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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2,309.11497 | FreeU: Free Lunch in Diffusion U-Net | ['Chenyang Si', 'Ziqi Huang', 'Yuming Jiang', 'Ziwei Liu'] | ['cs.CV'] | In this paper, we uncover the untapped potential of diffusion U-Net, which
serves as a "free lunch" that substantially improves the generation quality on
the fly. We initially investigate the key contributions of the U-Net
architecture to the denoising process and identify that its main backbone
primarily contributes t... | 2023-09-20T17:56:18Z | Method update: we proposed structure-based scaling to enhance the
performance of FreeU. Project page: https://chenyangsi.top/FreeU/ | null | null | null | null | null | null | null | null | null |
2,309.11566 | SignBank+: Preparing a Multilingual Sign Language Dataset for Machine
Translation Using Large Language Models | ['Amit Moryossef', 'Zifan Jiang'] | ['cs.CL'] | We introduce SignBank+, a clean version of the SignBank dataset, optimized
for machine translation between spoken language text and SignWriting, a
phonetic sign language writing system. In addition to previous work that
employs complex factorization techniques to enable translation between text and
SignWriting, we show... | 2023-09-20T18:08:28Z | null | null | null | SignBank+: Preparing a Multilingual Sign Language Dataset for Machine Translation Using Large Language Models | ['Amit Moryossef', 'Zifan Jiang'] | 2,023 | null | 0 | 27 | ['Computer Science'] |
2,309.11568 | BTLM-3B-8K: 7B Parameter Performance in a 3B Parameter Model | ['Nolan Dey', 'Daria Soboleva', 'Faisal Al-Khateeb', 'Bowen Yang', 'Ribhu Pathria', 'Hemant Khachane', 'Shaheer Muhammad', 'Zhiming', 'Chen', 'Robert Myers', 'Jacob Robert Steeves', 'Natalia Vassilieva', 'Marvin Tom', 'Joel Hestness'] | ['cs.AI', 'cs.CL', 'cs.LG'] | We introduce the Bittensor Language Model, called "BTLM-3B-8K", a new
state-of-the-art 3 billion parameter open-source language model. BTLM-3B-8K was
trained on 627B tokens from the SlimPajama dataset with a mixture of 2,048 and
8,192 context lengths. BTLM-3B-8K outperforms all existing 3B parameter models
by 2-5.5% ac... | 2023-09-20T18:12:56Z | null | null | null | null | null | null | null | null | null | null |
2,309.11674 | A Paradigm Shift in Machine Translation: Boosting Translation
Performance of Large Language Models | ['Haoran Xu', 'Young Jin Kim', 'Amr Sharaf', 'Hany Hassan Awadalla'] | ['cs.CL'] | Generative Large Language Models (LLMs) have achieved remarkable advancements
in various NLP tasks. However, these advances have not been reflected in the
translation task, especially those with moderate model sizes (i.e., 7B or 13B
parameters), which still lag behind conventional supervised encoder-decoder
translation... | 2023-09-20T22:53:15Z | Accepted at ICLR 2024 | null | null | null | null | null | null | null | null | null |
2,309.11925 | Scaling up COMETKIWI: Unbabel-IST 2023 Submission for the Quality
Estimation Shared Task | ['Ricardo Rei', 'Nuno M. Guerreiro', 'José Pombal', 'Daan van Stigt', 'Marcos Treviso', 'Luisa Coheur', 'José G. C. de Souza', 'André F. T. Martins'] | ['cs.CL'] | We present the joint contribution of Unbabel and Instituto Superior T\'ecnico
to the WMT 2023 Shared Task on Quality Estimation (QE). Our team participated
on all tasks: sentence- and word-level quality prediction (task 1) and
fine-grained error span detection (task 2). For all tasks, we build on the
COMETKIWI-22 model... | 2023-09-21T09:38:56Z | null | null | null | Scaling up CometKiwi: Unbabel-IST 2023 Submission for the Quality Estimation Shared Task | ['Ricardo Rei', 'Nuno M. Guerreiro', 'José P. Pombal', 'Daan van Stigt', 'Marcos Vinícius Treviso', 'Luísa Coheur', 'José G. C. de Souza', 'André F. T. Martins'] | 2,023 | Conference on Machine Translation | 63 | 17 | ['Computer Science'] |
2,309.11998 | LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset | ['Lianmin Zheng', 'Wei-Lin Chiang', 'Ying Sheng', 'Tianle Li', 'Siyuan Zhuang', 'Zhanghao Wu', 'Yonghao Zhuang', 'Zhuohan Li', 'Zi Lin', 'Eric P. Xing', 'Joseph E. Gonzalez', 'Ion Stoica', 'Hao Zhang'] | ['cs.CL', 'cs.AI'] | Studying how people interact with large language models (LLMs) in real-world
scenarios is increasingly important due to their widespread use in various
applications. In this paper, we introduce LMSYS-Chat-1M, a large-scale dataset
containing one million real-world conversations with 25 state-of-the-art LLMs.
This datas... | 2023-09-21T12:13:55Z | null | null | null | null | null | null | null | null | null | null |
2,309.12053 | AceGPT, Localizing Large Language Models in Arabic | ['Huang Huang', 'Fei Yu', 'Jianqing Zhu', 'Xuening Sun', 'Hao Cheng', 'Dingjie Song', 'Zhihong Chen', 'Abdulmohsen Alharthi', 'Bang An', 'Juncai He', 'Ziche Liu', 'Zhiyi Zhang', 'Junying Chen', 'Jianquan Li', 'Benyou Wang', 'Lian Zhang', 'Ruoyu Sun', 'Xiang Wan', 'Haizhou Li', 'Jinchao Xu'] | ['cs.CL'] | This paper is devoted to the development of a localized Large Language Model
(LLM) specifically for Arabic, a language imbued with unique cultural
characteristics inadequately addressed by current mainstream models.
Significant concerns emerge when addressing cultural sensitivity and local
values. To address this, the ... | 2023-09-21T13:20:13Z | Accepted to NAACL main conference.
https://github.com/FreedomIntelligence/AceGPT | null | null | null | null | null | null | null | null | null |
2,309.12161 | Code Soliloquies for Accurate Calculations in Large Language Models | ['Shashank Sonkar', 'MyCo Le', 'Xinghe Chen', 'Naiming Liu', 'Debshila Basu Mallick', 'Richard G. Baraniuk'] | ['cs.CL'] | High-quality conversational datasets are crucial for the successful
development of Intelligent Tutoring Systems (ITS) that utilize a Large Language
Model (LLM) backend. Synthetic student-teacher dialogues, generated using
advanced GPT-4 models, are a common strategy for creating these datasets.
However, subjects like p... | 2023-09-21T15:16:58Z | null | null | null | null | null | null | null | null | null | null |
2,309.12284 | MetaMath: Bootstrap Your Own Mathematical Questions for Large Language
Models | ['Longhui Yu', 'Weisen Jiang', 'Han Shi', 'Jincheng Yu', 'Zhengying Liu', 'Yu Zhang', 'James T. Kwok', 'Zhenguo Li', 'Adrian Weller', 'Weiyang Liu'] | ['cs.CL', 'cs.AI'] | Large language models (LLMs) have pushed the limits of natural language
understanding and exhibited excellent problem-solving ability. Despite the
great success, most existing open-source LLMs (e.g., LLaMA-2) are still far
away from satisfactory for solving mathematical problem due to the complex
reasoning procedures. ... | 2023-09-21T17:45:42Z | To appear at ICLR 2024 (Spotlight). Project Page:
https://meta-math.github.io/ | null | null | MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models | ['L. Yu', 'Weisen Jiang', 'Han Shi', 'Jincheng Yu', 'Zhengying Liu', 'Yu Zhang', 'James T. Kwok', 'Zheng Li', 'Adrian Weller', 'Weiyang Liu'] | 2,023 | International Conference on Learning Representations | 395 | 84 | ['Computer Science'] |
2,309.12307 | LongLoRA: Efficient Fine-tuning of Long-Context Large Language Models | ['Yukang Chen', 'Shengju Qian', 'Haotian Tang', 'Xin Lai', 'Zhijian Liu', 'Song Han', 'Jiaya Jia'] | ['cs.CL', 'cs.AI', 'cs.LG'] | We present LongLoRA, an efficient fine-tuning approach that extends the
context sizes of pre-trained large language models (LLMs), with limited
computation cost. Typically, training LLMs with long context sizes is
computationally expensive, requiring extensive training hours and GPU
resources. For example, training on ... | 2023-09-21T17:59:11Z | Code, models, dataset, and demo are available at
https://github.com/dvlab-research/LongLoRA | null | null | null | null | null | null | null | null | null |
2,309.12871 | AnglE-optimized Text Embeddings | ['Xianming Li', 'Jing Li'] | ['cs.CL', 'cs.AI', 'cs.LG'] | High-quality text embedding is pivotal in improving semantic textual
similarity (STS) tasks, which are crucial components in Large Language Model
(LLM) applications. However, a common challenge existing text embedding models
face is the problem of vanishing gradients, primarily due to their reliance on
the cosine funct... | 2023-09-22T13:52:42Z | Published at the Proceedings of ACL24. AoE: Angle-optimized
Embeddings for Semantic Textual Similarity
(https://aclanthology.org/2024.acl-long.101/) | null | null | null | null | null | null | null | null | null |
2,309.13202 | Investigating Large Language Models and Control Mechanisms to Improve
Text Readability of Biomedical Abstracts | ['Zihao Li', 'Samuel Belkadi', 'Nicolo Micheletti', 'Lifeng Han', 'Matthew Shardlow', 'Goran Nenadic'] | ['cs.CL', 'cs.AI'] | Biomedical literature often uses complex language and inaccessible
professional terminologies. That is why simplification plays an important role
in improving public health literacy. Applying Natural Language Processing (NLP)
models to automate such tasks allows for quick and direct accessibility for lay
readers. In th... | 2023-09-22T22:47:32Z | Accepted by IEEE-ICHI 2024 https://ieeeichi2024.github.io/ | null | null | null | null | null | null | null | null | null |
2,309.13259 | EMelodyGen: Emotion-Conditioned Melody Generation in ABC Notation with
