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2,306.02928 | LRVS-Fashion: Extending Visual Search with Referring Instructions | ['Simon Lepage', 'Jérémie Mary', 'David Picard'] | ['cs.CV', '68T07 (Primary) 68T45 (Secondary)', 'I.2.10'] | This paper introduces a new challenge for image similarity search in the
context of fashion, addressing the inherent ambiguity in this domain stemming
from complex images. We present Referred Visual Search (RVS), a task allowing
users to define more precisely the desired similarity, following recent
interest in the ind... | 2023-06-05T14:45:38Z | 29 pages, 14 figures, 5 tables | null | null | null | null | null | null | null | null | null |
2,306.0303 | Benchmarking Large Language Models on CMExam -- A Comprehensive Chinese
Medical Exam Dataset | ['Junling Liu', 'Peilin Zhou', 'Yining Hua', 'Dading Chong', 'Zhongyu Tian', 'Andrew Liu', 'Helin Wang', 'Chenyu You', 'Zhenhua Guo', 'Lei Zhu', 'Michael Lingzhi Li'] | ['cs.CL'] | Recent advancements in large language models (LLMs) have transformed the
field of question answering (QA). However, evaluating LLMs in the medical field
is challenging due to the lack of standardized and comprehensive datasets. To
address this gap, we introduce CMExam, sourced from the Chinese National
Medical Licensin... | 2023-06-05T16:48:41Z | Accepted by NeurIPS 2023 Datasets and Benchmarks Track | null | null | null | null | null | null | null | null | null |
2,306.03268 | Skill over Scale: The Case for Medium, Domain-Specific Models for SE | ['Manisha Mukherjee', 'Vincent J. Hellendoorn'] | ['cs.CL', 'cs.SE'] | Recent advancements in AI have sparked a trend in constructing large,
generalist language models that handle a multitude of tasks, including many
code-related ones. While these models are expensive to train and are often
closed-source, they have enjoyed broad adoption because they tend to outperform
smaller, domain-spe... | 2023-06-05T21:38:30Z | null | null | null | null | null | null | null | null | null | null |
2,306.03341 | Inference-Time Intervention: Eliciting Truthful Answers from a Language
Model | ['Kenneth Li', 'Oam Patel', 'Fernanda Viégas', 'Hanspeter Pfister', 'Martin Wattenberg'] | ['cs.LG', 'cs.AI', 'cs.CL'] | We introduce Inference-Time Intervention (ITI), a technique designed to
enhance the "truthfulness" of large language models (LLMs). ITI operates by
shifting model activations during inference, following a set of directions
across a limited number of attention heads. This intervention significantly
improves the performa... | 2023-06-06T01:26:53Z | NeurIPS 2023 spotlight; code:
https://github.com/likenneth/honest_llama | null | null | null | null | null | null | null | null | null |
2,306.0335 | Click: Controllable Text Generation with Sequence Likelihood Contrastive
Learning | ['Chujie Zheng', 'Pei Ke', 'Zheng Zhang', 'Minlie Huang'] | ['cs.CL'] | It has always been an important yet challenging problem to control language
models to avoid generating texts with undesirable attributes, such as toxic
language and unnatural repetition. We introduce Click for controllable text
generation, which needs no modification to the model architecture and
facilitates out-of-the... | 2023-06-06T01:56:44Z | Findings of ACL 2023 | null | null | null | null | null | null | null | null | null |
2,306.03423 | I'm Afraid I Can't Do That: Predicting Prompt Refusal in Black-Box
Generative Language Models | ['Max Reuter', 'William Schulze'] | ['cs.AI'] | Since the release of OpenAI's ChatGPT, generative language models have
attracted extensive public attention. The increased usage has highlighted
generative models' broad utility, but also revealed several forms of embedded
