05-10T13:13:46Z | null | null | null | null | null | null | null | null | null | null |
2,405.0664 | Linearizing Large Language Models | ['Jean Mercat', 'Igor Vasiljevic', 'Sedrick Keh', 'Kushal Arora', 'Achal Dave', 'Adrien Gaidon', 'Thomas Kollar'] | ['cs.CL'] | Linear transformers have emerged as a subquadratic-time alternative to
softmax attention and have garnered significant interest due to their
fixed-size recurrent state that lowers inference cost. However, their original
formulation suffers from poor scaling and underperforms compute-matched
transformers. Recent linear ... | 2024-05-10T17:59:08Z | null | null | null | null | null | null | null | null | null | null |
2,405.06694 | SUTRA: Scalable Multilingual Language Model Architecture | ['Abhijit Bendale', 'Michael Sapienza', 'Steven Ripplinger', 'Simon Gibbs', 'Jaewon Lee', 'Pranav Mistry'] | ['cs.CL', 'cs.AI'] | In this paper, we introduce SUTRA, multilingual Large Language Model
architecture capable of understanding, reasoning, and generating text in over
50 languages. SUTRA's design uniquely decouples core conceptual understanding
from language-specific processing, which facilitates scalable and efficient
multilingual alignm... | 2024-05-07T20:11:44Z | null | null | null | SUTRA: Scalable Multilingual Language Model Architecture | ['Abhijit Bendale', 'Michael Sapienza', 'Steven Ripplinger', 'Simon Gibbs', 'Jaewon Lee', 'Pranav Mistry'] | 2,024 | arXiv.org | 5 | 38 | ['Computer Science'] |
2,405.06932 | Piccolo2: General Text Embedding with Multi-task Hybrid Loss Training | ['Junqin Huang', 'Zhongjie Hu', 'Zihao Jing', 'Mengya Gao', 'Yichao Wu'] | ['cs.CL', 'cs.AI'] | In this report, we introduce Piccolo2, an embedding model that surpasses
other models in the comprehensive evaluation over 6 tasks on CMTEB benchmark,
setting a new state-of-the-art. Piccolo2 primarily leverages an efficient
multi-task hybrid loss training approach, effectively harnessing textual data
and labels from d... | 2024-05-11T06:32:08Z | tech report | null | null | Piccolo2: General Text Embedding with Multi-task Hybrid Loss Training | ['Junqin Huang', 'Zhongjie Hu', 'Zihao Jing', 'Mengya Gao', 'Yichao Wu'] | 2,024 | arXiv.org | 6 | 33 | ['Computer Science'] |
2,405.07101 | Advanced Natural-based interaction for the ITAlian language:
LLaMAntino-3-ANITA | ['Marco Polignano', 'Pierpaolo Basile', 'Giovanni Semeraro'] | ['cs.CL', 'cs.AI'] | In the pursuit of advancing natural language processing for the Italian
language, we introduce a state-of-the-art Large Language Model (LLM) based on
the novel Meta LLaMA-3 model: LLaMAntino-3-ANITA-8B-Inst-DPO-ITA. We fine-tuned
the original 8B parameters instruction tuned model using the Supervised
Fine-tuning (SFT) ... | 2024-05-11T22:02:55Z | null | null | null | Advanced Natural-based interaction for the ITAlian language: LLaMAntino-3-ANITA | ['Marco Polignano', 'Pierpaolo Basile', 'Giovanni Semeraro'] | 2,024 | arXiv.org | 20 | 29 | ['Computer Science'] |
2,405.07615 | ViWikiFC: Fact-Checking for Vietnamese Wikipedia-Based Textual Knowledge
Source | ['Hung Tuan Le', 'Long Truong To', 'Manh Trong Nguyen', 'Kiet Van Nguyen'] | ['cs.CL'] | Fact-checking is essential due to the explosion of misinformation in the
media ecosystem. Although false information exists in every language and
country, most research to solve the problem mainly concentrated on huge
communities like English and Chinese. Low-resource languages like Vietnamese
are necessary to explore ... | 2024-05-13T10:24:05Z | null | null | null | null | null | null | null | null | null | null |
2,405.07703 | OpenLLM-Ro -- Technical Report on Open-source Romanian LLMs | ['Mihai Masala', 'Denis C. Ilie-Ablachim', 'Dragos Corlatescu', 'Miruna Zavelca', 'Marius Leordeanu', 'Horia Velicu', 'Marius Popescu', 'Mihai Dascalu', 'Traian Rebedea'] | ['cs.CL'] | In recent years, Large Language Models (LLMs) have achieved almost human-like
performance on various tasks. While some LLMs have been trained on multilingual
data, most of the training data is in English. Hence, their performance in
English greatly exceeds their performance in other languages. This document
presents ou... | 2024-05-13T12:46:11Z | null | null | null | null | null | null | null | null | null | null |
2,405.07719 | USP: A Unified Sequence Parallelism Approach for Long Context Generative
AI | ['Jiarui Fang', 'Shangchun Zhao'] | ['cs.LG', 'cs.AI'] | Sequence parallelism (SP), which divides the sequence dimension of input
tensors across multiple computational devices, is becoming key to unlocking the
long-context capabilities of generative AI models. This paper investigates the
state-of-the-art SP approaches, i.e. DeepSpeed-Ulysses and Ring-Attention, and
proposes ... | 2024-05-13T13:08:02Z | null | null | null | null | null | null | null | null | null | null |
2,405.07778 | A Comprehensive Analysis of Static Word Embeddings for Turkish | ['Karahan Sarıtaş', 'Cahid Arda Öz', 'Tunga Güngör'] | ['cs.CL', 'cs.AI'] | Word embeddings are fixed-length, dense and distributed word representations
that are used in natural language processing (NLP) applications. There are
basically two types of word embedding models which are non-contextual (static)
models and contextual models. The former method generates a single embedding
for a word r... | 2024-05-13T14:23:37Z | null | Expert Systems with Applications Volume 252, Part A, 15 October
2024, 124123 | 10.1016/j.eswa.2024.124123 | A Comprehensive Analysis of Static Word Embeddings for Turkish | ['Karahan Saritas', 'Cahid Arda Öz', 'Tunga Güngör'] | 2,024 | Expert systems with applications | 4 | 60 | ['Computer Science'] |
2,405.07813 | Localizing Task Information for Improved Model Merging and Compression | ['Ke Wang', 'Nikolaos Dimitriadis', 'Guillermo Ortiz-Jimenez', 'François Fleuret', 'Pascal Frossard'] | ['cs.LG', 'cs.CV'] | Model merging and task arithmetic have emerged as promising scalable
approaches to merge multiple single-task checkpoints to one multi-task model,
but their applicability is reduced by significant performance loss. Previous
works have linked these drops to interference in the weight space and erasure
of important task-... | 2024-05-13T14:54:37Z | Accepted ICML 2024; The first two authors contributed equally to this
work; Project website: https://tall-masks.github.io | null | null | null | null | null | null | null | null | null |
2,405.07863 | RLHF Workflow: From Reward Modeling to Online RLHF | ['Hanze Dong', 'Wei Xiong', 'Bo Pang', 'Haoxiang Wang', 'Han Zhao', 'Yingbo Zhou', 'Nan Jiang', 'Doyen Sahoo', 'Caiming Xiong', 'Tong Zhang'] | ['cs.LG', 'cs.AI', 'cs.CL', 'stat.ML'] | We present the workflow of Online Iterative Reinforcement Learning from Human
Feedback (RLHF) in this technical report, which is widely reported to
outperform its offline counterpart by a large margin in the recent large
language model (LLM) literature. However, existing open-source RLHF projects
are still largely conf... | 2024-05-13T15:50:39Z | Published in Transactions on Machine Learning Research (09/2024) | null | null | null | null | null | null | null | null | null |
2,405.07883 | Zero-Shot Tokenizer Transfer | ['Benjamin Minixhofer', 'Edoardo Maria Ponti', 'Ivan Vulić'] | ['cs.CL'] | Language models (LMs) are bound to their tokenizer, which maps raw text to a
sequence of vocabulary items (tokens). This restricts their flexibility: for
example, LMs trained primarily on English may still perform well in other
natural and programming languages, but have vastly decreased efficiency due to
their English... | 2024-05-13T16:17:10Z | null | null | null | null | null | null | null | null | null | null |
2,405.07913 | CTRLorALTer: Conditional LoRAdapter for Efficient 0-Shot Control &
Altering of T2I Models | ['Nick Stracke', 'Stefan Andreas Baumann', 'Joshua M. Susskind', 'Miguel Angel Bautista', 'Björn Ommer'] | ['cs.CV'] | Text-to-image generative models have become a prominent and powerful tool
that excels at generating high-resolution realistic images. However, guiding
the generative process of these models to consider detailed forms of
conditioning reflecting style and/or structure information remains an open
problem. In this paper, w... | 2024-05-13T16:46:44Z | for the project page and code, view
https://compvis.github.io/LoRAdapter/ | null | null | CTRLorALTer: Conditional LoRAdapter for Efficient 0-Shot Control & Altering of T2I Models | ['Nick Stracke', 'Stefan Andreas Baumann', 'J. Susskind', 'Miguel Angel Bautista', 'Bjorn Ommer'] | 2,024 | arXiv.org | 3 | 51 | ['Computer Science'] |
2,405.0792 | Rank-DistiLLM: Closing the Effectiveness Gap Between Cross-Encoders and
LLMs for Passage Re-Ranking | ['Ferdinand Schlatt', 'Maik Fröbe', 'Harrisen Scells', 'Shengyao Zhuang', 'Bevan Koopman', 'Guido Zuccon', 'Benno Stein', 'Martin Potthast', 'Matthias Hagen'] | ['cs.IR'] | Cross-encoders distilled from large language models (LLMs) are often more
effective re-rankers than cross-encoders fine-tuned on manually labeled data.