the Musical Feature Template | ['Monan Zhou', 'Xiaobing Li', 'Feng Yu', 'Wei Li'] | ['cs.IR', 'cs.AI', 'cs.SD', 'eess.AS'] | The EMelodyGen system focuses on emotional melody generation in ABC notation
controlled by the musical feature template. Owing to the scarcity of
well-structured and emotionally labeled sheet music, we designed a template for
controlling emotional melody generation by statistical correlations between
musical features a... | 2023-09-23T04:46:28Z | 6 pages, 4 figures, accepted by ICMEW2025 | 2025 IEEE International Conference on Multimedia and Expo
Workshops (ICMEW), Nantes, France, 2025 | null | null | null | null | null | null | null | null |
2,309.13353 | Beyond Grids: Exploring Elastic Input Sampling for Vision Transformers | ['Adam Pardyl', 'Grzegorz Kurzejamski', 'Jan Olszewski', 'Tomasz Trzciński', 'Bartosz Zieliński'] | ['cs.CV'] | Vision transformers have excelled in various computer vision tasks but mostly
rely on rigid input sampling using a fixed-size grid of patches. It limits
their applicability in real-world problems, such as active visual exploration,
where patches have various scales and positions. Our paper addresses this
limitation by ... | 2023-09-23T12:03:30Z | WACV 2025 | null | null | Beyond Grids: Exploring Elastic Input Sampling for Vision Transformers | ['Adam Pardyl', 'Grzegorz Kurzejamski', 'Jan Olszewski', "Tomasz Trzci'nski", "Bartosz Zieli'nski"] | 2,023 | IEEE Workshop/Winter Conference on Applications of Computer Vision | 1 | 36 | ['Computer Science'] |
2,309.13567 | MentaLLaMA: Interpretable Mental Health Analysis on Social Media with
Large Language Models | ['Kailai Yang', 'Tianlin Zhang', 'Ziyan Kuang', 'Qianqian Xie', 'Jimin Huang', 'Sophia Ananiadou'] | ['cs.CL'] | With the development of web technology, social media texts are becoming a
rich source for automatic mental health analysis. As traditional discriminative
methods bear the problem of low interpretability, the recent large language
models have been explored for interpretable mental health analysis on social
media, which ... | 2023-09-24T06:46:08Z | Accepted by WWW 2024 | null | 10.1145/3589334.3648137 | MentaLLaMA: Interpretable Mental Health Analysis on Social Media with Large Language Models | ['Kailai Yang', 'Tianlin Zhang', 'Zi-Zhou Kuang', 'Qianqian Xie', 'Sophia Ananiadou'] | 2,023 | The Web Conference | 58 | 62 | ['Computer Science'] |
2,309.13876 | Reproducing Whisper-Style Training Using an Open-Source Toolkit and
Publicly Available Data | ['Yifan Peng', 'Jinchuan Tian', 'Brian Yan', 'Dan Berrebbi', 'Xuankai Chang', 'Xinjian Li', 'Jiatong Shi', 'Siddhant Arora', 'William Chen', 'Roshan Sharma', 'Wangyou Zhang', 'Yui Sudo', 'Muhammad Shakeel', 'Jee-weon Jung', 'Soumi Maiti', 'Shinji Watanabe'] | ['cs.CL', 'cs.SD', 'eess.AS'] | Pre-training speech models on large volumes of data has achieved remarkable
success. OpenAI Whisper is a multilingual multitask model trained on 680k hours
of supervised speech data. It generalizes well to various speech recognition
and translation benchmarks even in a zero-shot setup. However, the full
pipeline for de... | 2023-09-25T05:01:34Z | Accepted at ASRU 2023 | null | null | Reproducing Whisper-Style Training Using An Open-Source Toolkit And Publicly Available Data | ['Yifan Peng', 'Jinchuan Tian', 'Brian Yan', 'Dan Berrebbi', 'Xuankai Chang', 'Xinjian Li', 'Jiatong Shi', 'Siddhant Arora', 'William Chen', 'Roshan Sharma', 'Wangyou Zhang', 'Yui Sudo', 'Muhammad Shakeel', 'Jee-weon Jung', 'Soumi Maiti', 'Shinji Watanabe'] | 2,023 | Automatic Speech Recognition & Understanding | 41 | 70 | ['Computer Science', 'Engineering'] |
2,309.14113 | HyperTrack: Neural Combinatorics for High Energy Physics | ['Mikael Mieskolainen'] | ['hep-ph', 'cs.LG', 'hep-ex'] | Combinatorial inverse problems in high energy physics span enormous
algorithmic challenges. This work presents a new deep learning driven
clustering algorithm that utilizes a space-time non-local trainable graph
constructor, a graph neural network, and a set transformer. The model is
trained with loss functions at the ... | 2023-09-25T13:12:08Z | CHEP 2023 proceedings. 8 pages (max) | null | null | null | null | null | null | null | null | null |
2,309.14316 | Physics of Language Models: Part 3.1, Knowledge Storage and Extraction | ['Zeyuan Allen-Zhu', 'Yuanzhi Li'] | ['cs.CL', 'cs.AI', 'cs.LG'] | Large language models (LLMs) can store a vast amount of world knowledge,
often extractable via question-answering (e.g., "What is Abraham Lincoln's
birthday?"). However, do they answer such questions based on exposure to
similar questions during training (i.e., cheating), or by genuinely learning to
extract knowledge f... | 2023-09-25T17:37:20Z | V2 polishes writing + fixes author name; V3 includes additional Llama
experiments and writing improvements | null | null | null | null | null | null | null | null | null |
2,309.14322 | Small-scale proxies for large-scale Transformer training instabilities | ['Mitchell Wortsman', 'Peter J. Liu', 'Lechao Xiao', 'Katie Everett', 'Alex Alemi', 'Ben Adlam', 'John D. Co-Reyes', 'Izzeddin Gur', 'Abhishek Kumar', 'Roman Novak', 'Jeffrey Pennington', 'Jascha Sohl-dickstein', 'Kelvin Xu', 'Jaehoon Lee', 'Justin Gilmer', 'Simon Kornblith'] | ['cs.LG'] | Teams that have trained large Transformer-based models have reported training
instabilities at large scale that did not appear when training with the same
hyperparameters at smaller scales. Although the causes of such instabilities
are of scientific interest, the amount of resources required to reproduce them
has made ... | 2023-09-25T17:48:51Z | null | null | null | null | null | null | null | null | null | null |
2,309.14402 | Physics of Language Models: Part 3.2, Knowledge Manipulation | ['Zeyuan Allen-Zhu', 'Yuanzhi Li'] | ['cs.CL', 'cs.AI', 'cs.LG'] | Language models can store vast factual knowledge, yet their ability to
flexibly use this knowledge for downstream tasks (e.g., via instruction
finetuning) remains questionable. This paper investigates four fundamental
knowledge manipulation tasks: retrieval (e.g., "What is person A's attribute
X?"), classification (e.g... | 2023-09-25T17:50:41Z | V2 polishes writing and includes additional Llama/Mistral experiments
and larger data; but the conclusions remain unchanged | null | null | Physics of Language Models: Part 3.2, Knowledge Manipulation | ['Zeyuan Allen-Zhu', 'Yuanzhi Li'] | 2,023 | International Conference on Learning Representations | 105 | 37 | ['Computer Science'] |
2,309.14405 | Joint Audio and Speech Understanding | ['Yuan Gong', 'Alexander H. Liu', 'Hongyin Luo', 'Leonid Karlinsky', 'James Glass'] | ['cs.SD', 'cs.AI', 'eess.AS'] | Humans are surrounded by audio signals that include both speech and
non-speech sounds. The recognition and understanding of speech and non-speech
audio events, along with a profound comprehension of the relationship between
them, constitute fundamental cognitive capabilities. For the first time, we
build a machine lear... | 2023-09-25T17:59:05Z | Accepted at ASRU 2023. Code, dataset, and pretrained models are at
https://github.com/yuangongnd/ltu. Interactive demo at
https://huggingface.co/spaces/yuangongfdu/ltu-2 | null | null | null | null | null | null | null | null | null |
2,309.14507 | Noise-Robust DSP-Assisted Neural Pitch Estimation with Very Low
Complexity | ['Krishna Subramani', 'Jean-Marc Valin', 'Jan Buethe', 'Paris Smaragdis', 'Mike Goodwin'] | ['eess.AS', 'cs.SD'] | Pitch estimation is an essential step of many speech processing algorithms,
including speech coding, synthesis, and enhancement. Recently, pitch estimators
based on deep neural networks (DNNs) have have been outperforming
well-established DSP-based techniques. Unfortunately, these new estimators can
be impractical to d... | 2023-09-25T20:14:31Z | Submitted to ICASSP 2024, 5 pages | null | null | Noise-Robust DSP-Assisted Neural Pitch Estimation With Very Low Complexity | ['K. Subramani', 'J. Valin', 'Jan Büthe', 'Paris Smaragdis', 'Mike Goodwin'] | 2,023 | IEEE International Conference on Acoustics, Speech, and Signal Processing | 3 | 32 | ['Engineering', 'Computer Science'] |
2,309.14509 | DeepSpeed Ulysses: System Optimizations for Enabling Training of Extreme
Long Sequence Transformer Models | ['Sam Ade Jacobs', 'Masahiro Tanaka', 'Chengming Zhang', 'Minjia Zhang', 'Shuaiwen Leon Song', 'Samyam Rajbhandari', 'Yuxiong He'] | ['cs.LG', 'cs.CL', 'cs.DC'] | Computation in a typical Transformer-based large language model (LLM) can be
characterized by batch size, hidden dimension, number of layers, and sequence
length. Until now, system works for accelerating LLM training have focused on
the first three dimensions: data parallelism for batch size, tensor parallelism
for hid... | 2023-09-25T20:15:57Z | null | null | null | null | null | null | null | null | null | null |
2,309.14859 | Navigating Text-To-Image Customization: From LyCORIS Fine-Tuning to
Model Evaluation | ['Shih-Ying Yeh', 'Yu-Guan Hsieh', 'Zhidong Gao', 'Bernard B W Yang', 'Giyeong Oh', 'Yanmin Gong'] | ['cs.CV', 'cs.AI', 'cs.GR', 'cs.LG'] | Text-to-image generative models have garnered immense attention for their
ability to produce high-fidelity images from text prompts. Among these, Stable
Diffusion distinguishes itself as a leading open-source model in this
fast-growing field. However, the intricacies of fine-tuning these models pose