bias. Some is induced by the pre-training corpus; but additional bias specific
to generative mode... | 2023-06-06T05:50:58Z | Submitted for review to KDD 2023 via the workshop "Foundations and
Applications in Large-scale AI Models: Pre-training, Fine-tuning, and
Prompt-based Learning" | null | null | null | null | null | null | null | null | null |
2,306.03514 | Recognize Anything: A Strong Image Tagging Model | ['Youcai Zhang', 'Xinyu Huang', 'Jinyu Ma', 'Zhaoyang Li', 'Zhaochuan Luo', 'Yanchun Xie', 'Yuzhuo Qin', 'Tong Luo', 'Yaqian Li', 'Shilong Liu', 'Yandong Guo', 'Lei Zhang'] | ['cs.CV'] | We present the Recognize Anything Model (RAM): a strong foundation model for
image tagging. RAM makes a substantial step for large models in computer
vision, demonstrating the zero-shot ability to recognize any common category
with high accuracy. RAM introduces a new paradigm for image tagging, leveraging
large-scale i... | 2023-06-06T09:00:10Z | Homepage: https://recognize-anything.github.io/ | null | null | null | null | null | null | null | null | null |
2,306.03767 | Metal artefact reduction sequences for a piezoelectric bone conduction
implant using a realistic head phantom in MRI | ['Guy Fierens', 'Joris Walraevens', 'Ronald Peeters', 'Christ Glorieux', 'Nicolas Verhaert'] | ['physics.med-ph'] | Industry standards require medical device manufacturers to perform
implant-induced artefact testing in phantoms at a pre-clinical stage to define
the extent of artefacts that can be expected during MRI. Once a device is
commercially available, studies on volunteers, cadavers or patients are
performed to investigate imp... | 2023-06-06T15:28:52Z | 22 pages, 12 figures including supplementary information | null | null | null | null | null | null | null | null | null |
2,306.03809 | Can large language models democratize access to dual-use biotechnology? | ['Emily H. Soice', 'Rafael Rocha', 'Kimberlee Cordova', 'Michael Specter', 'Kevin M. Esvelt'] | ['cs.CY', 'cs.AI'] | Large language models (LLMs) such as those embedded in 'chatbots' are
accelerating and democratizing research by providing comprehensible information
and expertise from many different fields. However, these models may also confer
easy access to dual-use technologies capable of inflicting great harm. To
evaluate this ri... | 2023-06-06T15:52:05Z | 6 pages, 0 figures | null | null | null | null | null | null | null | null | null |
2,306.03819 | LEACE: Perfect linear concept erasure in closed form | ['Nora Belrose', 'David Schneider-Joseph', 'Shauli Ravfogel', 'Ryan Cotterell', 'Edward Raff', 'Stella Biderman'] | ['cs.LG', 'cs.CL', 'cs.CY'] | Concept erasure aims to remove specified features from an embedding. It can
improve fairness (e.g. preventing a classifier from using gender or race) and
interpretability (e.g. removing a concept to observe changes in model
behavior). We introduce LEAst-squares Concept Erasure (LEACE), a closed-form
method which provab... | 2023-06-06T16:07:24Z | null | null | null | null | null | null | null | null | null | null |
2,306.04054 | RescueSpeech: A German Corpus for Speech Recognition in Search and
Rescue Domain | ['Sangeet Sagar', 'Mirco Ravanelli', 'Bernd Kiefer', 'Ivana Kruijff Korbayova', 'Josef van Genabith'] | ['eess.AS', 'cs.LG', 'cs.SD', 'eess.SP'] | Despite the recent advancements in speech recognition, there are still
difficulties in accurately transcribing conversational and emotional speech in
noisy and reverberant acoustic environments. This poses a particular challenge
in the search and rescue (SAR) domain, where transcribing conversations among
rescue team m... | 2023-06-06T23:04:22Z | null | null | null | null | null | null | null | null | null | null |