However, distilled models do not match the effectiveness of their teacher LLMs.
We hypothesize that this effectiveness gap is due to the fact that previous
work has not... | 2024-05-13T16:51:53Z | Accepted at ECIR'25 | null | 10.1007/978-3-031-88714-7_31 | Rank-DistiLLM: Closing the Effectiveness Gap Between Cross-Encoders and LLMs for Passage Re-ranking | ['Ferdinand Schlatt', 'Maik Frobe', 'Harrisen Scells', 'Shengyao Zhuang', 'B. Koopman', 'G. Zuccon', 'Benno Stein', 'Martin Potthast', 'Matthias Hagen'] | 2,024 | European Conference on Information Retrieval | 6 | 70 | ['Computer Science'] |
2,405.0794 | RAID: A Shared Benchmark for Robust Evaluation of Machine-Generated Text
Detectors | ['Liam Dugan', 'Alyssa Hwang', 'Filip Trhlik', 'Josh Magnus Ludan', 'Andrew Zhu', 'Hainiu Xu', 'Daphne Ippolito', 'Chris Callison-Burch'] | ['cs.CL', 'I.2.7'] | Many commercial and open-source models claim to detect machine-generated text
with extremely high accuracy (99% or more). However, very few of these
detectors are evaluated on shared benchmark datasets and even when they are,
the datasets used for evaluation are insufficiently challenging-lacking
variations in sampling... | 2024-05-13T17:15:14Z | ACL 2024 | null | null | RAID: A Shared Benchmark for Robust Evaluation of Machine-Generated Text Detectors | ['Liam Dugan', 'Alyssa Hwang', 'Filip Trhlik', 'Josh Magnus Ludan', 'Andrew Zhu', 'Hainiu Xu', 'Daphne Ippolito', 'Christopher Callison-Burch'] | 2,024 | Annual Meeting of the Association for Computational Linguistics | 52 | 94 | ['Computer Science'] |
2,405.0796 | AgentClinic: a multimodal agent benchmark to evaluate AI in simulated
clinical environments | ['Samuel Schmidgall', 'Rojin Ziaei', 'Carl Harris', 'Eduardo Reis', 'Jeffrey Jopling', 'Michael Moor'] | ['cs.HC', 'cs.CL'] | Evaluating large language models (LLM) in clinical scenarios is crucial to
assessing their potential clinical utility. Existing benchmarks rely heavily on
static question-answering, which does not accurately depict the complex,
sequential nature of clinical decision-making. Here, we introduce AgentClinic,
a multimodal ... | 2024-05-13T17:38:53Z | null | null | null | null | null | null | null | null | null | null |
2,405.07988 | MedVersa: A Generalist Foundation Model for Medical Image Interpretation | ['Hong-Yu Zhou', 'Julián Nicolás Acosta', 'Subathra Adithan', 'Suvrankar Datta', 'Eric J. Topol', 'Pranav Rajpurkar'] | ['cs.CV'] | Current medical AI systems are often limited to narrow applications,
hindering widespread adoption. We present MedVersa, a generalist foundation
model trained on tens of millions of compiled medical instances. MedVersa
unlocks generalist learning from multimodal inputs and outputs, representing
the first example of a g... | 2024-05-13T17:58:51Z | Technical study | null | null | MedVersa: A Generalist Foundation Model for Medical Image Interpretation | ['Hong-Yu Zhou', 'J. N. Acosta', 'Subathra Adithan', 'Suvrankar Datta', 'E. Topol', 'P. Rajpurkar'] | 2,024 | null | 29 | 0 | ['Computer Science'] |
2,405.07992 | MambaOut: Do We Really Need Mamba for Vision? | ['Weihao Yu', 'Xinchao Wang'] | ['cs.CV', 'cs.AI', 'cs.LG'] | Mamba, an architecture with RNN-like token mixer of state space model (SSM),
was recently introduced to address the quadratic complexity of the attention
mechanism and subsequently applied to vision tasks. Nevertheless, the
performance of Mamba for vision is often underwhelming when compared with
convolutional and atte... | 2024-05-13T17:59:56Z | Code: https://github.com/yuweihao/MambaOut | null | null | null | null | null | null | null | null | null |
2,405.08553 | Improving Transformers with Dynamically Composable Multi-Head Attention | ['Da Xiao', 'Qingye Meng', 'Shengping Li', 'Xingyuan Yuan'] | ['cs.LG', 'cs.CL'] | Multi-Head Attention (MHA) is a key component of Transformer. In MHA,
attention heads work independently, causing problems such as low-rank
bottleneck of attention score matrices and head redundancy. We propose
Dynamically Composable Multi-Head Attention (DCMHA), a parameter and
computation efficient attention architec... | 2024-05-14T12:41:11Z | Accepted to the 41st International Conference on Machine Learning
(ICML'24 oral) | null | null | null | null | null | null | null | null | null |
2,405.08748 | Hunyuan-DiT: A Powerful Multi-Resolution Diffusion Transformer with
Fine-Grained Chinese Understanding | ['Zhimin Li', 'Jianwei Zhang', 'Qin Lin', 'Jiangfeng Xiong', 'Yanxin Long', 'Xinchi Deng', 'Yingfang Zhang', 'Xingchao Liu', 'Minbin Huang', 'Zedong Xiao', 'Dayou Chen', 'Jiajun He', 'Jiahao Li', 'Wenyue Li', 'Chen Zhang', 'Rongwei Quan', 'Jianxiang Lu', 'Jiabin Huang', 'Xiaoyan Yuan', 'Xiaoxiao Zheng', 'Yixuan Li', 'J... | ['cs.CV'] | We present Hunyuan-DiT, a text-to-image diffusion transformer with
fine-grained understanding of both English and Chinese. To construct
Hunyuan-DiT, we carefully design the transformer structure, text encoder, and
positional encoding. We also build from scratch a whole data pipeline to update
and evaluate data for iter... | 2024-05-14T16:33:25Z | Project Page: https://dit.hunyuan.tencent.com/ | null | null | null | null | null | null | null | null | null |
2,405.09055 | A safety realignment framework via subspace-oriented model fusion for
large language models | ['Xin Yi', 'Shunfan Zheng', 'Linlin Wang', 'Xiaoling Wang', 'Liang He'] | ['cs.CL'] | The current safeguard mechanisms for large language models (LLMs) are indeed
susceptible to jailbreak attacks, making them inherently fragile. Even the
process of fine-tuning on apparently benign data for downstream tasks can
jeopardize safety. One potential solution is to conduct safety fine-tuning
subsequent to downs... | 2024-05-15T03:04:05Z | null | null | null | null | null | null | null | null | null | null |
2,405.09111 | CarDreamer: Open-Source Learning Platform for World Model based
Autonomous Driving | ['Dechen Gao', 'Shuangyu Cai', 'Hanchu Zhou', 'Hang Wang', 'Iman Soltani', 'Junshan Zhang'] | ['cs.RO', 'cs.AI'] | To safely navigate intricate real-world scenarios, autonomous vehicles must
be able to adapt to diverse road conditions and anticipate future events. World
model (WM) based reinforcement learning (RL) has emerged as a promising
approach by learning and predicting the complex dynamics of various
environments. Neverthele... | 2024-05-15T05:57:20Z | Dechen Gao, Shuangyu Cai, Hanchu Zhou, Hang Wang contributed equally | null | null | null | null | null | null | null | null | null |
2,405.09215 | Xmodel-VLM: A Simple Baseline for Multimodal Vision Language Model | ['Wanting Xu', 'Yang Liu', 'Langping He', 'Xucheng Huang', 'Ling Jiang'] | ['cs.CV', 'cs.AI'] | We introduce Xmodel-VLM, a cutting-edge multimodal vision language model. It
is designed for efficient deployment on consumer GPU servers. Our work directly
confronts a pivotal industry issue by grappling with the prohibitive service
costs that hinder the broad adoption of large-scale multimodal systems. Through
rigoro... | 2024-05-15T09:47:59Z | null | null | null | Xmodel-VLM: A Simple Baseline for Multimodal Vision Language Model | ['Wanting Xu', 'Yang Liu', 'Langping He', 'Xucheng Huang', 'Ling Jiang'] | 2,024 | arXiv.org | 2 | 49 | ['Computer Science'] |
2,405.09318 | Transfer Learning in Pre-Trained Large Language Models for Malware
Detection Based on System Calls | ['Pedro Miguel Sánchez Sánchez', 'Alberto Huertas Celdrán', 'Gérôme Bovet', 'Gregorio Martínez Pérez'] | ['cs.CR', 'cs.LG'] | In the current cybersecurity landscape, protecting military devices such as
communication and battlefield management systems against sophisticated cyber
attacks is crucial. Malware exploits vulnerabilities through stealth methods,
often evading traditional detection mechanisms such as software signatures. The
applicati... | 2024-05-15T13:19:43Z | Submitted to IEEE MILCOM 2024 | null | null | Transfer Learning in Pre-Trained Large Language Models for Malware Detection Based on System Calls | ['P. Sánchez', 'Alberto Huertas Celdrán', 'Gérôme Bovet', 'Gregorio Martínez Pérez'] | 2,024 | IEEE Military Communications Conference | 11 | 24 | ['Computer Science'] |
2,405.09365 | SARATR-X: Toward Building A Foundation Model for SAR Target Recognition | ['Weijie Li', 'Wei Yang', 'Yuenan Hou', 'Li Liu', 'Yongxiang Liu', 'Xiang Li'] | ['cs.CV'] | Despite the remarkable progress in synthetic aperture radar automatic target