multiple challenges... | 2023-09-26T11:36:26Z | In International Conference on Learning Representations 12 (ICLR
2024) [79 pages, 54 figures, 7 tables] | null | null | Navigating Text-To-Image Customization: From LyCORIS Fine-Tuning to Model Evaluation | ['Shin-Ying Yeh', 'Yu-Guan Hsieh', 'Zhidong Gao', 'Bernard B. W. Yang', 'Giyeong Oh', 'Yanmin Gong'] | 2,023 | arXiv.org | 87 | 0 | ['Computer Science'] |
2,309.15088 | RankVicuna: Zero-Shot Listwise Document Reranking with Open-Source Large
Language Models | ['Ronak Pradeep', 'Sahel Sharifymoghaddam', 'Jimmy Lin'] | ['cs.IR', 'cs.CL'] | Researchers have successfully applied large language models (LLMs) such as
ChatGPT to reranking in an information retrieval context, but to date, such
work has mostly been built on proprietary models hidden behind opaque API
endpoints. This approach yields experimental results that are not reproducible
and non-determin... | 2023-09-26T17:31:57Z | null | null | null | RankVicuna: Zero-Shot Listwise Document Reranking with Open-Source Large Language Models | ['Ronak Pradeep', 'Sahel Sharifymoghaddam', 'Jimmy Lin'] | 2,023 | arXiv.org | 43 | 41 | ['Computer Science'] |
2,309.15103 | LAVIE: High-Quality Video Generation with Cascaded Latent Diffusion
Models | ['Yaohui Wang', 'Xinyuan Chen', 'Xin Ma', 'Shangchen Zhou', 'Ziqi Huang', 'Yi Wang', 'Ceyuan Yang', 'Yinan He', 'Jiashuo Yu', 'Peiqing Yang', 'Yuwei Guo', 'Tianxing Wu', 'Chenyang Si', 'Yuming Jiang', 'Cunjian Chen', 'Chen Change Loy', 'Bo Dai', 'Dahua Lin', 'Yu Qiao', 'Ziwei Liu'] | ['cs.CV'] | This work aims to learn a high-quality text-to-video (T2V) generative model
by leveraging a pre-trained text-to-image (T2I) model as a basis. It is a
highly desirable yet challenging task to simultaneously a) accomplish the
synthesis of visually realistic and temporally coherent videos while b)
preserving the strong cr... | 2023-09-26T17:52:03Z | Project webpage: https://vchitect.github.io/LaVie-project/ | null | null | LAVIE: High-Quality Video Generation with Cascaded Latent Diffusion Models | ['Yaohui Wang', 'Xinyuan Chen', 'Xin Ma', 'Shangchen Zhou', 'Ziqi Huang', 'Yi Wang', 'Ceyuan Yang', 'Yinan He', 'Jiashuo Yu', 'Pe-der Yang', 'Yuwei Guo', 'Tianxing Wu', 'Chenyang Si', 'Yuming Jiang', 'Cunjian Chen', 'Chen Change Loy', 'Bo Dai', 'Dahua Lin', 'Y. Qiao', 'Ziwei Liu'] | 2,023 | International Journal of Computer Vision | 231 | 76 | ['Computer Science'] |
2,309.15112 | InternLM-XComposer: A Vision-Language Large Model for Advanced
Text-image Comprehension and Composition | ['Pan Zhang', 'Xiaoyi Dong', 'Bin Wang', 'Yuhang Cao', 'Chao Xu', 'Linke Ouyang', 'Zhiyuan Zhao', 'Haodong Duan', 'Songyang Zhang', 'Shuangrui Ding', 'Wenwei Zhang', 'Hang Yan', 'Xinyue Zhang', 'Wei Li', 'Jingwen Li', 'Kai Chen', 'Conghui He', 'Xingcheng Zhang', 'Yu Qiao', 'Dahua Lin', 'Jiaqi Wang'] | ['cs.CV'] | We propose InternLM-XComposer, a vision-language large model that enables
advanced image-text comprehension and composition. The innovative nature of our
model is highlighted by three appealing properties: 1) Interleaved Text-Image
Composition: InternLM-XComposer can effortlessly generate coherent and
contextual articl... | 2023-09-26T17:58:20Z | Code and models are available at
https://github.com/InternLM/InternLM-XComposer | null | null | null | null | null | null | null | null | null |
2,309.15217 | Ragas: Automated Evaluation of Retrieval Augmented Generation | ['Shahul Es', 'Jithin James', 'Luis Espinosa-Anke', 'Steven Schockaert'] | ['cs.CL'] | We introduce Ragas (Retrieval Augmented Generation Assessment), a framework
for reference-free evaluation of Retrieval Augmented Generation (RAG)
pipelines. RAG systems are composed of a retrieval and an LLM based generation
module, and provide LLMs with knowledge from a reference textual database,
which enables them t... | 2023-09-26T19:23:54Z | Reference-free (not tied to having ground truth available) evaluation
framework for retrieval agumented generation | null | null | null | null | null | null | null | null | null |
2,309.15317 | Joint Prediction and Denoising for Large-scale Multilingual
Self-supervised Learning | ['William Chen', 'Jiatong Shi', 'Brian Yan', 'Dan Berrebbi', 'Wangyou Zhang', 'Yifan Peng', 'Xuankai Chang', 'Soumi Maiti', 'Shinji Watanabe'] | ['cs.CL', 'cs.AI', 'cs.SD', 'eess.AS'] | Multilingual self-supervised learning (SSL) has often lagged behind
state-of-the-art (SOTA) methods due to the expenses and complexity required to
handle many languages. This further harms the reproducibility of SSL, which is
already limited to few research groups due to its resource usage. We show that
more powerful t... | 2023-09-26T23:55:57Z | Accepted to ASRU 2023 | null | null | null | null | null | null | null | null | null |
2,309.15505 | Finite Scalar Quantization: VQ-VAE Made Simple | ['Fabian Mentzer', 'David Minnen', 'Eirikur Agustsson', 'Michael Tschannen'] | ['cs.CV', 'cs.LG'] | We propose to replace vector quantization (VQ) in the latent representation
of VQ-VAEs with a simple scheme termed finite scalar quantization (FSQ), where
we project the VAE representation down to a few dimensions (typically less than
10). Each dimension is quantized to a small set of fixed values, leading to an
(impli... | 2023-09-27T09:13:40Z | Code:
https://github.com/google-research/google-research/tree/master/fsq | null | null | Finite Scalar Quantization: VQ-VAE Made Simple | ['Fabian Mentzer', 'David C. Minnen', 'E. Agustsson', 'Michael Tschannen'] | 2,023 | International Conference on Learning Representations | 190 | 51 | ['Computer Science'] |
2,309.15818 | Show-1: Marrying Pixel and Latent Diffusion Models for Text-to-Video
Generation | ['David Junhao Zhang', 'Jay Zhangjie Wu', 'Jia-Wei Liu', 'Rui Zhao', 'Lingmin Ran', 'Yuchao Gu', 'Difei Gao', 'Mike Zheng Shou'] | ['cs.CV'] | Significant advancements have been achieved in the realm of large-scale
pre-trained text-to-video Diffusion Models (VDMs). However, previous methods
either rely solely on pixel-based VDMs, which come with high computational
costs, or on latent-based VDMs, which often struggle with precise text-video
alignment. In this ... | 2023-09-27T17:44:18Z | project page is https://showlab.github.io/Show-1 | null | null | null | null | null | null | null | null | null |
2,309.1602 | GeoCLIP: Clip-Inspired Alignment between Locations and Images for
Effective Worldwide Geo-localization | ['Vicente Vivanco Cepeda', 'Gaurav Kumar Nayak', 'Mubarak Shah'] | ['cs.CV', 'cs.LG'] | Worldwide Geo-localization aims to pinpoint the precise location of images
taken anywhere on Earth. This task has considerable challenges due to immense
variation in geographic landscapes. The image-to-image retrieval-based
approaches fail to solve this problem on a global scale as it is not feasible
to construct a lar... | 2023-09-27T20:54:56Z | Accepted at NeurIPS 2023 | null | null | null | null | null | null | null | null | null |
2,309.16039 | Effective Long-Context Scaling of Foundation Models | ['Wenhan Xiong', 'Jingyu Liu', 'Igor Molybog', 'Hejia Zhang', 'Prajjwal Bhargava', 'Rui Hou', 'Louis Martin', 'Rashi Rungta', 'Karthik Abinav Sankararaman', 'Barlas Oguz', 'Madian Khabsa', 'Han Fang', 'Yashar Mehdad', 'Sharan Narang', 'Kshitiz Malik', 'Angela Fan', 'Shruti Bhosale', 'Sergey Edunov', 'Mike Lewis', 'Sino... | ['cs.CL'] | We present a series of long-context LLMs that support effective context
windows of up to 32,768 tokens. Our model series are built through continual
pretraining from Llama 2 with longer training sequences and on a dataset where
long texts are upsampled. We perform extensive evaluation on language modeling,
synthetic co... | 2023-09-27T21:41:49Z | null | null | null | Effective Long-Context Scaling of Foundation Models | ['Wenhan Xiong', 'Jingyu Liu', 'Igor Molybog', 'Hejia Zhang', 'Prajjwal Bhargava', 'Rui Hou', 'Louis Martin', 'Rashi Rungta', 'Karthik Abinav Sankararaman', 'Barlas Oğuz', 'Madian Khabsa', 'Han Fang', 'Yashar Mehdad', 'Sharan Narang', 'Kshitiz Malik', 'Angela Fan', 'Shruti Bhosale', 'Sergey Edunov', 'Mike Lewis', 'Sino... | 2,023 | North American Chapter of the Association for Computational Linguistics | 231 | 66 | ['Computer Science'] |
2,309.16058 | AnyMAL: An Efficient and Scalable Any-Modality Augmented Language Model | ['Seungwhan Moon', 'Andrea Madotto', 'Zhaojiang Lin', 'Tushar Nagarajan', 'Matt Smith', 'Shashank Jain', 'Chun-Fu Yeh', 'Prakash Murugesan', 'Peyman Heidari', 'Yue Liu', 'Kavya Srinet', 'Babak Damavandi', 'Anuj Kumar'] | ['cs.LG', 'cs.CL', 'cs.CV'] | We present Any-Modality Augmented Language Model (AnyMAL), a unified model
that reasons over diverse input modality signals (i.e. text, image, video,
audio, IMU motion sensor), and generates textual responses. AnyMAL inherits the
powerful text-based reasoning abilities of the state-of-the-art LLMs including
LLaMA-2 (70... | 2023-09-27T22:50:51Z | null | null | null | null | null | null | null | null | null | null |
2,309.16287 | Predicting performance difficulty from piano sheet music images | ['Pedro Ramoneda', 'Jose J. Valero-Mas', 'Dasaem Jeong', 'Xavier Serra'] | ['cs.SD', 'cs.DL', 'eess.AS'] | Estimating the performance difficulty of a musical score is crucial in music
education for adequately designing the learning curriculum of the students.