2,306.04306 | Allophant: Cross-lingual Phoneme Recognition with Articulatory
Attributes | ['Kevin Glocker', 'Aaricia Herygers', 'Munir Georges'] | ['cs.CL', 'cs.SD', 'eess.AS', 'I.2.7'] | This paper proposes Allophant, a multilingual phoneme recognizer. It requires
only a phoneme inventory for cross-lingual transfer to a target language,
allowing for low-resource recognition. The architecture combines a
compositional phone embedding approach with individually supervised phonetic
attribute classifiers in... | 2023-06-07T10:11:09Z | 5 pages, 2 figures, 2 tables, accepted to INTERSPEECH 2023; published
version | Proc. INTERSPEECH 2023, 2258-2262 | 10.21437/Interspeech.2023-772 | null | null | null | null | null | null | null |
2,306.04387 | M$^3$IT: A Large-Scale Dataset towards Multi-Modal Multilingual
Instruction Tuning | ['Lei Li', 'Yuwei Yin', 'Shicheng Li', 'Liang Chen', 'Peiyi Wang', 'Shuhuai Ren', 'Mukai Li', 'Yazheng Yang', 'Jingjing Xu', 'Xu Sun', 'Lingpeng Kong', 'Qi Liu'] | ['cs.CV', 'cs.CL'] | Instruction tuning has significantly advanced large language models (LLMs)
such as ChatGPT, enabling them to align with human instructions across diverse
tasks. However, progress in open vision-language models (VLMs) has been limited
due to the scarcity of high-quality instruction datasets. To tackle this
challenge and... | 2023-06-07T12:35:37Z | Fix dataset url: https://huggingface.co/datasets/MMInstruction/M3IT
Project: https://m3-it.github.io/ | null | null | null | null | null | null | null | null | null |
2,306.04399 | Transfer Learning of Transformer-based Speech Recognition Models from
Czech to Slovak | ['Jan Lehečka', 'Josef V. Psutka', 'Josef Psutka'] | ['cs.CL'] | In this paper, we are comparing several methods of training the Slovak speech
recognition models based on the Transformers architecture. Specifically, we are
exploring the approach of transfer learning from the existing Czech pre-trained
Wav2Vec 2.0 model into Slovak. We are demonstrating the benefits of the
proposed a... | 2023-06-07T12:58:46Z | Accepted to TSD 2023 | Text, Speech, and Dialogue: 26th International Conference, TSD
2023 | 10.1007/978-3-031-40498-6_29 | Transfer Learning of Transformer-based Speech Recognition Models from Czech to Slovak | ['Jan Lehecka', 'J. Psutka', 'J. Psutka'] | 2,023 | International Conference on Text, Speech and Dialogue | 2 | 18 | ['Computer Science'] |
2,306.04488 | Rewarded soups: towards Pareto-optimal alignment by interpolating
weights fine-tuned on diverse rewards | ['Alexandre Ramé', 'Guillaume Couairon', 'Mustafa Shukor', 'Corentin Dancette', 'Jean-Baptiste Gaya', 'Laure Soulier', 'Matthieu Cord'] | ['cs.LG', 'cs.AI', 'cs.CV'] | Foundation models are first pre-trained on vast unsupervised datasets and
then fine-tuned on labeled data. Reinforcement learning, notably from human
feedback (RLHF), can further align the network with the intended usage. Yet the
imperfections in the proxy reward may hinder the training and lead to
suboptimal results; ... | 2023-06-07T14:58:15Z | null | null | null | null | null | null | null | null | null | null |
2,306.04527 | ContriMix: Scalable stain color augmentation for domain generalization
without domain labels in digital pathology | ['Tan H. Nguyen', 'Dinkar Juyal', 'Jin Li', 'Aaditya Prakash', 'Shima Nofallah', 'Chintan Shah', 'Sai Chowdary Gullapally', 'Limin Yu', 'Michael Griffin', 'Anand Sampat', 'John Abel', 'Justin Lee', 'Amaro Taylor-Weiner'] | ['eess.IV', 'cs.CV', 'cs.LG'] | Differences in staining and imaging procedures can cause significant color
variations in histopathology images, leading to poor generalization when