recognition (SAR ATR), recent efforts have concentrated on detecting and
classifying a specific category, e.g., vehicles, ships, airplanes, or
buildings. One of the fundamental limitations of the top-performing SAR ATR
methods is that the lear... | 2024-05-15T14:17:44Z | 20 pages, 9 figures | null | null | SARATR-X: Toward Building a Foundation Model for SAR Target Recognition | ['Wei-Jang Li', 'Wei Yang', 'Yuenan Hou', 'Li Liu', 'Yongxiang Liu', 'Xiang Li'] | 2,024 | IEEE Transactions on Image Processing | 11 | 132 | ['Medicine', 'Computer Science'] |
2,405.09605 | Elements of World Knowledge (EWoK): A Cognition-Inspired Framework for
Evaluating Basic World Knowledge in Language Models | ['Anna A. Ivanova', 'Aalok Sathe', 'Benjamin Lipkin', 'Unnathi Kumar', 'Setayesh Radkani', 'Thomas H. Clark', 'Carina Kauf', 'Jennifer Hu', 'R. T. Pramod', 'Gabriel Grand', 'Vivian Paulun', 'Maria Ryskina', 'Ekin Akyürek', 'Ethan Wilcox', 'Nafisa Rashid', 'Leshem Choshen', 'Roger Levy', 'Evelina Fedorenko', 'Joshua Ten... | ['cs.CL', 'cs.AI', 'cs.LG'] | The ability to build and reason about models of the world is essential for
situated language understanding. But evaluating world modeling capabilities in
modern AI systems -- especially those based on language models -- has proven
challenging, in large part because of the difficulty of disentangling
conceptual knowledg... | 2024-05-15T17:19:42Z | Accepted to Transactions of the ACL (TACL). Contains 25 pages (14
main), 6 figures. Visit http://ewok-core.github.io for data and code. Authors
Anna Ivanova, Aalok Sathe, Benjamin Lipkin contributed equally | null | null | null | null | null | null | null | null | null |
2,405.09673 | LoRA Learns Less and Forgets Less | ['Dan Biderman', 'Jacob Portes', 'Jose Javier Gonzalez Ortiz', 'Mansheej Paul', 'Philip Greengard', 'Connor Jennings', 'Daniel King', 'Sam Havens', 'Vitaliy Chiley', 'Jonathan Frankle', 'Cody Blakeney', 'John P. Cunningham'] | ['cs.LG', 'cs.AI', 'cs.CL'] | Low-Rank Adaptation (LoRA) is a widely-used parameter-efficient finetuning
method for large language models. LoRA saves memory by training only low rank
perturbations to selected weight matrices. In this work, we compare the
performance of LoRA and full finetuning on two target domains, programming and
mathematics. We ... | 2024-05-15T19:27:45Z | Final version with new experiments and analyses, as accepted to
Transactions on Machine Learning Research, August 2024 (Featured
Certification). https://openreview.net/forum?id=aloEru2qCG¬eId=Jb3PQNQDI2 | null | null | LoRA Learns Less and Forgets Less | ['D. Biderman', 'Jose Gonzalez Ortiz', 'Jacob Portes', 'Mansheej Paul', 'Philip Greengard', 'Connor Jennings', 'Daniel King', 'Sam Havens', 'Vitaliy Chiley', 'Jonathan Frankle', 'Cody Blakeney', 'John P. Cunningham'] | 2,024 | Trans. Mach. Learn. Res. | 142 | 89 | ['Computer Science'] |
2,405.09814 | Semantic Gesticulator: Semantics-Aware Co-Speech Gesture Synthesis | ['Zeyi Zhang', 'Tenglong Ao', 'Yuyao Zhang', 'Qingzhe Gao', 'Chuan Lin', 'Baoquan Chen', 'Libin Liu'] | ['cs.GR', 'cs.CV', 'cs.SD', 'eess.AS'] | In this work, we present Semantic Gesticulator, a novel framework designed to
synthesize realistic gestures accompanying speech with strong semantic
correspondence. Semantically meaningful gestures are crucial for effective
non-verbal communication, but such gestures often fall within the long tail of
the distribution ... | 2024-05-16T05:09:01Z | SIGGRAPH 2024 (Journal Track); Project page:
https://pku-mocca.github.io/Semantic-Gesticulator-Page | null | null | Semantic Gesticulator: Semantics-Aware Co-Speech Gesture Synthesis | ['Zeyi Zhang', 'Tenglong Ao', 'Yuyao Zhang', 'Qingzhe Gao', 'Chuan Lin', 'Baoquan Chen', 'Libin Liu'] | 2,024 | ACM Transactions on Graphics | 17 | 32 | ['Computer Science', 'Engineering'] |
2,405.09818 | Chameleon: Mixed-Modal Early-Fusion Foundation Models | ['Chameleon Team'] | ['cs.CL'] | We present Chameleon, a family of early-fusion token-based mixed-modal models
capable of understanding and generating images and text in any arbitrary
sequence. We outline a stable training approach from inception, an alignment
recipe, and an architectural parameterization tailored for the early-fusion,
token-based, mi... | 2024-05-16T05:23:41Z | null | null | null | null | null | null | null | null | null | null |
2,405.09927 | Moreau Envelope for Nonconvex Bi-Level Optimization: A Single-loop and
Hessian-free Solution Strategy | ['Risheng Liu', 'Zhu Liu', 'Wei Yao', 'Shangzhi Zeng', 'Jin Zhang'] | ['math.OC', 'cs.LG'] | This work focuses on addressing two major challenges in the context of
large-scale nonconvex Bi-Level Optimization (BLO) problems, which are
increasingly applied in machine learning due to their ability to model nested
structures. These challenges involve ensuring computational efficiency and
providing theoretical guar... | 2024-05-16T09:33:28Z | Accepted by ICML 2024 | null | null | null | null | null | null | null | null | null |
2,405.1014 | Libra: Building Decoupled Vision System on Large Language Models | ['Yifan Xu', 'Xiaoshan Yang', 'Yaguang Song', 'Changsheng Xu'] | ['cs.CV'] | In this work, we introduce Libra, a prototype model with a decoupled vision
system on a large language model (LLM). The decoupled vision system decouples
inner-modal modeling and cross-modal interaction, yielding unique visual
information modeling and effective cross-modal comprehension. Libra is trained
through discre... | 2024-05-16T14:34:44Z | ICML2024 | null | null | Libra: Building Decoupled Vision System on Large Language Models | ['Yifan Xu', 'Xiaoshan Yang', 'Y. Song', 'Changsheng Xu'] | 2,024 | International Conference on Machine Learning | 8 | 79 | ['Computer Science'] |
2,405.10243 | DocuMint: Docstring Generation for Python using Small Language Models | ['Bibek Poudel', 'Adam Cook', 'Sekou Traore', 'Shelah Ameli'] | ['cs.SE', 'cs.LG'] | Effective communication, specifically through documentation, is the beating
heart of collaboration among contributors in software development. Recent
advancements in language models (LMs) have enabled the introduction of a new
type of actor in that ecosystem: LM-powered assistants capable of code
generation, optimizati... | 2024-05-16T16:46:46Z | 12 pages, 4 figures | null | null | null | null | null | null | null | null | null |
2,405.10254 | PRISM: A Multi-Modal Generative Foundation Model for Slide-Level
Histopathology | ['George Shaikovski', 'Adam Casson', 'Kristen Severson', 'Eric Zimmermann', 'Yi Kan Wang', 'Jeremy D. Kunz', 'Juan A. Retamero', 'Gerard Oakley', 'David Klimstra', 'Christopher Kanan', 'Matthew Hanna', 'Michal Zelechowski', 'Julian Viret', 'Neil Tenenholtz', 'James Hall', 'Nicolo Fusi', 'Razik Yousfi', 'Peter Hamilton'... | ['eess.IV', 'cs.CV', 'cs.LG'] | Foundation models in computational pathology promise to unlock the
development of new clinical decision support systems and models for precision
medicine. However, there is a mismatch between most clinical analysis, which is
defined at the level of one or more whole slide images, and foundation models
to date, which pr... | 2024-05-16T16:59:12Z | null | null | null | PRISM: A Multi-Modal Generative Foundation Model for Slide-Level Histopathology | ['George Shaikovski', 'Adam Casson', 'Kristen Severson', 'Eric Zimmermann', 'Yi Kan Wang', 'J. Kunz', 'J. Retamero', 'Gerard Oakley', 'D. Klimstra', 'C. Kanan', 'Matthew G Hanna', 'Michal Zelechowski', 'Julian Viret', 'Neil Tenenholtz', 'James Hall', 'Nicolò Fusi', 'Razik Yousfi', 'Peter Hamilton', 'William A. Moye', '... | 2,024 | arXiv.org | 35 | 48 | ['Computer Science', 'Engineering'] |
2,405.10315 | TRANSIC: Sim-to-Real Policy Transfer by Learning from Online Correction | ['Yunfan Jiang', 'Chen Wang', 'Ruohan Zhang', 'Jiajun Wu', 'Li Fei-Fei'] | ['cs.RO', 'cs.AI', 'cs.LG'] | Learning in simulation and transferring the learned policy to the real world
has the potential to enable generalist robots. The key challenge of this
approach is to address simulation-to-reality (sim-to-real) gaps. Previous
methods often require domain-specific knowledge a priori. We argue that a
straightforward way to... | 2024-05-16T17:59:07Z | 8th Conference on Robot Learning (CoRL 2024), Munich, Germany.