Although the Music Information Retrieval community has recently shown interest
in this task, existing approaches mainly use machine-readable scores, leaving
the broade... | 2023-09-28T09:33:47Z | null | null | null | null | null | null | null | null | null | null |
2,309.16374 | MHG-GNN: Combination of Molecular Hypergraph Grammar with Graph Neural
Network | ['Akihiro Kishimoto', 'Hiroshi Kajino', 'Masataka Hirose', 'Junta Fuchiwaki', 'Indra Priyadarsini', 'Lisa Hamada', 'Hajime Shinohara', 'Daiju Nakano', 'Seiji Takeda'] | ['cs.LG'] | Property prediction plays an important role in material discovery. As an
initial step to eventually develop a foundation model for material science, we
introduce a new autoencoder called the MHG-GNN, which combines graph neural
network (GNN) with Molecular Hypergraph Grammar (MHG). Results on a variety of
property pred... | 2023-09-28T12:19:43Z | 8 pages, 1 figure | null | null | MHG-GNN: Combination of Molecular Hypergraph Grammar with Graph Neural Network | ['Akihiro Kishimoto', 'Hiroshi Kajino', 'Masataka Hirose', 'Junta Fuchiwaki', 'Indra Priyadarsini', 'Lisa Hamada', 'Hajime Shinohara', 'D. Nakano', 'Seiji Takeda'] | 2,023 | arXiv.org | 5 | 45 | ['Computer Science'] |
2,309.16418 | Efficient Supervised Training of Audio Transformers for Music
Representation Learning | ['Pablo Alonso-Jiménez', 'Xavier Serra', 'Dmitry Bogdanov'] | ['cs.SD', 'eess.AS'] | In this work, we address music representation learning using convolution-free
transformers. We build on top of existing spectrogram-based audio transformers
such as AST and train our models on a supervised task using patchout training
similar to PaSST. In contrast to previous works, we study how specific design
decisio... | 2023-09-28T13:11:48Z | Accepted at the 2023 International Society for Music Information
Retrieval Conference (ISMIR'23) | null | null | null | null | null | null | null | null | null |
2,309.16496 | CCEdit: Creative and Controllable Video Editing via Diffusion Models | ['Ruoyu Feng', 'Wenming Weng', 'Yanhui Wang', 'Yuhui Yuan', 'Jianmin Bao', 'Chong Luo', 'Zhibo Chen', 'Baining Guo'] | ['cs.CV'] | In this paper, we present CCEdit, a versatile generative video editing
framework based on diffusion models. Our approach employs a novel trident
network structure that separates structure and appearance control, ensuring
precise and creative editing capabilities. Utilizing the foundational
ControlNet architecture, we m... | 2023-09-28T15:03:44Z | null | null | null | CCEdit: Creative and Controllable Video Editing via Diffusion Models | ['Ruoyu Feng', 'Wenming Weng', 'Yanhui Wang', 'Yuhui Yuan', 'Jianmin Bao', 'Chong Luo', 'Zhibo Chen', 'Baining Guo'] | 2,023 | Computer Vision and Pattern Recognition | 49 | 64 | ['Computer Science'] |
2,309.16588 | Vision Transformers Need Registers | ['Timothée Darcet', 'Maxime Oquab', 'Julien Mairal', 'Piotr Bojanowski'] | ['cs.CV'] | Transformers have recently emerged as a powerful tool for learning visual
representations. In this paper, we identify and characterize artifacts in
feature maps of both supervised and self-supervised ViT networks. The artifacts
correspond to high-norm tokens appearing during inference primarily in
low-informative backg... | 2023-09-28T16:45:46Z | null | null | null | Vision Transformers Need Registers | ['Timothée Darcet', 'Maxime Oquab', 'J. Mairal', 'Piotr Bojanowski'] | 2,023 | International Conference on Learning Representations | 357 | 34 | ['Computer Science'] |
2,309.16609 | Qwen Technical Report | ['Jinze Bai', 'Shuai Bai', 'Yunfei Chu', 'Zeyu Cui', 'Kai Dang', 'Xiaodong Deng', 'Yang Fan', 'Wenbin Ge', 'Yu Han', 'Fei Huang', 'Binyuan Hui', 'Luo Ji', 'Mei Li', 'Junyang Lin', 'Runji Lin', 'Dayiheng Liu', 'Gao Liu', 'Chengqiang Lu', 'Keming Lu', 'Jianxin Ma', 'Rui Men', 'Xingzhang Ren', 'Xuancheng Ren', 'Chuanqi Ta... | ['cs.CL'] | Large language models (LLMs) have revolutionized the field of artificial
intelligence, enabling natural language processing tasks that were previously
thought to be exclusive to humans. In this work, we introduce Qwen, the first
installment of our large language model series. Qwen is a comprehensive
language model seri... | 2023-09-28T17:07:49Z | 59 pages, 5 figures | null | null | null | null | null | null | null | null | null |
2,309.16671 | Demystifying CLIP Data | ['Hu Xu', 'Saining Xie', 'Xiaoqing Ellen Tan', 'Po-Yao Huang', 'Russell Howes', 'Vasu Sharma', 'Shang-Wen Li', 'Gargi Ghosh', 'Luke Zettlemoyer', 'Christoph Feichtenhofer'] | ['cs.CV', 'cs.CL'] | Contrastive Language-Image Pre-training (CLIP) is an approach that has
advanced research and applications in computer vision, fueling modern
recognition systems and generative models. We believe that the main ingredient
to the success of CLIP is its data and not the model architecture or
pre-training objective. However... | 2023-09-28T17:59:56Z | 17 pages. arXiv admin note: text overlap with arXiv:2103.00020 by
other authors | null | null | null | null | null | null | null | null | null |
2,309.16676 | On a Seldom Oversight in Fermi's Calculations: Seventy Years Later | ['Sergei K. Suslov'] | ['physics.hist-ph'] | We discuss an unfortunate mistake, for a Dirac free particle, in the last
Fermi lecture notes on quantum mechanics, in a course given at the University
of Chicago in winter and spring of 1954. As is demonstrated, the correct result
can be obtained by a simple matrix multiplication. An attempt to collect a
relevant bibl... | 2023-07-09T17:12:09Z | 14 pages, 4 figures, 51 references | null | null | null | null | null | null | null | null | null |
2,309.16844 | DeBERTinha: A Multistep Approach to Adapt DebertaV3 XSmall for Brazilian
Portuguese Natural Language Processing Task | ['Israel Campiotti', 'Matheus Rodrigues', 'Yuri Albuquerque', 'Rafael Azevedo', 'Alyson Andrade'] | ['cs.CL'] | This paper presents an approach for adapting the DebertaV3 XSmall model
pre-trained in English for Brazilian Portuguese natural language processing
(NLP) tasks. A key aspect of the methodology involves a multistep training
process to ensure the model is effectively tuned for the Portuguese language.
Initial datasets fr... | 2023-09-28T20:53:25Z | 6 pages, 1 table | null | null | DeBERTinha: A Multistep Approach to Adapt DebertaV3 XSmall for Brazilian Portuguese Natural Language Processing Task | ['Israel Campiotti', 'Matheus Rodrigues', 'Yuri Albuquerque', 'Rafael Azevedo', 'Alyson Andrade'] | 2,023 | arXiv.org | 3 | 17 | ['Computer Science'] |
2,309.16921 | YOLOR-Based Multi-Task Learning | ['Hung-Shuo Chang', 'Chien-Yao Wang', 'Richard Robert Wang', 'Gene Chou', 'Hong-Yuan Mark Liao'] | ['cs.CV'] | Multi-task learning (MTL) aims to learn multiple tasks using a single model
and jointly improve all of them assuming generalization and shared semantics.
Reducing conflicts between tasks during joint learning is difficult and
generally requires careful network design and extremely large models. We
propose building on Y... | 2023-09-29T01:42:21Z | null | null | null | YOLOR-Based Multi-Task Learning | ['Hung-Shuo Chang', 'Chien-Yao Wang', 'Richard Robert Wang', 'Gene Chou', 'Hongpeng Liao'] | 2,023 | arXiv.org | 16 | 44 | ['Computer Science'] |
2,309.16948 | Denoising Diffusion Bridge Models | ['Linqi Zhou', 'Aaron Lou', 'Samar Khanna', 'Stefano Ermon'] | ['cs.CV', 'cs.AI'] | Diffusion models are powerful generative models that map noise to data using
stochastic processes. However, for many applications such as image editing, the
model input comes from a distribution that is not random noise. As such,
diffusion models must rely on cumbersome methods like guidance or projected
sampling to in... | 2023-09-29T03:24:24Z | Github: https://github.com/alexzhou907/DDBM/ | null | null | null | null | null | null | null | null | null |
2,309.17012 | Benchmarking Cognitive Biases in Large Language Models as Evaluators | ['Ryan Koo', 'Minhwa Lee', 'Vipul Raheja', 'Jong Inn Park', 'Zae Myung Kim', 'Dongyeop Kang'] | ['cs.CL', 'cs.AI', 'cs.LG', 'I.2.7'] | Large Language Models are cognitively biased judges. Large Language Models
(LLMs) have recently been shown to be effective as automatic evaluators with
simple prompting and in-context learning. In this work, we assemble 15 LLMs of
four different size ranges and evaluate their output responses by preference
ranking from... | 2023-09-29T06:53:10Z | Publishsed at ACL 2024. 29 pages, 9 figures, 14 tables | null | null | null | null | null | null | null | null | null |
2,309.1705 | Interpretable Long-Form Legal Question Answering with
Retrieval-Augmented Large Language Models | ['Antoine Louis', 'Gijs van Dijck', 'Gerasimos Spanakis'] | ['cs.CL'] | Many individuals are likely to face a legal dispute at some point in their
lives, but their lack of understanding of how to navigate these complex issues
often renders them vulnerable. The advancement of natural language processing
opens new avenues for bridging this legal literacy gap through the development
of automa... | 2023-09-29T08:23:19Z | Under review. Code is available at
https://github.com/maastrichtlawtech/lleqa | null | null | Interpretable Long-Form Legal Question Answering with Retrieval-Augmented Large Language Models | ['Antoine Louis', 'G. van Dijck', 'Gerasimos Spanakis'] | 2,023 | AAAI Conference on Artificial Intelligence | 41 | 90 | ['Computer Science'] |
2,309.17102 | Guiding Instruction-based Image Editing via Multimodal Large Language
Models | ['Tsu-Jui Fu', 'Wenze Hu', 'Xianzhi Du', 'William Yang Wang', 'Yinfei Yang', 'Zhe Gan'] | ['cs.CV'] | Instruction-based image editing improves the controllability and flexibility
of image manipulation via natural commands without elaborate descriptions or
regional masks. However, human instructions are sometimes too brief for current
methods to capture and follow. Multimodal large language models (MLLMs) show
promising... | 2023-09-29T10:01:50Z | ICLR'24 (Spotlight) ; Project at https://mllm-ie.github.io ; Code at
https://github.com/tsujuifu/pytorch_mgie | null | null | null | null | null | null | null | null | null |
2,309.17134 | Promoting Generalized Cross-lingual Question Answering in Few-resource
Scenarios via Self-knowledge Distillation | ['Casimiro Pio Carrino', 'Carlos Escolano', 'José A. R. Fonollosa'] | ['cs.CL'] | Despite substantial progress in multilingual extractive Question Answering
(QA), models with high and uniformly distributed performance across languages
remain challenging, especially for languages with limited resources. We study
cross-lingual transfer mainly focusing on the Generalized Cross-Lingual
Transfer (G-XLT) ... | 2023-09-29T10:54:59Z | Submitted to the Journal of Artificial Intelligence Research (JAIR) | null | null | null | null | null | null | null | null | null |
2,309.17179 | Alphazero-like Tree-Search can Guide Large Language Model Decoding and
Training | ['Xidong Feng', 'Ziyu Wan', 'Muning Wen', 'Stephen Marcus McAleer', 'Ying Wen', 'Weinan Zhang', 'Jun Wang'] | ['cs.LG', 'cs.AI', 'cs.CL'] | Recent works like Tree-of-Thought (ToT) and Reasoning via Planning (RAP) aim
to augment the reasoning capabilities of LLMs by using tree-search algorithms
to guide multi-step reasoning. These methods rely on prompting a pre-trained
model to serve as a value function and focus on problems with low search depth.