deploying deep-learning models trained from a different data source. Various
color augmentation methods have been proposed to generate synthetic images
during training to m... | 2023-06-07T15:36:26Z | null | null | null | null | null | null | null | null | null | null |
2,306.04632 | Designing a Better Asymmetric VQGAN for StableDiffusion | ['Zixin Zhu', 'Xuelu Feng', 'Dongdong Chen', 'Jianmin Bao', 'Le Wang', 'Yinpeng Chen', 'Lu Yuan', 'Gang Hua'] | ['cs.CV', 'cs.GR'] | StableDiffusion is a revolutionary text-to-image generator that is causing a
stir in the world of image generation and editing. Unlike traditional methods
that learn a diffusion model in pixel space, StableDiffusion learns a diffusion
model in the latent space via a VQGAN, ensuring both efficiency and quality. It
not o... | 2023-06-07T17:56:02Z | code is available at
https://github.com/buxiangzhiren/Asymmetric_VQGAN | null | null | null | null | null | null | null | null | null |
2,306.0464 | ModuleFormer: Modularity Emerges from Mixture-of-Experts | ['Yikang Shen', 'Zheyu Zhang', 'Tianyou Cao', 'Shawn Tan', 'Zhenfang Chen', 'Chuang Gan'] | ['cs.CL', 'cs.AI', 'cs.LG'] | Large Language Models (LLMs) have achieved remarkable results. However,
existing models are expensive to train and deploy, and it is also difficult to
expand their knowledge beyond pre-training data without forgetting previous
knowledge. This paper proposes a new neural network architecture, ModuleFormer,
that leverage... | 2023-06-07T17:59:57Z | null | null | null | null | null | null | null | null | null | null |
2,306.04675 | Exposing flaws of generative model evaluation metrics and their unfair
treatment of diffusion models | ['George Stein', 'Jesse C. Cresswell', 'Rasa Hosseinzadeh', 'Yi Sui', 'Brendan Leigh Ross', 'Valentin Villecroze', 'Zhaoyan Liu', 'Anthony L. Caterini', 'J. Eric T. Taylor', 'Gabriel Loaiza-Ganem'] | ['cs.LG', 'cs.CV', 'stat.ML'] | We systematically study a wide variety of generative models spanning
semantically-diverse image datasets to understand and improve the feature
extractors and metrics used to evaluate them. Using best practices in
psychophysics, we measure human perception of image realism for generated
samples by conducting the largest... | 2023-06-07T18:00:00Z | NeurIPS 2023. 53 pages, 29 figures, 12 tables. Code at
https://github.com/layer6ai-labs/dgm-eval, reviews at
https://openreview.net/forum?id=08zf7kTOoh | Thirty-seventh Conference on Neural Information Processing Systems
(2023) | null | null | null | null | null | null | null | null |
2,306.04751 | How Far Can Camels Go? Exploring the State of Instruction Tuning on Open
Resources | ['Yizhong Wang', 'Hamish Ivison', 'Pradeep Dasigi', 'Jack Hessel', 'Tushar Khot', 'Khyathi Raghavi Chandu', 'David Wadden', 'Kelsey MacMillan', 'Noah A. Smith', 'Iz Beltagy', 'Hannaneh Hajishirzi'] | ['cs.CL'] | In this work we explore recent advances in instruction-tuning language models
on a range of open instruction-following datasets. Despite recent claims that
open models can be on par with state-of-the-art proprietary models, these
claims are often accompanied by limited evaluation, making it difficult to
compare models ... | 2023-06-07T19:59:23Z | 18 pages, 6 figure, 10 tables. NeurIPS 2023 Datasets and Benchmarks
Track Camera Ready | null | null | null | null | null | null | null | null | null |
2,306.04757 | INSTRUCTEVAL: Towards Holistic Evaluation of Instruction-Tuned Large
Language Models | ['Yew Ken Chia', 'Pengfei Hong', 'Lidong Bing', 'Soujanya Poria'] | ['cs.CL', 'cs.AI'] | Instruction-tuned large language models have revolutionized natural language
processing and have shown great potential in applications such as