Project website: https://transic-robot.github.io/ | null | null | null | null | null | null | null | null | null |
2,405.10517 | Towards Better Question Generation in QA-based Event Extraction | ['Zijin Hong', 'Jian Liu'] | ['cs.CL'] | Event Extraction (EE) is an essential information extraction task that aims
to extract event-related information from unstructured texts. The paradigm of
this task has shifted from conventional classification-based methods to more
contemporary question-answering-based (QA-based) approaches. However, in
QA-based EE, the... | 2024-05-17T03:52:01Z | Accepted to ACL2024 Findings | null | null | null | null | null | null | null | null | null |
2,405.10637 | Layer-Condensed KV Cache for Efficient Inference of Large Language
Models | ['Haoyi Wu', 'Kewei Tu'] | ['cs.CL'] | Huge memory consumption has been a major bottleneck for deploying
high-throughput large language models in real-world applications. In addition
to the large number of parameters, the key-value (KV) cache for the attention
mechanism in the transformer architecture consumes a significant amount of
memory, especially when... | 2024-05-17T08:59:46Z | Accepted to ACL2024 main conference | null | null | Layer-Condensed KV Cache for Efficient Inference of Large Language Models | ['Haoyi Wu', 'Kewei Tu'] | 2,024 | Annual Meeting of the Association for Computational Linguistics | 19 | 38 | ['Computer Science'] |
2,405.10725 | INDUS: Effective and Efficient Language Models for Scientific
Applications | ['Bishwaranjan Bhattacharjee', 'Aashka Trivedi', 'Masayasu Muraoka', 'Muthukumaran Ramasubramanian', 'Takuma Udagawa', 'Iksha Gurung', 'Nishan Pantha', 'Rong Zhang', 'Bharath Dandala', 'Rahul Ramachandran', 'Manil Maskey', 'Kaylin Bugbee', 'Mike Little', 'Elizabeth Fancher', 'Irina Gerasimov', 'Armin Mehrabian', 'Laure... | ['cs.CL', 'cs.IR'] | Large language models (LLMs) trained on general domain corpora showed
remarkable results on natural language processing (NLP) tasks. However,
previous research demonstrated LLMs trained using domain-focused corpora
perform better on specialized tasks. Inspired by this insight, we developed
INDUS, a comprehensive suite ... | 2024-05-17T12:15:07Z | EMNLP 2024 (Industry Track) | null | null | null | null | null | null | null | null | null |
2,405.11143 | OpenRLHF: An Easy-to-use, Scalable and High-performance RLHF Framework | ['Jian Hu', 'Xibin Wu', 'Wei Shen', 'Jason Klein Liu', 'Zilin Zhu', 'Weixun Wang', 'Songlin Jiang', 'Haoran Wang', 'Hao Chen', 'Bin Chen', 'Weikai Fang', 'Xianyu', 'Yu Cao', 'Haotian Xu', 'Yiming Liu'] | ['cs.AI', 'cs.CL', 'cs.LG'] | Large Language Models (LLMs) fine-tuned via Reinforcement Learning from Human
Feedback (RLHF) and Reinforcement Learning with Verifiable Rewards (RLVR)
significantly improve the alignment of human-AI values and further raise the
upper bound of AI capabilities, particularly in reasoning-intensive,
long-context Chain-of-... | 2024-05-20T01:04:40Z | null | null | null | OpenRLHF: An Easy-to-use, Scalable and High-performance RLHF Framework | ['Jian Hu', 'Xibin Wu', 'Weixun Wang', 'Dehao Zhang', 'Yu Cao', 'OpenLLMAI Team', 'Netease Fuxi', 'AI Lab', 'Alibaba Group'] | 2,024 | arXiv.org | 130 | 30 | ['Computer Science'] |
2,405.1129 | MBIAS: Mitigating Bias in Large Language Models While Retaining Context | ['Shaina Raza', 'Ananya Raval', 'Veronica Chatrath'] | ['cs.CL'] | The deployment of Large Language Models (LLMs) in diverse applications
necessitates an assurance of safety without compromising the contextual
integrity of the generated content. Traditional approaches, including
safety-specific fine-tuning or adversarial testing, often yield safe outputs at
the expense of contextual m... | 2024-05-18T13:31:12Z | null | null | null | null | null | null | null | null | null | null |
2,405.11403 | MapCoder: Multi-Agent Code Generation for Competitive Problem Solving | ['Md. Ashraful Islam', 'Mohammed Eunus Ali', 'Md Rizwan Parvez'] | ['cs.CL', 'cs.AI'] | Code synthesis, which requires a deep understanding of complex natural
language problem descriptions, generation of code instructions for complex
algorithms and data structures, and the successful execution of comprehensive
unit tests, presents a significant challenge. While large language models
(LLMs) demonstrate imp... | 2024-05-18T22:10:15Z | null | null | null | null | null | null | null | null | null | null |
2,405.11449 | NetMamba: Efficient Network Traffic Classification via Pre-training
Unidirectional Mamba | ['Tongze Wang', 'Xiaohui Xie', 'Wenduo Wang', 'Chuyi Wang', 'Youjian Zhao', 'Yong Cui'] | ['cs.LG', 'cs.NI'] | Network traffic classification is a crucial research area aiming to enhance
service quality, streamline network management, and bolster cybersecurity. To
address the growing complexity of transmission encryption techniques, various
machine learning and deep learning methods have been proposed. However,
existing approac... | 2024-05-19T04:58:53Z | null | null | null | null | null | null | null | null | null | null |
2,405.11582 | SLAB: Efficient Transformers with Simplified Linear Attention and
Progressive Re-parameterized Batch Normalization | ['Jialong Guo', 'Xinghao Chen', 'Yehui Tang', 'Yunhe Wang'] | ['cs.CV', 'cs.CL'] | Transformers have become foundational architectures for both natural language
and computer vision tasks. However, the high computational cost makes it quite
challenging to deploy on resource-constraint devices. This paper investigates
the computational bottleneck modules of efficient transformer, i.e.,
normalization la... | 2024-05-19T15:22:25Z | ICML 2024 | null | null | SLAB: Efficient Transformers with Simplified Linear Attention and Progressive Re-parameterized Batch Normalization | ['Jialong Guo', 'Xinghao Chen', 'Yehui Tang', 'Yunhe Wang'] | 2,024 | International Conference on Machine Learning | 14 | 46 | ['Computer Science'] |
2,405.11724 | Token-wise Influential Training Data Retrieval for Large Language Models | ['Huawei Lin', 'Jikai Long', 'Zhaozhuo Xu', 'Weijie Zhao'] | ['cs.CL', 'cs.AI', 'cs.CR', 'cs.IR'] | Given a Large Language Model (LLM) generation, how can we identify which
training data led to this generation? In this paper, we proposed RapidIn, a
scalable framework adapting to LLMs for estimating the influence of each
training data. The proposed framework consists of two stages: caching and
retrieval. First, we com... | 2024-05-20T01:57:34Z | Accepted to ACL 2024. Keywords: Influence Function, Influence
Estimation, Training Data Attribution | null | null | null | null | null | null | null | null | null |
2,405.11788 | TinyLLaVA Factory: A Modularized Codebase for Small-scale Large
Multimodal Models | ['Junlong Jia', 'Ying Hu', 'Xi Weng', 'Yiming Shi', 'Miao Li', 'Xingjian Zhang', 'Baichuan Zhou', 'Ziyu Liu', 'Jie Luo', 'Lei Huang', 'Ji Wu'] | ['cs.LG'] | We present TinyLLaVA Factory, an open-source modular codebase for small-scale
large multimodal models (LMMs) with a focus on simplicity of code
implementations, extensibility of new features, and reproducibility of training
results. Following the design philosophy of the factory pattern in software
engineering, TinyLLa... | 2024-05-20T05:11:02Z | Our codebase is made public at
https://github.com/TinyLLaVA/TinyLLaVA_Factory with documentation available
at https://tinyllava-factory.readthedocs.io/en/latest/ | null | null | null | null | null | null | null | null | null |
2,405.11794 | ViViD: Video Virtual Try-on using Diffusion Models | ['Zixun Fang', 'Wei Zhai', 'Aimin Su', 'Hongliang Song', 'Kai Zhu', 'Mao Wang', 'Yu Chen', 'Zhiheng Liu', 'Yang Cao', 'Zheng-Jun Zha'] | ['cs.CV'] | Video virtual try-on aims to transfer a clothing item onto the video of a
target person. Directly applying the technique of image-based try-on to the
video domain in a frame-wise manner will cause temporal-inconsistent outcomes
while previous video-based try-on solutions can only generate low visual
quality and blurrin... | 2024-05-20T05:28:22Z | null | null | null | null | null | null | null | null | null | null |
2,405.11831 | SSAMBA: Self-Supervised Audio Representation Learning with Mamba State
Space Model | ['Siavash Shams', 'Sukru Samet Dindar', 'Xilin Jiang', 'Nima Mesgarani'] | ['eess.AS', 'cs.LG'] | Transformers have revolutionized deep learning across various tasks,
including audio representation learning, due to their powerful modeling
capabilities. However, they often suffer from quadratic complexity in both GPU
memory usage and computational inference time, affecting their efficiency.