As a res... | 2023-09-29T12:20:19Z | null | null | null | null | null | null | null | null | null | null |
2,309.17207 | Memory Gym: Towards Endless Tasks to Benchmark Memory Capabilities of
Agents | ['Marco Pleines', 'Matthias Pallasch', 'Frank Zimmer', 'Mike Preuss'] | ['cs.LG'] | Memory Gym presents a suite of 2D partially observable environments, namely
Mortar Mayhem, Mystery Path, and Searing Spotlights, designed to benchmark
memory capabilities in decision-making agents. These environments, originally
with finite tasks, are expanded into innovative, endless formats, mirroring the
escalating ... | 2023-09-29T12:59:28Z | 40 pages, 12 figures, 7 tables, accepted at JMLR | null | null | null | null | null | null | null | null | null |
2,309.17352 | Improving Audio Captioning Models with Fine-grained Audio Features, Text
Embedding Supervision, and LLM Mix-up Augmentation | ['Shih-Lun Wu', 'Xuankai Chang', 'Gordon Wichern', 'Jee-weon Jung', 'François Germain', 'Jonathan Le Roux', 'Shinji Watanabe'] | ['cs.SD', 'eess.AS'] | Automated audio captioning (AAC) aims to generate informative descriptions
for various sounds from nature and/or human activities. In recent years, AAC
has quickly attracted research interest, with state-of-the-art systems now
relying on a sequence-to-sequence (seq2seq) backbone powered by strong models
such as Transfo... | 2023-09-29T15:57:46Z | ICASSP 2024 camera-ready paper. Winner of the DCASE 2023 Challenge
Task 6A: Automated Audio Captioning (AAC) | null | null | null | null | null | null | null | null | null |
2,309.17425 | Data Filtering Networks | ['Alex Fang', 'Albin Madappally Jose', 'Amit Jain', 'Ludwig Schmidt', 'Alexander Toshev', 'Vaishaal Shankar'] | ['cs.AI', 'cs.LG'] | Large training sets have become a cornerstone of machine learning and are the
foundation for recent advances in language modeling and multimodal learning.
While data curation for pre-training is often still ad-hoc, one common paradigm
is to first collect a massive pool of data from the Web and then filter this
candidat... | 2023-09-29T17:37:29Z | null | null | null | null | null | null | null | null | null | null |
2,309.17444 | LLM-grounded Video Diffusion Models | ['Long Lian', 'Baifeng Shi', 'Adam Yala', 'Trevor Darrell', 'Boyi Li'] | ['cs.CV', 'cs.AI', 'cs.CL'] | Text-conditioned diffusion models have emerged as a promising tool for neural
video generation. However, current models still struggle with intricate
spatiotemporal prompts and often generate restricted or incorrect motion. To
address these limitations, we introduce LLM-grounded Video Diffusion (LVD).
Instead of direct... | 2023-09-29T17:54:46Z | ICLR 2024. Project Page:
https://llm-grounded-video-diffusion.github.io/ | null | null | LLM-grounded Video Diffusion Models | ['Long Lian', 'Baifeng Shi', 'Adam Yala', 'Trevor Darrell', 'Boyi Li'] | 2,023 | International Conference on Learning Representations | 55 | 57 | ['Computer Science'] |
2,309.17448 | SMPLer-X: Scaling Up Expressive Human Pose and Shape Estimation | ['Zhongang Cai', 'Wanqi Yin', 'Ailing Zeng', 'Chen Wei', 'Qingping Sun', 'Yanjun Wang', 'Hui En Pang', 'Haiyi Mei', 'Mingyuan Zhang', 'Lei Zhang', 'Chen Change Loy', 'Lei Yang', 'Ziwei Liu'] | ['cs.CV'] | Expressive human pose and shape estimation (EHPS) unifies body, hands, and
face motion capture with numerous applications. Despite encouraging progress,
current state-of-the-art methods still depend largely on a confined set of
training datasets. In this work, we investigate scaling up EHPS towards the
first generalist... | 2023-09-29T17:58:06Z | Homepage: https://caizhongang.github.io/projects/SMPLer-X/ | null | null | SMPLer-X: Scaling Up Expressive Human Pose and Shape Estimation | ['Zhongang Cai', 'Wanqi Yin', 'Ailing Zeng', 'Chen Wei', 'Qingping Sun', 'Yanjun Wang', 'Hui En Pang', 'Haiyi Mei', 'Mingyuan Zhang', 'Lei Zhang', 'Chen Change Loy', 'Lei Yang', 'Ziwei Liu'] | 2,023 | Neural Information Processing Systems | 87 | 70 | ['Computer Science'] |
2,309.17452 | ToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem Solving | ['Zhibin Gou', 'Zhihong Shao', 'Yeyun Gong', 'Yelong Shen', 'Yujiu Yang', 'Minlie Huang', 'Nan Duan', 'Weizhu Chen'] | ['cs.CL', 'cs.AI'] | Large language models have made significant progress in various language
tasks, yet they still struggle with complex mathematics. In this paper, we
propose ToRA a series of Tool-integrated Reasoning Agents designed to solve
challenging mathematical problems by seamlessly integrating natural language
reasoning with the ... | 2023-09-29T17:59:38Z | ICLR 2024; First two authors equal contribution | null | null | ToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem Solving | ['Zhibin Gou', 'Zhihong Shao', 'Yeyun Gong', 'Yelong Shen', 'Yujiu Yang', 'Minlie Huang', 'Nan Duan', 'Weizhu Chen'] | 2,023 | International Conference on Learning Representations | 168 | 85 | ['Computer Science'] |
2,309.17453 | Efficient Streaming Language Models with Attention Sinks | ['Guangxuan Xiao', 'Yuandong Tian', 'Beidi Chen', 'Song Han', 'Mike Lewis'] | ['cs.CL', 'cs.AI'] | Deploying Large Language Models (LLMs) in streaming applications such as
multi-round dialogue, where long interactions are expected, is urgently needed
but poses two major challenges. Firstly, during the decoding stage, caching
previous tokens' Key and Value states (KV) consumes extensive memory. Secondly,
popular LLMs... | 2023-09-29T17:59:56Z | ICLR 2024 | null | null | null | null | null | null | null | null | null |
2,310.0012 | Multi-Grid Tensorized Fourier Neural Operator for High-Resolution PDEs | ['Jean Kossaifi', 'Nikola Kovachki', 'Kamyar Azizzadenesheli', 'Anima Anandkumar'] | ['cs.LG'] | Memory complexity and data scarcity have so far prohibited learning solution
operators of partial differential equations (PDEs) at high resolutions. We
address these limitations by introducing a new data efficient and highly
parallelizable operator learning approach with reduced memory requirement and
better generaliza... | 2023-09-29T20:18:52Z | null | null | null | null | null | null | null | null | null | null |
2,310.00274 | AfriSpeech-200: Pan-African Accented Speech Dataset for Clinical and
General Domain ASR | ['Tobi Olatunji', 'Tejumade Afonja', 'Aditya Yadavalli', 'Chris Chinenye Emezue', 'Sahib Singh', 'Bonaventure F. P. Dossou', 'Joanne Osuchukwu', 'Salomey Osei', 'Atnafu Lambebo Tonja', 'Naome Etori', 'Clinton Mbataku'] | ['cs.CL'] | Africa has a very low doctor-to-patient ratio. At very busy clinics, doctors
could see 30+ patients per day -- a heavy patient burden compared with
developed countries -- but productivity tools such as clinical automatic speech
recognition (ASR) are lacking for these overworked clinicians. However,
clinical ASR is matu... | 2023-09-30T06:38:43Z | Accepted to TACL 2023. This is a pre-MIT Press publication version | null | null | AfriSpeech-200: Pan-African Accented Speech Dataset for Clinical and General Domain ASR | ['Tobi Olatunji', 'Tejumade Afonja', 'Aditya Yadavalli', 'Chris Chinenye Emezue', 'Sahib Singh', 'Bonaventure F. P. Dossou', 'Joanne I. Osuchukwu', 'Salomey Osei', 'A. Tonja', 'Naome A. Etori', 'Clinton Mbataku'] | 2,023 | Transactions of the Association for Computational Linguistics | 19 | 80 | ['Computer Science'] |
2,310.00426 | PixArt-$α$: Fast Training of Diffusion Transformer for
Photorealistic Text-to-Image Synthesis | ['Junsong Chen', 'Jincheng Yu', 'Chongjian Ge', 'Lewei Yao', 'Enze Xie', 'Yue Wu', 'Zhongdao Wang', 'James Kwok', 'Ping Luo', 'Huchuan Lu', 'Zhenguo Li'] | ['cs.CV'] | The most advanced text-to-image (T2I) models require significant training
costs (e.g., millions of GPU hours), seriously hindering the fundamental
innovation for the AIGC community while increasing CO2 emissions. This paper
introduces PIXART-$\alpha$, a Transformer-based T2I diffusion model whose image
generation quali... | 2023-09-30T16:18:00Z | Project Page: https://pixart-alpha.github.io | null | null | PixArt-α: Fast Training of Diffusion Transformer for Photorealistic Text-to-Image Synthesis | ['Junsong Chen', 'Jincheng Yu', 'Chongjian Ge', 'Lewei Yao', 'Enze Xie', 'Yue Wu', 'Zhongdao Wang', 'James T. Kwok', 'Ping Luo', 'Huchuan Lu', 'Zhenguo Li'] | 2,023 | International Conference on Learning Representations | 460 | 79 | ['Computer Science'] |
2,310.00566 | Empowering Many, Biasing a Few: Generalist Credit Scoring through Large
Language Models | ['Duanyu Feng', 'Yongfu Dai', 'Jimin Huang', 'Yifang Zhang', 'Qianqian Xie', 'Weiguang Han', 'Zhengyu Chen', 'Alejandro Lopez-Lira', 'Hao Wang'] | ['cs.LG', 'cs.AI', 'cs.CL', 'cs.CY'] | In the financial industry, credit scoring is a fundamental element, shaping
access to credit and determining the terms of loans for individuals and
businesses alike. Traditional credit scoring methods, however, often grapple
with challenges such as narrow knowledge scope and isolated evaluation of
credit tasks. Our wor... | 2023-10-01T03:50:34Z | null | null | null | Empowering Many, Biasing a Few: Generalist Credit Scoring through Large Language Models | ['Duanyu Feng', 'Yongfu Dai', 'Jimin Huang', 'Yifang Zhang', 'Qianqian Xie', 'Weiguang Han', 'Alejandro Lopez-Lira', 'Hao Wang'] | 2,023 | arXiv.org | 12 | 79 | ['Computer Science'] |
2,310.00673 | Learning Type Inference for Enhanced Dataflow Analysis | ['Lukas Seidel', 'Sedick David Baker Effendi', 'Xavier Pinho', 'Konrad Rieck', 'Brink van der Merwe', 'Fabian Yamaguchi'] | ['cs.LG', 'cs.CR'] | Statically analyzing dynamically-typed code is a challenging endeavor, as
even seemingly trivial tasks such as determining the targets of procedure calls
are non-trivial without knowing the types of objects at compile time.