conversational agents. These models, such as GPT-4, can not only master
language but also solve complex tasks in areas like mathematics, coding,
medicine, and law. Despite their... | 2023-06-07T20:12:29Z | Github: https://github.com/declare-lab/instruct-eval Leaderboard:
https://declare-lab.github.io/instruct-eval/ | null | null | null | null | null | null | null | null | null |
2,306.05087 | PandaLM: An Automatic Evaluation Benchmark for LLM Instruction Tuning
Optimization | ['Yidong Wang', 'Zhuohao Yu', 'Zhengran Zeng', 'Linyi Yang', 'Cunxiang Wang', 'Hao Chen', 'Chaoya Jiang', 'Rui Xie', 'Jindong Wang', 'Xing Xie', 'Wei Ye', 'Shikun Zhang', 'Yue Zhang'] | ['cs.CL', 'cs.AI'] | Instruction tuning large language models (LLMs) remains a challenging task,
owing to the complexity of hyperparameter selection and the difficulty involved
in evaluating the tuned models. To determine the optimal hyperparameters, an
automatic, robust, and reliable evaluation benchmark is essential. However,
establishin... | 2023-06-08T10:41:56Z | Accepted by ICLR 2024 | null | null | PandaLM: An Automatic Evaluation Benchmark for LLM Instruction Tuning Optimization | ['Yidong Wang', 'Zhuohao Yu', 'Zhengran Zeng', 'Linyi Yang', 'Cunxiang Wang', 'Hao Chen', 'Chaoya Jiang', 'Rui Xie', 'Jindong Wang', 'Xingxu Xie', 'Wei Ye', 'Shi-Bo Zhang', 'Yue Zhang'] | 2,023 | International Conference on Learning Representations | 249 | 90 | ['Computer Science'] |
2,306.05179 | M3Exam: A Multilingual, Multimodal, Multilevel Benchmark for Examining
Large Language Models | ['Wenxuan Zhang', 'Sharifah Mahani Aljunied', 'Chang Gao', 'Yew Ken Chia', 'Lidong Bing'] | ['cs.CL', 'cs.CV'] | Despite the existence of various benchmarks for evaluating natural language
processing models, we argue that human exams are a more suitable means of
evaluating general intelligence for large language models (LLMs), as they
inherently demand a much wider range of abilities such as language
understanding, domain knowled... | 2023-06-08T13:21:29Z | NeurIPS 2023 (Datasets and Benchmarks) | null | null | M3Exam: A Multilingual, Multimodal, Multilevel Benchmark for Examining Large Language Models | ['Wenxuan Zhang', 'Sharifah Mahani Aljunied', 'Chang Gao', 'Yew Ken Chia', 'Lidong Bing'] | 2,023 | Neural Information Processing Systems | 87 | 45 | ['Computer Science'] |
2,306.05284 | Simple and Controllable Music Generation | ['Jade Copet', 'Felix Kreuk', 'Itai Gat', 'Tal Remez', 'David Kant', 'Gabriel Synnaeve', 'Yossi Adi', 'Alexandre Défossez'] | ['cs.SD', 'cs.AI', 'cs.LG', 'eess.AS'] | We tackle the task of conditional music generation. We introduce MusicGen, a
single Language Model (LM) that operates over several streams of compressed
discrete music representation, i.e., tokens. Unlike prior work, MusicGen is
comprised of a single-stage transformer LM together with efficient token
interleaving patte... | 2023-06-08T15:31:05Z | Published at Neurips 2023 | null | null | null | null | null | null | null | null | null |
2,306.05301 | ToolAlpaca: Generalized Tool Learning for Language Models with 3000
Simulated Cases | ['Qiaoyu Tang', 'Ziliang Deng', 'Hongyu Lin', 'Xianpei Han', 'Qiao Liang', 'Boxi Cao', 'Le Sun'] | ['cs.CL'] | Enabling large language models to utilize real-world tools effectively is
crucial for achieving embodied intelligence. Existing approaches to tool
learning have either primarily relied on extremely large language models, such
as GPT-4, to attain generalized tool-use abilities in a zero-shot manner, or
utilized supervis... | 2023-06-08T15:46:32Z | null | null | null | null | null | null | null | null | null | null |
2,306.05399 | Matting Anything | ['Jiachen Li', 'Jitesh Jain', 'Humphrey Shi'] | ['cs.CV'] | In this paper, we propose the Matting Anything Model (MAM), an efficient and