Recently, state space mod... | 2024-05-20T06:58:47Z | Code at https://github.com/SiavashShams/ssamba | 2024 IEEE Spoken Language Technology Workshop (SLT), Macao, pp.
1053-1059 | 10.1109/SLT61566.2024.10832304 | null | null | null | null | null | null | null |
2,405.1185 | Rethinking Overlooked Aspects in Vision-Language Models | ['Yuan Liu', 'Le Tian', 'Xiao Zhou', 'Jie Zhou'] | ['cs.CV'] | Recent advancements in large vision-language models (LVLMs), such as GPT4-V
and LLaVA, have been substantial. LLaVA's modular architecture, in particular,
offers a blend of simplicity and efficiency. Recent works mainly focus on
introducing more pre-training and instruction tuning data to improve model's
performance. T... | 2024-05-20T07:53:41Z | null | null | null | null | null | null | null | null | null | null |
2,405.12107 | Imp: Highly Capable Large Multimodal Models for Mobile Devices | ['Zhenwei Shao', 'Zhou Yu', 'Jun Yu', 'Xuecheng Ouyang', 'Lihao Zheng', 'Zhenbiao Gai', 'Mingyang Wang', 'Jiajun Ding'] | ['cs.CV', 'cs.CL'] | By harnessing the capabilities of large language models (LLMs), recent large
multimodal models (LMMs) have shown remarkable versatility in open-world
multimodal understanding. Nevertheless, they are usually parameter-heavy and
computation-intensive, thus hindering their applicability in
resource-constrained scenarios. ... | 2024-05-20T15:23:19Z | fix some typos and correct a few number in the tables | null | null | null | null | null | null | null | null | null |
2,405.12255 | Mammo-CLIP: A Vision Language Foundation Model to Enhance Data
Efficiency and Robustness in Mammography | ['Shantanu Ghosh', 'Clare B. Poynton', 'Shyam Visweswaran', 'Kayhan Batmanghelich'] | ['eess.IV', 'cs.CV'] | The lack of large and diverse training data on Computer-Aided Diagnosis (CAD)
in breast cancer detection has been one of the concerns that impedes the
adoption of the system. Recently, pre-training with large-scale image text
datasets via Vision-Language models (VLM) (\eg CLIP) partially addresses the
issue of robustne... | 2024-05-20T08:27:39Z | MICCAI 2024, early accept, top 11% | null | null | null | null | null | null | null | null | null |
2,405.12399 | Diffusion for World Modeling: Visual Details Matter in Atari | ['Eloi Alonso', 'Adam Jelley', 'Vincent Micheli', 'Anssi Kanervisto', 'Amos Storkey', 'Tim Pearce', 'François Fleuret'] | ['cs.LG', 'cs.AI', 'cs.CV'] | World models constitute a promising approach for training reinforcement
learning agents in a safe and sample-efficient manner. Recent world models
predominantly operate on sequences of discrete latent variables to model
environment dynamics. However, this compression into a compact discrete
representation may ignore vi... | 2024-05-20T22:51:05Z | NeurIPS 2024 (Spotlight) | null | null | Diffusion for World Modeling: Visual Details Matter in Atari | ['Eloi Alonso', 'Adam Jelley', 'Vincent Micheli', 'A. Kanervisto', 'A. Storkey', 'Tim Pearce', 'Franccois Fleuret'] | 2,024 | Neural Information Processing Systems | 69 | 89 | ['Computer Science'] |
2,405.12612 | Tagengo: A Multilingual Chat Dataset | ['Peter Devine'] | ['cs.CL', 'cs.AI', 'cs.LG'] | Open source large language models (LLMs) have shown great improvements in
recent times. However, many of these models are focused solely on popular
spoken languages. We present a high quality dataset of more than 70k
prompt-response pairs in 74 languages which consist of human generated prompts
and synthetic responses.... | 2024-05-21T09:06:36Z | null | null | null | null | null | null | null | null | null | null |
2,405.12739 | SPO: Multi-Dimensional Preference Sequential Alignment With Implicit
Reward Modeling | ['Xingzhou Lou', 'Junge Zhang', 'Jian Xie', 'Lifeng Liu', 'Dong Yan', 'Kaiqi Huang'] | ['cs.LG'] | Human preference alignment is critical in building powerful and reliable
large language models (LLMs). However, current methods either ignore the
multi-dimensionality of human preferences (e.g. helpfulness and harmlessness)
or struggle with the complexity of managing multiple reward models. To address
these issues, we ... | 2024-05-21T12:47:17Z | null | null | null | null | null | null | null | null | null | null |
2,405.1297 | Face Adapter for Pre-Trained Diffusion Models with Fine-Grained ID and
Attribute Control | ['Yue Han', 'Junwei Zhu', 'Keke He', 'Xu Chen', 'Yanhao Ge', 'Wei Li', 'Xiangtai Li', 'Jiangning Zhang', 'Chengjie Wang', 'Yong Liu'] | ['cs.CV'] | Current face reenactment and swapping methods mainly rely on GAN frameworks,
but recent focus has shifted to pre-trained diffusion models for their superior
generation capabilities. However, training these models is resource-intensive,
and the results have not yet achieved satisfactory performance levels. To
address th... | 2024-05-21T17:50:12Z | Accepted to ECCV2024; Project Page:
https://faceadapter.github.io/face-adapter.github.io/ | null | null | null | null | null | null | null | null | null |
2,405.12972 | Accelerating Resonance Searches via Signature-Oriented Pre-training | ['Congqiao Li', 'Antonios Agapitos', 'Jovin Drews', 'Javier Duarte', 'Dawei Fu', 'Leyun Gao', 'Raghav Kansal', 'Gregor Kasieczka', 'Louis Moureaux', 'Huilin Qu', 'Cristina Mantilla Suarez', 'Qiang Li'] | ['hep-ph', 'hep-ex', 'physics.data-an'] | The search for heavy resonances beyond the Standard Model (BSM) is a key
objective at the LHC. While the recent use of advanced deep neural networks for
boosted-jet tagging significantly enhances the sensitivity of dedicated
searches, it is limited to specific final states, leaving vast potential BSM
phase space undere... | 2024-05-21T17:54:53Z | 14 pages, 5 figures | null | null | null | null | null | null | null | null | null |
2,405.1301 | UCCIX: Irish-eXcellence Large Language Model | ['Khanh-Tung Tran', "Barry O'Sullivan", 'Hoang D. Nguyen'] | ['cs.CL', 'cs.AI'] | The development of Large Language Models (LLMs) has predominantly focused on
high-resource languages, leaving extremely low-resource languages like Irish
with limited representation. This work presents UCCIX, a pioneering effort on
the development of an open-source Irish-based LLM. We propose a novel framework
for cont... | 2024-05-13T13:19:27Z | null | null | null | null | null | null | null | null | null | null |
2,405.13053 | MeteoRA: Multiple-tasks Embedded LoRA for Large Language Models | ['Jingwei Xu', 'Junyu Lai', 'Yunpeng Huang'] | ['cs.CL', 'cs.AI', 'I.2.7'] | The pretrain+fine-tune paradigm is foundational for deploying large language
models (LLMs) across various downstream applications. Within this framework,
Low-Rank Adaptation (LoRA) stands out for its parameter-efficient fine-tuning
(PEFT), producing numerous reusable task-specific LoRA adapters. However, this
approach ... | 2024-05-19T20:46:07Z | 26 pages | null | null | null | null | null | null | null | null | null |
2,405.13144 | LLMs for Mathematical Modeling: Towards Bridging the Gap between Natural
and Mathematical Languages | ['Xuhan Huang', 'Qingning Shen', 'Yan Hu', 'Anningzhe Gao', 'Benyou Wang'] | ['cs.AI', 'cs.CL'] | Large Language Models (LLMs) have demonstrated strong performance across
various natural language processing tasks, yet their proficiency in
mathematical reasoning remains a key challenge. Addressing the gap between
natural and mathematical language requires advanced reasoning capabilities,
approaching those of Artific... | 2024-05-21T18:29:54Z | Findings of NAACL2025. Project:
https://github.com/FreedomIntelligence/Mamo | null | null | LLMs for Mathematical Modeling: Towards Bridging the Gap between Natural and Mathematical Languages | ['Xuhan Huang', 'Qingning Shen', 'Yan Hu', 'Anningzhe Gao', 'Benyou Wang'] | 2,024 | North American Chapter of the Association for Computational Linguistics | 3 | 36 | ['Computer Science'] |
2,405.13226 | Dataset Decomposition: Faster LLM Training with Variable Sequence Length
Curriculum | ['Hadi Pouransari', 'Chun-Liang Li', 'Jen-Hao Rick Chang', 'Pavan Kumar Anasosalu Vasu', 'Cem Koc', 'Vaishaal Shankar', 'Oncel Tuzel'] | ['cs.CL', 'cs.LG'] | Large language models (LLMs) are commonly trained on datasets consisting of
fixed-length token sequences. These datasets are created by randomly
concatenating documents of various lengths and then chunking them into
sequences of a predetermined target length (concat-and-chunk). Recent attention
implementations mask cro... | 2024-05-21T22:26:01Z | NeurIPS 2024 | null | null | Dataset Decomposition: Faster LLM Training with Variable Sequence Length Curriculum | ['Hadi Pouransari', 'Chun-Liang Li', 'Jen-Hao Rick Chang', 'Pavan Kumar Anasosalu Vasu', 'Cem Koc', 'Vaishaal Shankar', 'Oncel Tuzel'] | 2,024 | Neural Information Processing Systems | 11 | 66 | ['Computer Science'] |