Addressing this challenge, gradual typing is increasingly added to
dynamically-typed languages, ... | 2023-10-01T13:52:28Z | - fixed last author's name - fixed header | 28th European Symposium on Research in Computer Security (ESORICS)
2023 | null | Learning Type Inference for Enhanced Dataflow Analysis | ['Lukas Seidel', 'Sedick Baker Effendi', 'Xavier Pinho', 'Konrad Rieck', 'Brink van der Merwe', 'Fabian Yamaguchi'] | 2,023 | European Symposium on Research in Computer Security | 2 | 46 | ['Computer Science'] |
2,310.00752 | TIGERScore: Towards Building Explainable Metric for All Text Generation
Tasks | ['Dongfu Jiang', 'Yishan Li', 'Ge Zhang', 'Wenhao Huang', 'Bill Yuchen Lin', 'Wenhu Chen'] | ['cs.CL', 'cs.AI'] | We present TIGERScore, a \textbf{T}rained metric that follows
\textbf{I}nstruction \textbf{G}uidance to perform \textbf{E}xplainable, and
\textbf{R}eference-free evaluation over a wide spectrum of text generation
tasks. Different from other automatic evaluation methods that only provide
arcane scores, TIGERScore is gui... | 2023-10-01T18:01:51Z | null | null | null | null | null | null | null | null | null | null |
2,310.00796 | SIP: Injecting a Structural Inductive Bias into a Seq2Seq Model by
Simulation | ['Matthias Lindemann', 'Alexander Koller', 'Ivan Titov'] | ['cs.CL'] | Strong inductive biases enable learning from little data and help
generalization outside of the training distribution. Popular neural
architectures such as Transformers lack strong structural inductive biases for
seq2seq NLP tasks on their own. Consequently, they struggle with systematic
generalization beyond the train... | 2023-10-01T21:19:12Z | ACL 2024 camera-ready | null | null | Injecting a Structural Inductive Bias into a Seq2Seq Model by Simulation | ['Matthias Lindemann', 'Alexander Koller', 'Ivan Titov'] | 2,023 | Annual Meeting of the Association for Computational Linguistics | 5 | 52 | ['Computer Science'] |
2,310.01018 | Controlling Vision-Language Models for Multi-Task Image Restoration | ['Ziwei Luo', 'Fredrik K. Gustafsson', 'Zheng Zhao', 'Jens Sjölund', 'Thomas B. Schön'] | ['cs.CV'] | Vision-language models such as CLIP have shown great impact on diverse
downstream tasks for zero-shot or label-free predictions. However, when it
comes to low-level vision such as image restoration their performance
deteriorates dramatically due to corrupted inputs. In this paper, we present a
degradation-aware vision-... | 2023-10-02T09:10:16Z | Accepted by ICLR 2024. Project page:
https://algolzw.github.io/daclip-uir/index.html | null | null | null | null | null | null | null | null | null |
2,310.01045 | Tool-Augmented Reward Modeling | ['Lei Li', 'Yekun Chai', 'Shuohuan Wang', 'Yu Sun', 'Hao Tian', 'Ningyu Zhang', 'Hua Wu'] | ['cs.CL'] | Reward modeling (a.k.a., preference modeling) is instrumental for aligning
large language models with human preferences, particularly within the context
of reinforcement learning from human feedback (RLHF). While conventional reward
models (RMs) have exhibited remarkable scalability, they oft struggle with
fundamental ... | 2023-10-02T09:47:40Z | ICLR 2024 Spotlight | null | null | Tool-Augmented Reward Modeling | ['Lei Li', 'Yekun Chai', 'Shuohuan Wang', 'Yu Sun', 'Hao Tian', 'Ningyu Zhang', 'Hua Wu'] | 2,023 | International Conference on Learning Representations | 14 | 52 | ['Computer Science'] |
2,310.01074 | Back to the Future: Towards Explainable Temporal Reasoning with Large
Language Models | ['Chenhan Yuan', 'Qianqian Xie', 'Jimin Huang', 'Sophia Ananiadou'] | ['cs.CL', 'cs.AI'] | Temporal reasoning is a crucial NLP task, providing a nuanced understanding
of time-sensitive contexts within textual data. Although recent advancements in
LLMs have demonstrated their potential in temporal reasoning, the predominant
focus has been on tasks such as temporal expression and temporal relation
extraction. ... | 2023-10-02T10:35:23Z | 14 pages, 5 figures, code and dataset:
https://github.com/chenhan97/TimeLlama | null | null | null | null | null | null | null | null | null |
2,310.01119 | Synthetic Data Generation in Low-Resource Settings via Fine-Tuning of
Large Language Models | ['Jean Kaddour', 'Qi Liu'] | ['cs.CL', 'cs.LG'] | The in-context learning ability of large language models (LLMs) enables them
to generalize to novel downstream tasks with relatively few labeled examples.
However, they require enormous computational resources to be deployed.
Alternatively, smaller models can solve specific tasks if fine-tuned with
enough labeled examp... | 2023-10-02T11:49:05Z | null | null | null | Synthetic Data Generation in Low-Resource Settings via Fine-Tuning of Large Language Models | ['Jean Kaddour', 'Qi Liu'] | 2,023 | null | 2 | 38 | ['Computer Science'] |
2,310.01188 | Quantifying the Plausibility of Context Reliance in Neural Machine
Translation | ['Gabriele Sarti', 'Grzegorz Chrupała', 'Malvina Nissim', 'Arianna Bisazza'] | ['cs.CL', 'cs.AI', 'cs.HC', 'cs.LG', 'I.2.7'] | Establishing whether language models can use contextual information in a
human-plausible way is important to ensure their trustworthiness in real-world
settings. However, the questions of when and which parts of the context affect
model generations are typically tackled separately, with current plausibility
evaluations... | 2023-10-02T13:26:43Z | ICLR 2024 Camera Ready. Code: https://github.com/gsarti/pecore.
Artifacts:
https://huggingface.co/collections/gsarti/pecore-iclr-2024-65edab42e28439e21b612c2e | null | null | Quantifying the Plausibility of Context Reliance in Neural Machine Translation | ['Gabriele Sarti', 'Grzegorz Chrupała', 'M. Nissim', 'Arianna Bisazza'] | 2,023 | International Conference on Learning Representations | 5 | 79 | ['Computer Science'] |
2,310.01208 | Label Supervised LLaMA Finetuning | ['Zongxi Li', 'Xianming Li', 'Yuzhang Liu', 'Haoran Xie', 'Jing Li', 'Fu-lee Wang', 'Qing Li', 'Xiaoqin Zhong'] | ['cs.CL'] | The recent success of Large Language Models (LLMs) has gained significant
attention in both academia and industry. Substantial efforts have been made to
enhance the zero- and few-shot generalization capabilities of open-source LLMs
through finetuning. Currently, the prevailing approach is instruction-tuning,
which trai... | 2023-10-02T13:53:03Z | null | null | null | Label Supervised LLaMA Finetuning | ['Zongxi Li', 'Xianming Li', 'Yuzhang Liu', 'Haoran Xie', 'Jing Li', 'F. Wang', 'Qing Li', 'Xiaoqin Zhong'] | 2,023 | arXiv.org | 23 | 31 | ['Computer Science'] |
2,310.0121 | Towards Robust Cardiac Segmentation using Graph Convolutional Networks | ['Gilles Van De Vyver', 'Sarina Thomas', 'Guy Ben-Yosef', 'Sindre Hellum Olaisen', 'Håvard Dalen', 'Lasse Løvstakken', 'Erik Smistad'] | ['eess.IV', 'cs.CV', 'cs.LG'] | Fully automatic cardiac segmentation can be a fast and reproducible method to
extract clinical measurements from an echocardiography examination. The U-Net
architecture is the current state-of-the-art deep learning architecture for
medical segmentation and can segment cardiac structures in real-time with
average errors... | 2023-10-02T13:55:06Z | This work has been submitted to the IEEE for possible publication | null | null | null | null | null | null | null | null | null |
2,310.01218 | Making LLaMA SEE and Draw with SEED Tokenizer | ['Yuying Ge', 'Sijie Zhao', 'Ziyun Zeng', 'Yixiao Ge', 'Chen Li', 'Xintao Wang', 'Ying Shan'] | ['cs.CV'] | The great success of Large Language Models (LLMs) has expanded the potential
of multimodality, contributing to the gradual evolution of General Artificial
Intelligence (AGI). A true AGI agent should not only possess the capability to
perform predefined multi-tasks but also exhibit emergent abilities in an
open-world co... | 2023-10-02T14:03:02Z | Project released at: https://github.com/AILab-CVC/SEED. arXiv admin
note: substantial text overlap with arXiv:2307.08041 | null | null | null | null | null | null | null | null | null |
2,310.01324 | ZeroI2V: Zero-Cost Adaptation of Pre-trained Transformers from Image to
Video | ['Xinhao Li', 'Yuhan Zhu', 'Limin Wang'] | ['cs.CV'] | Adapting image models to the video domain has emerged as an efficient
paradigm for solving video recognition tasks. Due to the huge number of
parameters and effective transferability of image models, performing full
fine-tuning is less efficient and even unnecessary. Thus, recent research is
shifting its focus toward p... | 2023-10-02T16:41:20Z | Accepted by ECCV2024 | null | null | ZeroI2V: Zero-Cost Adaptation of Pre-trained Transformers from Image to Video | ['Xinhao Li', 'Limin Wang'] | 2,023 | European Conference on Computer Vision | 9 | 87 | ['Computer Science'] |
2,310.01377 | UltraFeedback: Boosting Language Models with Scaled AI Feedback | ['Ganqu Cui', 'Lifan Yuan', 'Ning Ding', 'Guanming Yao', 'Bingxiang He', 'Wei Zhu', 'Yuan Ni', 'Guotong Xie', 'Ruobing Xie', 'Yankai Lin', 'Zhiyuan Liu', 'Maosong Sun'] | ['cs.CL', 'cs.AI', 'cs.LG'] | Learning from human feedback has become a pivot technique in aligning large
language models (LLMs) with human preferences. However, acquiring vast and
premium human feedback is bottlenecked by time, labor, and human capability,
resulting in small sizes or limited topics of current datasets. This further
hinders feedbac... | 2023-10-02T17:40:01Z | ICML 2024 camera ready | null | null | UltraFeedback: Boosting Language Models with High-quality Feedback | ['Ganqu Cui', 'Lifan Yuan', 'Ning Ding', 'Guanming Yao', 'Wei Zhu', 'Yuan Ni', 'Guotong Xie', 'Zhiyuan Liu', 'Maosong Sun'] | 2,023 | International Conference on Machine Learning | 413 | 81 | ['Computer Science'] |
2,310.01596 | ImagenHub: Standardizing the evaluation of conditional image generation
models | ['Max Ku', 'Tianle Li', 'Kai Zhang', 'Yujie Lu', 'Xingyu Fu', 'Wenwen Zhuang', 'Wenhu Chen'] | ['cs.CV', 'cs.GR', 'cs.MM'] | Recently, a myriad of conditional image generation and editing models have
been developed to serve different downstream tasks, including text-to-image
generation, text-guided image editing, subject-driven image generation,
control-guided image generation, etc. However, we observe huge inconsistencies
in experimental co... | 2023-10-02T19:41:42Z | Accepted to ICLR2024 Camera Ready | null | null | null | null | null | null | null | null | null |
2,310.01602 | CAT-LM: Training Language Models on Aligned Code And Tests | ['Nikitha Rao', 'Kush Jain', 'Uri Alon', 'Claire Le Goues', 'Vincent J. Hellendoorn'] | ['cs.SE', 'cs.AI'] | Testing is an integral part of the software development process. Yet, writing
tests is time-consuming and therefore often neglected. Classical test
generation tools such as EvoSuite generate behavioral test suites by optimizing
for coverage, but tend to produce tests that are hard to understand. Language
models trained... | 2023-10-02T19:52:22Z | null | null | null | CAT-LM Training Language Models on Aligned Code And Tests | ['Nikitha Rao', 'Kush Jain', 'Uri Alon', 'Claire Le Goues', 'Vincent J. Hellendoorn'] | 2,023 | International Conference on Automated Software Engineering | 47 | 52 | ['Computer Science'] |
2,310.01809 | Mel-Band RoFormer for Music Source Separation | ['Ju-Chiang Wang', 'Wei-Tsung Lu', 'Minz Won'] | ['cs.SD', 'eess.AS'] | Recently, multi-band spectrogram-based approaches such as Band-Split RNN
(BSRNN) have demonstrated promising results for music source separation. In our
recent work, we introduce the BS-RoFormer model which inherits the idea of
band-split scheme in BSRNN at the front-end, and then uses the hierarchical
Transformer with... | 2023-10-03T05:53:23Z | submitted as an ISMIR 2023 late-breaking and demo paper | null | null | null | null | null | null | null | null | null |
2,310.01852 | LanguageBind: Extending Video-Language Pretraining to N-modality by
Language-based Semantic Alignment | ['Bin Zhu', 'Bin Lin', 'Munan Ning', 'Yang Yan', 'Jiaxi Cui', 'HongFa Wang', 'Yatian Pang', 'Wenhao Jiang', 'Junwu Zhang', 'Zongwei Li', 'Wancai Zhang', 'Zhifeng Li', 'Wei Liu', 'Li Yuan'] | ['cs.CV', 'cs.AI'] | The video-language (VL) pretraining has achieved remarkable improvement in
multiple downstream tasks. However, the current VL pretraining framework is
hard to extend to multiple modalities (N modalities, N>=3) beyond vision and
language. We thus propose LanguageBind, taking the language as the bind across
different mod... | 2023-10-03T07:33:27Z | Accepted by ICLR 2024 | null | null | LanguageBind: Extending Video-Language Pretraining to N-modality by Language-based Semantic Alignment | ['Bin Zhu', 'Bin Lin', 'Munan Ning', 'Yang Yan', 'Jiaxi Cui', 'Hongfa Wang', 'Yatian Pang', 'Wenhao Jiang', 'Junwu Zhang', 'Zongwei Li', 'Wancai Zhang', 'Zhifeng Li', 'Wei Liu', 'Liejie Yuan'] | 2,023 | International Conference on Learning Representations | 229 | 76 | ['Computer Science'] |
2,310.01889 | Ring Attention with Blockwise Transformers for Near-Infinite Context | ['Hao Liu', 'Matei Zaharia', 'Pieter Abbeel'] | ['cs.CL'] | Transformers have emerged as the architecture of choice for many
state-of-the-art AI models, showcasing exceptional performance across a wide
range of AI applications. However, the memory demands imposed by Transformers
limit their ability to handle long sequences, thereby posing challenges in
utilizing videos, actions... | 2023-10-03T08:44:50Z | Code: https://github.com/lhao499/llm_large_context | null | null | Ring Attention with Blockwise Transformers for Near-Infinite Context | ['Hao Liu', 'Matei Zaharia', 'Pieter Abbeel'] | 2,023 | International Conference on Learning Representations | 258 | 44 | ['Computer Science'] |
2,310.02031 | OceanGPT: A Large Language Model for Ocean Science Tasks | ['Zhen Bi', 'Ningyu Zhang', 'Yida Xue', 'Yixin Ou', 'Daxiong Ji', 'Guozhou Zheng', 'Huajun Chen'] | ['cs.CL', 'cs.AI', 'cs.CE', 'cs.LG', 'cs.RO'] | Ocean science, which delves into the oceans that are reservoirs of life and
biodiversity, is of great significance given that oceans cover over 70% of our
planet's surface. Recently, advances in Large Language Models (LLMs) have
transformed the paradigm in science. Despite the success in other domains,
current LLMs oft... | 2023-10-03T13:17:35Z | ACL2024. Project Website: http://oceangpt.zjukg.cn/ | null | null | null | null | null | null | null | null | null |
2,310.02074 | ACE: A fast, skillful learned global atmospheric model for climate
prediction | ['Oliver Watt-Meyer', 'Gideon Dresdner', 'Jeremy McGibbon', 'Spencer K. Clark', 'Brian Henn', 'James Duncan', 'Noah D. Brenowitz', 'Karthik Kashinath', 'Michael S. Pritchard', 'Boris Bonev', 'Matthew E. Peters', 'Christopher S. Bretherton'] | ['physics.ao-ph', 'cs.LG'] | Existing ML-based atmospheric models are not suitable for climate prediction,
which requires long-term stability and physical consistency. We present ACE
(AI2 Climate Emulator), a 200M-parameter, autoregressive machine learning
emulator of an existing comprehensive 100-km resolution global atmospheric
model. The formul... | 2023-10-03T14:15:06Z | Accepted at Tackling Climate Change with Machine Learning: workshop
at NeurIPS 2023 | null | null | ACE: A fast, skillful learned global atmospheric model for climate prediction | ['Oliver Watt‐Meyer', 'Gideon Dresdner', 'J. McGibbon', 'Spencer K. Clark', 'Brian Henn', 'James P. C. Duncan', 'Noah D. Brenowitz', 'K. Kashinath', 'Michael S. Pritchard', 'B. Bonev', 'Matthew E. Peters', 'Christopher S. Bretherton'] | 2,023 | arXiv.org | 47 | 25 | ['Physics', 'Computer Science'] |
2,310.02575 | AdaMerging: Adaptive Model Merging for Multi-Task Learning | ['Enneng Yang', 'Zhenyi Wang', 'Li Shen', 'Shiwei Liu', 'Guibing Guo', 'Xingwei Wang', 'Dacheng Tao'] | ['cs.LG', 'cs.CV'] | Multi-task learning (MTL) aims to empower a model to tackle multiple tasks
simultaneously. A recent development known as task arithmetic has revealed that
several models, each fine-tuned for distinct tasks, can be directly merged into
a single model to execute MTL without necessitating a retraining process using
the in... | 2023-10-04T04:26:33Z | International Conference on Learning Representations (ICLR 2024) | null | null | AdaMerging: Adaptive Model Merging for Multi-Task Learning | ['Enneng Yang', 'Zhenyi Wang', 'Li Shen', 'Shiwei Liu', 'Guibing Guo', 'Xingwei Wang', 'Dacheng Tao'] | 2,023 | International Conference on Learning Representations | 125 | 87 | ['Computer Science'] |
2,310.02601 | MagicDrive: Street View Generation with Diverse 3D Geometry Control | ['Ruiyuan Gao', 'Kai Chen', 'Enze Xie', 'Lanqing Hong', 'Zhenguo Li', 'Dit-Yan Yeung', 'Qiang Xu'] | ['cs.CV', 'cs.AI'] | Recent advancements in diffusion models have significantly enhanced the data
synthesis with 2D control. Yet, precise 3D control in street view generation,
crucial for 3D perception tasks, remains elusive. Specifically, utilizing
Bird's-Eye View (BEV) as the primary condition often leads to challenges in
geometry contro... | 2023-10-04T06:14:06Z | Project Page: https://flymin.github.io/magicdrive; Figure 7 updated | null | null | null | null | null | null | null | null | null |
2,310.02743 | Reward Model Ensembles Help Mitigate Overoptimization | ['Thomas Coste', 'Usman Anwar', 'Robert Kirk', 'David Krueger'] | ['cs.LG'] | Reinforcement learning from human feedback (RLHF) is a standard approach for
fine-tuning large language models to follow instructions. As part of this
process, learned reward models are used to approximately model human
preferences. However, as imperfect representations of the "true" reward, these
learned reward models... | 2023-10-04T11:34:22Z | Accepted at ICLR 2024 | null | null | Reward Model Ensembles Help Mitigate Overoptimization | ['Thomas Coste', 'Usman Anwar', 'Robert Kirk', 'D. Krueger'] | 2,023 | International Conference on Learning Representations | 139 | 55 | ['Computer Science'] |
2,310.03024 | AstroCLIP: A Cross-Modal Foundation Model for Galaxies | ['Liam Parker', 'Francois Lanusse', 'Siavash Golkar', 'Leopoldo Sarra', 'Miles Cranmer', 'Alberto Bietti', 'Michael Eickenberg', 'Geraud Krawezik', 'Michael McCabe', 'Ruben Ohana', 'Mariel Pettee', 'Bruno Regaldo-Saint Blancard', 'Tiberiu Tesileanu', 'Kyunghyun Cho', 'Shirley Ho'] | ['astro-ph.IM', 'cs.AI', 'cs.LG'] | We present AstroCLIP, a single, versatile model that can embed both galaxy
images and spectra into a shared, physically meaningful latent space. These
embeddings can then be used - without any model fine-tuning - for a variety of
downstream tasks including (1) accurate in-modality and cross-modality semantic
similarity... | 2023-10-04T17:59:38Z | 18 pages, accepted in Monthly Notices of the Royal Astronomical
Society, Presented at the NeurIPS 2023 AI4Science Workshop | null | 10.1093/mnras/stae1450 | null | null | null | null | null | null | null |
2,310.03269 | InstructProtein: Aligning Human and Protein Language via Knowledge
Instruction | ['Zeyuan Wang', 'Qiang Zhang', 'Keyan Ding', 'Ming Qin', 'Xiang Zhuang', 'Xiaotong Li', 'Huajun Chen'] | ['q-bio.BM', 'cs.CL'] | Large Language Models (LLMs) have revolutionized the field of natural
language processing, but they fall short in comprehending biological sequences
such as proteins. To address this challenge, we propose InstructProtein, an
innovative LLM that possesses bidirectional generation capabilities in both
human and protein l... | 2023-10-05T02:45:39Z | null | null | null | null | null | null | null | null | null | null |
2,310.03477 | Tik-to-Tok: Translating Language Models One Token at a Time: An
Embedding Initialization Strategy for Efficient Language Adaptation | ['François Remy', 'Pieter Delobelle', 'Bettina Berendt', 'Kris Demuynck', 'Thomas Demeester'] | ['cs.CL', 'cs.AI'] | Training monolingual language models for low and mid-resource languages is
made challenging by limited and often inadequate pretraining data. In this
study, we propose a novel model conversion strategy to address this issue,
adapting high-resources monolingual language models to a new target language.