2,405.13382 | VTG-LLM: Integrating Timestamp Knowledge into Video LLMs for Enhanced
Video Temporal Grounding | ['Yongxin Guo', 'Jingyu Liu', 'Mingda Li', 'Dingxin Cheng', 'Xiaoying Tang', 'Dianbo Sui', 'Qingbin Liu', 'Xi Chen', 'Kevin Zhao'] | ['cs.CV'] | Video Temporal Grounding (VTG) strives to accurately pinpoint event
timestamps in a specific video using linguistic queries, significantly
impacting downstream tasks like video browsing and editing. Unlike traditional
task-specific models, Video Large Language Models (video LLMs) can handle
multiple tasks concurrently ... | 2024-05-22T06:31:42Z | AAAI 2025 | null | null | null | null | null | null | null | null | null |
2,405.13386 | 360Zhinao Technical Report | ['360Zhinao Team'] | ['cs.CL', 'cs.AI'] | We present 360Zhinao models with 7B parameter size and context lengths
spanning 4K, 32K and 360K, all available at
https://github.com/Qihoo360/360zhinao. For rapid development in pretraining, we
establish a stable and sensitive ablation environment to evaluate and compare
experiment runs with minimal model size. Under ... | 2024-05-22T06:45:38Z | 360Zhinao technical report. Github:
https://github.com/Qihoo360/360zhinao | null | null | null | null | null | null | null | null | null |
2,405.13396 | Fine-tuned In-Context Learning Transformers are Excellent Tabular Data
Classifiers | ['Felix den Breejen', 'Sangmin Bae', 'Stephen Cha', 'Se-Young Yun'] | ['cs.LG', 'stat.ML'] | The recently introduced TabPFN pretrains an In-Context Learning (ICL)
transformer on synthetic data to perform tabular data classification. In this
work, we extend TabPFN to the fine-tuning setting, resulting in a significant
performance boost. We also discover that fine-tuning enables ICL-transformers
to create comple... | 2024-05-22T07:13:55Z | null | null | null | null | null | null | null | null | null | null |
2,405.13448 | Distilling Instruction-following Abilities of Large Language Models with
Task-aware Curriculum Planning | ['Yuanhao Yue', 'Chengyu Wang', 'Jun Huang', 'Peng Wang'] | ['cs.CL'] | Instruction tuning aims to align large language models (LLMs) with
open-domain instructions and human-preferred responses. While several studies
have explored autonomous approaches to distilling and annotating instructions
from powerful proprietary LLMs, such as ChatGPT, they often neglect the impact
of the distributio... | 2024-05-22T08:38:26Z | emnlp 2024 findings | null | null | Distilling Instruction-following Abilities of Large Language Models with Task-aware Curriculum Planning | ['Yuanhao Yue', 'Chengyu Wang', 'Jun Huang', 'Peng Wang'] | 2,024 | Conference on Empirical Methods in Natural Language Processing | 9 | 52 | ['Computer Science'] |
2,405.13636 | Audio Mamba: Pretrained Audio State Space Model For Audio Tagging | ['Jiaju Lin', 'Haoxuan Hu'] | ['cs.SD', 'cs.AI', 'eess.AS'] | Audio tagging is an important task of mapping audio samples to their
corresponding categories. Recently endeavours that exploit transformer models
in this field have achieved great success. However, the quadratic
self-attention cost limits the scaling of audio transformer models and further
constrains the development o... | 2024-05-22T13:35:56Z | null | null | null | Audio Mamba: Pretrained Audio State Space Model For Audio Tagging | ['Jiaju Lin', 'Haoxuan Hu'] | 2,024 | arXiv.org | 9 | 21 | ['Computer Science', 'Engineering'] |
2,405.13637 | Curriculum Direct Preference Optimization for Diffusion and Consistency
Models | ['Florinel-Alin Croitoru', 'Vlad Hondru', 'Radu Tudor Ionescu', 'Nicu Sebe', 'Mubarak Shah'] | ['cs.CV', 'cs.AI', 'cs.LG'] | Direct Preference Optimization (DPO) has been proposed as an effective and
efficient alternative to reinforcement learning from human feedback (RLHF). In
this paper, we propose a novel and enhanced version of DPO based on curriculum
learning for text-to-image generation. Our method is divided into two training
stages. ... | 2024-05-22T13:36:48Z | Accepted at CVPR 2025 | null | null | null | null | null | null | null | null | null |
2,405.138 | Dense Connector for MLLMs | ['Huanjin Yao', 'Wenhao Wu', 'Taojiannan Yang', 'YuXin Song', 'Mengxi Zhang', 'Haocheng Feng', 'Yifan Sun', 'Zhiheng Li', 'Wanli Ouyang', 'Jingdong Wang'] | ['cs.CV', 'cs.AI'] | Do we fully leverage the potential of visual encoder in Multimodal Large
Language Models (MLLMs)? The recent outstanding performance of MLLMs in
multimodal understanding has garnered broad attention from both academia and
industry. In the current MLLM rat race, the focus seems to be predominantly on
the linguistic side... | 2024-05-22T16:25:03Z | 27 pages, NeurIPS 2024 | NeurIPS 2024 | null | null | null | null | null | null | null | null |
2,405.13816 | Getting More from Less: Large Language Models are Good Spontaneous
Multilingual Learners | ['Shimao Zhang', 'Changjiang Gao', 'Wenhao Zhu', 'Jiajun Chen', 'Xin Huang', 'Xue Han', 'Junlan Feng', 'Chao Deng', 'Shujian Huang'] | ['cs.CL'] | Recently, Large Language Models (LLMs) have shown impressive language
capabilities. While most of the existing LLMs have very unbalanced performance
across different languages, multilingual alignment based on translation
parallel data is an effective method to enhance the LLMs' multilingual
capabilities. In this work, ... | 2024-05-22T16:46:19Z | null | null | null | null | null | null | null | null | null | null |
2,405.13865 | ReVideo: Remake a Video with Motion and Content Control | ['Chong Mou', 'Mingdeng Cao', 'Xintao Wang', 'Zhaoyang Zhang', 'Ying Shan', 'Jian Zhang'] | ['cs.CV'] | Despite significant advancements in video generation and editing using
diffusion models, achieving accurate and localized video editing remains a
substantial challenge. Additionally, most existing video editing methods
primarily focus on altering visual content, with limited research dedicated to
motion editing. In thi... | 2024-05-22T17:46:08Z | null | null | null | ReVideo: Remake a Video with Motion and Content Control | ['Chong Mou', 'Mingdeng Cao', 'Xintao Wang', 'Zhaoyang Zhang', 'Ying Shan', 'Jian Zhang'] | 2,024 | Neural Information Processing Systems | 31 | 0 | ['Computer Science'] |
2,405.13929 | Vikhr: The Family of Open-Source Instruction-Tuned Large Language Models
for Russian | ['Aleksandr Nikolich', 'Konstantin Korolev', 'Sergei Bratchikov', 'Igor Kiselev', 'Artem Shelmanov'] | ['cs.CL', 'cs.AI'] | There has been a surge in the development of various Large Language Models
(LLMs). However, text generation for languages other than English often faces
significant challenges, including poor generation quality and reduced
computational performance due to the disproportionate representation of tokens
in the model's voc... | 2024-05-22T18:58:58Z | null | null | null | Vikhr: The Family of Open-Source Instruction-Tuned Large Language Models for Russian | ['Aleksandr Nikolich', 'Konstantin Korolev', 'Artem Shelmanov'] | 2,024 | arXiv.org | 11 | 33 | ['Computer Science'] |
2,405.14129 | AlignGPT: Multi-modal Large Language Models with Adaptive Alignment
Capability | ['Fei Zhao', 'Taotian Pang', 'Chunhui Li', 'Zhen Wu', 'Junjie Guo', 'Shangyu Xing', 'Xinyu Dai'] | ['cs.CL', 'cs.AI', 'cs.CV'] | Multimodal Large Language Models (MLLMs) are widely regarded as crucial in
the exploration of Artificial General Intelligence (AGI). The core of MLLMs
lies in their capability to achieve cross-modal alignment. To attain this goal,
current MLLMs typically follow a two-phase training paradigm: the pre-training
phase and ... | 2024-05-23T03:07:56Z | null | null | null | AlignGPT: Multi-modal Large Language Models with Adaptive Alignment Capability | ['Fei Zhao', 'Taotian Pang', 'Chunhui Li', 'Zhen Wu', 'Junjie Guo', 'Shangyu Xing', 'Xinyu Dai'] | 2,024 | arXiv.org | 7 | 46 | ['Computer Science'] |
2,405.14141 | ViHateT5: Enhancing Hate Speech Detection in Vietnamese With A Unified
Text-to-Text Transformer Model | ['Luan Thanh Nguyen'] | ['cs.CL'] | Recent advancements in hate speech detection (HSD) in Vietnamese have made
significant progress, primarily attributed to the emergence of
transformer-based pre-trained language models, particularly those built on the
BERT architecture. However, the necessity for specialized fine-tuned models has
resulted in the complex... | 2024-05-23T03:31:50Z | Accepted at ACL'2024 (Findings) | null | null | null | null | null | null | null | null | null |
2,405.14205 | Agent Planning with World Knowledge Model | ['Shuofei Qiao', 'Runnan Fang', 'Ningyu Zhang', 'Yuqi Zhu', 'Xiang Chen', 'Shumin Deng', 'Yong Jiang', 'Pengjun Xie', 'Fei Huang', 'Huajun Chen'] | ['cs.CL', 'cs.AI', 'cs.CV', 'cs.LG', 'cs.MA'] | Recent endeavors towards directly using large language models (LLMs) as agent
models to execute interactive planning tasks have shown commendable results.