By generalizing o... | 2023-10-05T11:45:29Z | As first reviewed at TACL | null | null | null | null | null | null | null | null | null |
2,310.03668 | GoLLIE: Annotation Guidelines improve Zero-Shot Information-Extraction | ['Oscar Sainz', 'Iker García-Ferrero', 'Rodrigo Agerri', 'Oier Lopez de Lacalle', 'German Rigau', 'Eneko Agirre'] | ['cs.CL'] | Large Language Models (LLMs) combined with instruction tuning have made
significant progress when generalizing to unseen tasks. However, they have been
less successful in Information Extraction (IE), lagging behind task-specific
models. Typically, IE tasks are characterized by complex annotation guidelines
that describ... | 2023-10-05T16:43:13Z | The Twelfth International Conference on Learning Representations -
ICLR 2024 | null | null | null | null | null | null | null | null | null |
2,310.03708 | Beyond One-Preference-Fits-All Alignment: Multi-Objective Direct
Preference Optimization | ['Zhanhui Zhou', 'Jie Liu', 'Jing Shao', 'Xiangyu Yue', 'Chao Yang', 'Wanli Ouyang', 'Yu Qiao'] | ['cs.LG', 'cs.AI'] | A single language model, even when aligned with labelers through
reinforcement learning from human feedback (RLHF), may not suit all human
preferences. Recent approaches therefore prefer customization, gathering
multi-dimensional feedback, and creating distinct reward models for each
dimension. Different language model... | 2023-10-05T17:35:26Z | Findings of ACL 2024 | null | null | null | null | null | null | null | null | null |
2,310.03731 | MathCoder: Seamless Code Integration in LLMs for Enhanced Mathematical
Reasoning | ['Ke Wang', 'Houxing Ren', 'Aojun Zhou', 'Zimu Lu', 'Sichun Luo', 'Weikang Shi', 'Renrui Zhang', 'Linqi Song', 'Mingjie Zhan', 'Hongsheng Li'] | ['cs.CL', 'cs.AI', 'cs.CV', 'cs.LG'] | The recently released GPT-4 Code Interpreter has demonstrated remarkable
proficiency in solving challenging math problems, primarily attributed to its
ability to seamlessly reason with natural language, generate code, execute
code, and continue reasoning based on the execution output. In this paper, we
present a method... | 2023-10-05T17:52:09Z | The state-of-the-art open-source language models for mathematical
reasoning | null | null | null | null | null | null | null | null | null |
2,310.03739 | Aligning Text-to-Image Diffusion Models with Reward Backpropagation | ['Mihir Prabhudesai', 'Anirudh Goyal', 'Deepak Pathak', 'Katerina Fragkiadaki'] | ['cs.CV', 'cs.AI', 'cs.LG', 'cs.RO'] | Text-to-image diffusion models have recently emerged at the forefront of
image generation, powered by very large-scale unsupervised or weakly supervised
text-to-image training datasets. Due to their unsupervised training,
controlling their behavior in downstream tasks, such as maximizing
human-perceived image quality, ... | 2023-10-05T17:59:18Z | This paper is subsumed by a later paper of ours: arXiv:2407.08737 | null | null | Aligning Text-to-Image Diffusion Models with Reward Backpropagation | ['Mihir Prabhudesai', 'Anirudh Goyal', 'Deepak Pathak', 'Katerina Fragkiadaki'] | 2,023 | arXiv.org | 133 | 55 | ['Computer Science'] |
2,310.03744 | Improved Baselines with Visual Instruction Tuning | ['Haotian Liu', 'Chunyuan Li', 'Yuheng Li', 'Yong Jae Lee'] | ['cs.CV', 'cs.AI', 'cs.CL', 'cs.LG'] | Large multimodal models (LMM) have recently shown encouraging progress with
visual instruction tuning. In this note, we show that the fully-connected
vision-language cross-modal connector in LLaVA is surprisingly powerful and
data-efficient. With simple modifications to LLaVA, namely, using
CLIP-ViT-L-336px with an MLP... | 2023-10-05T17:59:56Z | Camera ready, CVPR 2024 (highlight). LLaVA project page:
https://llava-vl.github.io | null | null | Improved Baselines with Visual Instruction Tuning | ['Haotian Liu', 'Chunyuan Li', 'Yuheng Li', 'Yong Jae Lee'] | 2,023 | Computer Vision and Pattern Recognition | 2,834 | 71 | ['Computer Science'] |
2,310.03842 | PepMLM: Target Sequence-Conditioned Generation of Therapeutic Peptide
Binders via Span Masked Language Modeling | ['Tianlai Chen', 'Madeleine Dumas', 'Rio Watson', 'Sophia Vincoff', 'Christina Peng', 'Lin Zhao', 'Lauren Hong', 'Sarah Pertsemlidis', 'Mayumi Shaepers-Cheu', 'Tian Zi Wang', 'Divya Srijay', 'Connor Monticello', 'Pranay Vure', 'Rishab Pulugurta', 'Kseniia Kholina', 'Shrey Goel', 'Matthew P. DeLisa', 'Ray Truant', 'Hect... | ['q-bio.BM'] | Target proteins that lack accessible binding pockets and conformational
stability have posed increasing challenges for drug development. Induced
proximity strategies, such as PROTACs and molecular glues, have thus gained
attention as pharmacological alternatives, but still require small molecule
docking at binding pock... | 2023-10-05T18:59:51Z | null | null | null | PepMLM: Target Sequence-Conditioned Generation of Therapeutic Peptide Binders via Span Masked Language Modeling | ['Tianlai Chen', 'Madeleine Dumas', 'Rio Watson', 'Sophia Vincoff', 'Christina Peng', 'Lin Zhao', 'Lauren Hong', 'Sarah Pertsemlidis', 'Mayumi Shaepers-Cheu', 'Tian Wang', 'Divya Srijay', 'Connor Monticello', 'Pranay Vure', 'Rishab Pulugurta', 'Kseniia Kholina', 'Shrey Goel', 'M. DeLisa', 'R. Truant', 'Hector C. Aguila... | 2,023 | arXiv.org | 18 | 53 | ['Biology', 'Medicine'] |
2,310.04378 | Latent Consistency Models: Synthesizing High-Resolution Images with
Few-Step Inference | ['Simian Luo', 'Yiqin Tan', 'Longbo Huang', 'Jian Li', 'Hang Zhao'] | ['cs.CV', 'cs.LG'] | Latent Diffusion models (LDMs) have achieved remarkable results in
synthesizing high-resolution images. However, the iterative sampling process is
computationally intensive and leads to slow generation. Inspired by Consistency
Models (song et al.), we propose Latent Consistency Models (LCMs), enabling
swift inference w... | 2023-10-06T17:11:58Z | null | null | null | Latent Consistency Models: Synthesizing High-Resolution Images with Few-Step Inference | ['Simian Luo', 'Yiqin Tan', 'Longbo Huang', 'Jian Li', 'Hang Zhao'] | 2,023 | arXiv.org | 479 | 38 | ['Computer Science'] |
2,310.04418 | Functional Interpolation for Relative Positions Improves Long Context
Transformers | ['Shanda Li', 'Chong You', 'Guru Guruganesh', 'Joshua Ainslie', 'Santiago Ontanon', 'Manzil Zaheer', 'Sumit Sanghai', 'Yiming Yang', 'Sanjiv Kumar', 'Srinadh Bhojanapalli'] | ['cs.LG'] | Preventing the performance decay of Transformers on inputs longer than those
used for training has been an important challenge in extending the context
length of these models. Though the Transformer architecture has fundamentally
no limits on the input sequence lengths it can process, the choice of position
encoding us... | 2023-10-06T17:59:11Z | 26 pages; ICLR 2024 camera ready version | null | null | null | null | null | null | null | null | null |
2,310.04484 | Ada-Instruct: Adapting Instruction Generators for Complex Reasoning | ['Wanyun Cui', 'Qianle Wang'] | ['cs.CL', 'cs.AI'] | Instructions augmentation is a crucial step for unleashing the full potential
of large language models (LLMs) in downstream tasks. Existing Self-Instruct
methods primarily simulate new instructions from a few initial instructions
with in-context learning. However, our study identifies a critical flaw in this
approach: ... | 2023-10-06T13:28:04Z | null | null | null | null | null | null | null | null | null | null |
2,310.04562 | Towards Foundation Models for Knowledge Graph Reasoning | ['Mikhail Galkin', 'Xinyu Yuan', 'Hesham Mostafa', 'Jian Tang', 'Zhaocheng Zhu'] | ['cs.CL', 'cs.AI'] | Foundation models in language and vision have the ability to run inference on
any textual and visual inputs thanks to the transferable representations such
as a vocabulary of tokens in language. Knowledge graphs (KGs) have different
entity and relation vocabularies that generally do not overlap. The key
challenge of de... | 2023-10-06T20:00:07Z | ICLR 2024 | null | null | null | null | null | null | null | null | null |
2,310.04564 | ReLU Strikes Back: Exploiting Activation Sparsity in Large Language
Models | ['Iman Mirzadeh', 'Keivan Alizadeh', 'Sachin Mehta', 'Carlo C Del Mundo', 'Oncel Tuzel', 'Golnoosh Samei', 'Mohammad Rastegari', 'Mehrdad Farajtabar'] | ['cs.LG', 'cs.AI'] | Large Language Models (LLMs) with billions of parameters have drastically
transformed AI applications. However, their demanding computation during
inference has raised significant challenges for deployment on
resource-constrained devices. Despite recent trends favoring alternative
activation functions such as GELU or S... | 2023-10-06T20:01:33Z | preprint | null | null | null | null | null | null | null | null | null |
2,310.04799 | Chat Vector: A Simple Approach to Equip LLMs with Instruction Following
and Model Alignment in New Languages | ['Shih-Cheng Huang', 'Pin-Zu Li', 'Yu-Chi Hsu', 'Kuang-Ming Chen', 'Yu Tung Lin', 'Shih-Kai Hsiao', 'Richard Tzong-Han Tsai', 'Hung-yi Lee'] | ['cs.CL'] | Recently, the development of open-source large language models (LLMs) has
advanced rapidly. Nevertheless, due to data constraints, the capabilities of
most open-source LLMs are primarily focused on English. To address this issue,
we introduce the concept of $\textit{chat vector}$ to equip pre-trained
language models wi... | 2023-10-07T13:34:21Z | ACL 2024 camera-ready version | null | null | Chat Vector: A Simple Approach to Equip LLMs with Instruction Following and Model Alignment in New Languages | ['Shih-Cheng Huang', 'Pin-Zu Li', 'Yu-Chi Hsu', 'Kuang-Ming Chen', 'Yu Tung Lin', 'Shih-Kai Hsiao', 'Richard Tzong-Han Tsai', 'Hung-yi Lee'] | 2,023 | Annual Meeting of the Association for Computational Linguistics | 17 | 39 | ['Computer Science'] |
2,310.04901 | WAIT: Feature Warping for Animation to Illustration video Translation
using GANs | ['Samet Hicsonmez', 'Nermin Samet', 'Fidan Samet', 'Oguz Bakir', 'Emre Akbas', 'Pinar Duygulu'] | ['cs.CV'] | In this paper, we explore a new domain for video-to-video translation.
Motivated by the availability of animation movies that are adopted from
illustrated books for children, we aim to stylize these videos with the style
of the original illustrations. Current state-of-the-art video-to-video
translation models rely on h... | 2023-10-07T19:45:24Z | Accepted to Neurocomputing | null | null | null | null | null | null | null | null | null |
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