Despite their achievements, however, they still struggle with brainless
trial-and-error in global planning and generating hallucinatory actions in
local planning due... | 2024-05-23T06:03:19Z | NeurIPS 2024 | null | null | null | null | null | null | null | null | null |
2,405.14295 | Focus Anywhere for Fine-grained Multi-page Document Understanding | ['Chenglong Liu', 'Haoran Wei', 'Jinyue Chen', 'Lingyu Kong', 'Zheng Ge', 'Zining Zhu', 'Liang Zhao', 'Jianjian Sun', 'Chunrui Han', 'Xiangyu Zhang'] | ['cs.CV'] | Modern LVLMs still struggle to achieve fine-grained document understanding,
such as OCR/translation/caption for regions of interest to the user, tasks that
require the context of the entire page, or even multiple pages. Accordingly,
this paper proposes Fox, an effective pipeline, hybrid data, and tuning
strategy, that ... | 2024-05-23T08:15:49Z | null | null | null | Focus Anywhere for Fine-grained Multi-page Document Understanding | ['Chenglong Liu', 'Haoran Wei', 'Jinyue Chen', 'Lingyu Kong', 'Zheng Ge', 'Zining Zhu', 'Liang Zhao', 'Jian‐Yuan Sun', 'Chunrui Han', 'Xiangyu Zhang'] | 2,024 | arXiv.org | 25 | 44 | ['Computer Science'] |
2,405.14297 | Dynamic Mixture of Experts: An Auto-Tuning Approach for Efficient
Transformer Models | ['Yongxin Guo', 'Zhenglin Cheng', 'Xiaoying Tang', 'Zhaopeng Tu', 'Tao Lin'] | ['cs.LG', 'cs.AI'] | The Sparse Mixture of Experts (SMoE) has been widely employed to enhance the
efficiency of training and inference for Transformer-based foundational models,
yielding promising results.However, the performance of SMoE heavily depends on
the choice of hyper-parameters, such as the number of experts and the number of
expe... | 2024-05-23T08:18:30Z | ICLR 2025 | null | null | Dynamic Mixture of Experts: An Auto-Tuning Approach for Efficient Transformer Models | ['Yongxin Guo', 'Zhenglin Cheng', 'Xiaoying Tang', 'Tao Lin'] | 2,024 | International Conference on Learning Representations | 9 | 69 | ['Computer Science'] |
2,405.14333 | DeepSeek-Prover: Advancing Theorem Proving in LLMs through Large-Scale
Synthetic Data | ['Huajian Xin', 'Daya Guo', 'Zhihong Shao', 'Zhizhou Ren', 'Qihao Zhu', 'Bo Liu', 'Chong Ruan', 'Wenda Li', 'Xiaodan Liang'] | ['cs.AI'] | Proof assistants like Lean have revolutionized mathematical proof
verification, ensuring high accuracy and reliability. Although large language
models (LLMs) show promise in mathematical reasoning, their advancement in
formal theorem proving is hindered by a lack of training data. To address this
issue, we introduce an... | 2024-05-23T09:03:42Z | null | null | null | DeepSeek-Prover: Advancing Theorem Proving in LLMs through Large-Scale Synthetic Data | ['Huajian Xin', 'Daya Guo', 'Zhihong Shao', 'Z. Ren', 'Qihao Zhu', 'Bo Liu (Benjamin Liu)', 'C. Ruan', 'Wenda Li', 'Xiaodan Liang'] | 2,024 | arXiv.org | 91 | 35 | ['Computer Science'] |
2,405.14365 | JiuZhang3.0: Efficiently Improving Mathematical Reasoning by Training
Small Data Synthesis Models | ['Kun Zhou', 'Beichen Zhang', 'Jiapeng Wang', 'Zhipeng Chen', 'Wayne Xin Zhao', 'Jing Sha', 'Zhichao Sheng', 'Shijin Wang', 'Ji-Rong Wen'] | ['cs.CL', 'cs.AI'] | Mathematical reasoning is an important capability of large language
models~(LLMs) for real-world applications. To enhance this capability, existing
work either collects large-scale math-related texts for pre-training, or relies
on stronger LLMs (\eg GPT-4) to synthesize massive math problems. Both types of
work general... | 2024-05-23T09:43:19Z | 28 pages, SOTA math LLM using Well-trained Data Synthesis LLM | null | null | null | null | null | null | null | null | null |
2,405.14385 | Emotion Identification for French in Written Texts: Considering their
Modes of Expression as a Step Towards Text Complexity Analysis | ['Aline Étienne', 'Delphine Battistelli', 'Gwénolé Lecorvé'] | ['cs.CL', 'cs.AI'] | The objective of this paper is to predict (A) whether a sentence in a written
text expresses an emotion, (B) the mode(s) in which it is expressed, (C)
whether it is basic or complex, and (D) its emotional category.
One of our major contributions, through a dataset and a model, is to
integrate the fact that an emotion... | 2024-05-23T10:02:13Z | 17 pages, 12 figures, submitted to ACL 2024 WASSA workshop | null | null | null | null | null | null | null | null | null |
2,405.14438 | LoRA-Ensemble: Efficient Uncertainty Modelling for Self-Attention
Networks | ['Dominik J. Mühlematter', 'Michelle Halbheer', 'Alexander Becker', 'Dominik Narnhofer', 'Helge Aasen', 'Konrad Schindler', 'Mehmet Ozgur Turkoglu'] | ['cs.LG'] | Numerous real-world decisions rely on machine learning algorithms and require
calibrated uncertainty estimates. However, modern methods often yield
overconfident, uncalibrated predictions. The dominant approach to quantifying
the uncertainty inherent in the model is to train an ensemble of separate
predictors and measu... | 2024-05-23T11:10:32Z | under review | null | null | LoRA-Ensemble: Efficient Uncertainty Modelling for Self-attention Networks | ['Michelle Halbheer', 'Dominik J. Mühlematter', 'Alexander Becker', 'Dominik Narnhofer', 'Helge Aasen', 'Konrad Schindler', 'Mehmet Ozgur Turkoglu'] | 2,024 | arXiv.org | 3 | 65 | ['Computer Science'] |
2,405.14449 | Adversarial Schrödinger Bridge Matching | ['Nikita Gushchin', 'Daniil Selikhanovych', 'Sergei Kholkin', 'Evgeny Burnaev', 'Alexander Korotin'] | ['cs.LG'] | The Schr\"odinger Bridge (SB) problem offers a powerful framework for
combining optimal transport and diffusion models. A promising recent approach
to solve the SB problem is the Iterative Markovian Fitting (IMF) procedure,
which alternates between Markovian and reciprocal projections of
continuous-time stochastic proc... | 2024-05-23T11:29:33Z | null | null | null | Adversarial Schrödinger Bridge Matching | ['Nikita Gushchin', 'Daniil Selikhanovych', 'Sergei Kholkin', 'Evgeny Burnaev', 'Alexander Korotin'] | 2,024 | Neural Information Processing Systems | 3 | 57 | ['Computer Science'] |
2,405.14458 | YOLOv10: Real-Time End-to-End Object Detection | ['Ao Wang', 'Hui Chen', 'Lihao Liu', 'Kai Chen', 'Zijia Lin', 'Jungong Han', 'Guiguang Ding'] | ['cs.CV'] | Over the past years, YOLOs have emerged as the predominant paradigm in the
field of real-time object detection owing to their effective balance between
computational cost and detection performance. Researchers have explored the
architectural designs, optimization objectives, data augmentation strategies,
and others for... | 2024-05-23T11:44:29Z | Code: https://github.com/THU-MIG/yolov10; NeurIPS 2024 Camera-ready
Version | null | null | null | null | null | null | null | null | null |
2,405.14488 | MoGU: A Framework for Enhancing Safety of Open-Sourced LLMs While
Preserving Their Usability | ['Yanrui Du', 'Sendong Zhao', 'Danyang Zhao', 'Ming Ma', 'Yuhan Chen', 'Liangyu Huo', 'Qing Yang', 'Dongliang Xu', 'Bing Qin'] | ['cs.CL'] | Large Language Models (LLMs) are increasingly deployed in various
applications. As their usage grows, concerns regarding their safety are rising,
especially in maintaining harmless responses when faced with malicious
instructions. Many defense strategies have been developed to enhance the safety
of LLMs. However, our r... | 2024-05-23T12:19:59Z | null | null | null | MoGU: A Framework for Enhancing Safety of Open-Sourced LLMs While Preserving Their Usability | ['Yanrui Du', 'Sendong Zhao', 'Danyang Zhao', 'Ming Ma', 'Yuhan Chen', 'Liangyu Huo', 'Qing Yang', 'Dongliang Xu', 'Bing Qin'] | 2,024 | arXiv.org | 11 | 44 | ['Computer Science'] |
2,405.14573 | AndroidWorld: A Dynamic Benchmarking Environment for Autonomous Agents | ['Christopher Rawles', 'Sarah Clinckemaillie', 'Yifan Chang', 'Jonathan Waltz', 'Gabrielle Lau', 'Marybeth Fair', 'Alice Li', 'William Bishop', 'Wei Li', 'Folawiyo Campbell-Ajala', 'Daniel Toyama', 'Robert Berry', 'Divya Tyamagundlu', 'Timothy Lillicrap', 'Oriana Riva'] | ['cs.AI', 'cs.LG'] | Autonomous agents that execute human tasks by controlling computers can
enhance human productivity and application accessibility. However, progress in
this field will be driven by realistic and reproducible benchmarks. We present
AndroidWorld, a fully functional Android environment that provides reward
signals for 116 ... | 2024-05-23T13:48:54Z | null | null | null | null | null | null | null | null | null | null |
2,405.14654 | Efficient Medical Question Answering with Knowledge-Augmented Question
Generation | ['Julien Khlaut', 'Corentin Dancette', 'Elodie Ferreres', 'Alaedine Bennani', 'Paul Hérent', 'Pierre Manceron'] | ['cs.CL', 'cs.AI'] | In the expanding field of language model applications, medical knowledge
representation remains a significant challenge due to the specialized nature of
the domain. Large language models, such as GPT-4, obtain reasonable scores on
medical question answering tasks, but smaller models are far behind. In this
work, we int... | 2024-05-23T14:53:52Z | Accepted at the Clinical Natural Language Processing Workshop, NAACL
2024 | null | null | null | null | null | null | null | null | null |
2,405.14734 | SimPO: Simple Preference Optimization with a Reference-Free Reward | ['Yu Meng', 'Mengzhou Xia', 'Danqi Chen'] | ['cs.CL', 'cs.LG'] | Direct Preference Optimization (DPO) is a widely used offline preference
optimization algorithm that reparameterizes reward functions in reinforcement
learning from human feedback (RLHF) to enhance simplicity and training
stability. In this work, we propose SimPO, a simpler yet more effective
approach. The effectivenes... | 2024-05-23T16:01:46Z | NeurIPS 2024. Code & models: https://github.com/princeton-nlp/SimPO.
v3 updates: Gemma 2 results (Appendix J); more discussions about length
normalization (Section 2.2) and KL regularization (Section 2.3) | null | null | SimPO: Simple Preference Optimization with a Reference-Free Reward | ['Yu Meng', 'Mengzhou Xia', 'Danqi Chen'] | 2,024 | Neural Information Processing Systems | 494 | 99 | ['Computer Science'] |
2,405.14753 | A Transformer-Based Approach for Smart Invocation of Automatic Code
Completion | ['Aral de Moor', 'Arie van Deursen', 'Maliheh Izadi'] | ['cs.SE', 'cs.AI', 'cs.HC', 'cs.LG'] | Transformer-based language models are highly effective for code completion,
with much research dedicated to enhancing the content of these completions.
Despite their effectiveness, these models come with high operational costs and
can be intrusive, especially when they suggest too often and interrupt
developers who are... | 2024-05-23T16:19:32Z | 10 pages, 3 figures; Accepted at FSE AIWARE'24 | null | 10.1145/3664646.3664760 | null | null | null | null | null | null | null |
2,405.14793 | SEA-RAFT: Simple, Efficient, Accurate RAFT for Optical Flow | ['Yihan Wang', 'Lahav Lipson', 'Jia Deng'] | ['cs.CV'] | We introduce SEA-RAFT, a more simple, efficient, and accurate RAFT for
optical flow. Compared with RAFT, SEA-RAFT is trained with a new loss (mixture
of Laplace). It directly regresses an initial flow for faster convergence in
iterative refinements and introduces rigid-motion pre-training to improve
generalization. SEA... | 2024-05-23T17:04:04Z | null | null | null | null | null | null | null | null | null | null |
2,405.14832 | Direct3D: Scalable Image-to-3D Generation via 3D Latent Diffusion
Transformer | ['Shuang Wu', 'Youtian Lin', 'Feihu Zhang', 'Yifei Zeng', 'Jingxi Xu', 'Philip Torr', 'Xun Cao', 'Yao Yao'] | ['cs.CV'] | Generating high-quality 3D assets from text and images has long been
challenging, primarily due to the absence of scalable 3D representations
capable of capturing intricate geometry distributions. In this work, we
introduce Direct3D, a native 3D generative model scalable to in-the-wild input
images, without requiring a... | 2024-05-23T17:49:37Z | null | null | null | null | null | null | null | null | null | null |
2,405.14839 | A Textbook Remedy for Domain Shifts: Knowledge Priors for Medical Image
Analysis | ['Yue Yang', 'Mona Gandhi', 'Yufei Wang', 'Yifan Wu', 'Michael S. Yao', 'Chris Callison-Burch', 'James C. Gee', 'Mark Yatskar'] | ['cs.CV', 'cs.CL'] | While deep networks have achieved broad success in analyzing natural images,
when applied to medical scans, they often fail in unexcepted situations. We
investigate this challenge and focus on model sensitivity to domain shifts,
such as data sampled from different hospitals or data confounded by demographic
variables s... | 2024-05-23T17:55:02Z | Published in NeurIPS 2024 (Spotlight), project page:
https://yueyang1996.github.io/knobo/ | null | null | A Textbook Remedy for Domain Shifts: Knowledge Priors for Medical Image Analysis | ['Yue Yang', 'Mona Gandhi', 'Yufei Wang', 'Yifan Wu', 'Michael S. Yao', 'Christopher Callison-Burch', 'James C. Gee', 'Mark Yatskar'] | 2,024 | Neural Information Processing Systems | 4 | 97 | ['Computer Science', 'Medicine'] |
2,405.14852 | PV-Tuning: Beyond Straight-Through Estimation for Extreme LLM
Compression | ['Vladimir Malinovskii', 'Denis Mazur', 'Ivan Ilin', 'Denis Kuznedelev', 'Konstantin Burlachenko', 'Kai Yi', 'Dan Alistarh', 'Peter Richtarik'] | ['cs.LG'] | There has been significant interest in "extreme" compression of large
language models (LLMs), i.e., to 1-2 bits per parameter, which allows such
models to be executed efficiently on resource-constrained devices. Existing
work focused on improved one-shot quantization techniques and weight
representations; yet, purely p... | 2024-05-23T17:57:04Z | Preprint | null | null | null | null | null | null | null | null | null |
2,405.14854 | TerDiT: Ternary Diffusion Models with Transformers | ['Xudong Lu', 'Aojun Zhou', 'Ziyi Lin', 'Qi Liu', 'Yuhui Xu', 'Renrui Zhang', 'Xue Yang', 'Junchi Yan', 'Peng Gao', 'Hongsheng Li'] | ['cs.CV', 'cs.LG'] | Recent developments in large-scale pre-trained text-to-image diffusion models
have significantly improved the generation of high-fidelity images,
particularly with the emergence of diffusion transformer models (DiTs). Among
diffusion models, diffusion transformers have demonstrated superior
image-generation capabilitie... | 2024-05-23T17:57:24Z | null | null | null | null | null | null | null | null | null | null |
2,405.14867 | Improved Distribution Matching Distillation for Fast Image Synthesis | ['Tianwei Yin', 'Michaël Gharbi', 'Taesung Park', 'Richard Zhang', 'Eli Shechtman', 'Fredo Durand', 'William T. Freeman'] | ['cs.CV'] | Recent approaches have shown promises distilling diffusion models into
efficient one-step generators. Among them, Distribution Matching Distillation
(DMD) produces one-step generators that match their teacher in distribution,
without enforcing a one-to-one correspondence with the sampling trajectories of
their teachers... | 2024-05-23T17:59:49Z | Code, model, and dataset are available at
https://tianweiy.github.io/dmd2 | null | null | null | null | null | null | null | null | null |
2,405.14905 | Structural Entities Extraction and Patient Indications Incorporation for
Chest X-ray Report Generation | ['Kang Liu', 'Zhuoqi Ma', 'Xiaolu Kang', 'Zhusi Zhong', 'Zhicheng Jiao', 'Grayson Baird', 'Harrison Bai', 'Qiguang Miao'] | ['eess.IV', 'cs.AI', 'cs.CL'] | The automated generation of imaging reports proves invaluable in alleviating
the workload of radiologists. A clinically applicable reports generation
algorithm should demonstrate its effectiveness in producing reports that
accurately describe radiology findings and attend to patient-specific
indications. In this paper,... | 2024-05-23T01:29:47Z | The code is available at https://github.com/mk-runner/SEI-Temp or
https://github.com/mk-runner/SEI | null | null | null | null | null | null | null | null | null |
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