versatile framework for estimating the alpha matte of any instance in an image
with flexible and interactive visual or linguistic user prompt guidance. MAM
offers several significant advantages over previous specialized image matting
networks:... | 2023-06-08T17:51:58Z | Project web-page:
https://chrisjuniorli.github.io/project/Matting-Anything/ | null | null | null | null | null | null | null | null | null |
2,306.05423 | ADDP: Learning General Representations for Image Recognition and
Generation with Alternating Denoising Diffusion Process | ['Changyao Tian', 'Chenxin Tao', 'Jifeng Dai', 'Hao Li', 'Ziheng Li', 'Lewei Lu', 'Xiaogang Wang', 'Hongsheng Li', 'Gao Huang', 'Xizhou Zhu'] | ['cs.CV'] | Image recognition and generation have long been developed independently of
each other. With the recent trend towards general-purpose representation
learning, the development of general representations for both recognition and
generation tasks is also promoted. However, preliminary attempts mainly focus
on generation pe... | 2023-06-08T17:59:32Z | Accepted by ICLR2024 | null | null | null | null | null | null | null | null | null |
2,306.05425 | MIMIC-IT: Multi-Modal In-Context Instruction Tuning | ['Bo Li', 'Yuanhan Zhang', 'Liangyu Chen', 'Jinghao Wang', 'Fanyi Pu', 'Jingkang Yang', 'Chunyuan Li', 'Ziwei Liu'] | ['cs.CV', 'cs.AI', 'cs.CL', 'cs.HC'] | High-quality instructions and responses are essential for the zero-shot
performance of large language models on interactive natural language tasks. For
interactive vision-language tasks involving intricate visual scenes, a large
quantity of diverse and creative instruction-response pairs should be
imperative to tune vi... | 2023-06-08T17:59:56Z | Project page: https://otter-ntu.github.io/ Dataset & code:
https://github.com/Luodian/otter Initial release, work in progress | null | null | MIMIC-IT: Multi-Modal In-Context Instruction Tuning | ['Bo Li', 'Yuanhan Zhang', 'Liangyu Chen', 'Jinghao Wang', 'Fanyi Pu', 'Jingkang Yang', 'C. Li', 'Ziwei Liu'] | 2,023 | arXiv.org | 240 | 55 | ['Computer Science'] |
2,306.05443 | PIXIU: A Large Language Model, Instruction Data and Evaluation Benchmark
for Finance | ['Qianqian Xie', 'Weiguang Han', 'Xiao Zhang', 'Yanzhao Lai', 'Min Peng', 'Alejandro Lopez-Lira', 'Jimin Huang'] | ['cs.CL', 'cs.AI'] | Although large language models (LLMs) has shown great performance on natural
language processing (NLP) in the financial domain, there are no publicly
available financial tailtored LLMs, instruction tuning datasets, and evaluation
benchmarks, which is critical for continually pushing forward the open-source
development ... | 2023-06-08T14:20:29Z | 12 pages, 1 figures | null | null | null | null | null | null | null | null | null |
2,306.05685 | Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena | ['Lianmin Zheng', 'Wei-Lin Chiang', 'Ying Sheng', 'Siyuan Zhuang', 'Zhanghao Wu', 'Yonghao Zhuang', 'Zi Lin', 'Zhuohan Li', 'Dacheng Li', 'Eric P. Xing', 'Hao Zhang', 'Joseph E. Gonzalez', 'Ion Stoica'] | ['cs.CL', 'cs.AI'] | Evaluating large language model (LLM) based chat assistants is challenging
due to their broad capabilities and the inadequacy of existing benchmarks in
measuring human preferences. To address this, we explore using strong LLMs as
judges to evaluate these models on more open-ended questions. We examine the
usage and lim... | 2023-06-09T05:55:52Z | NeurIPS 2023 Datasets and Benchmarks Track | null | null | null | null | null | null | null | null | null |
2,306.06081 | Carefully Blending Adversarial Training, Purification, and Aggregation
Improves Adversarial Robustness | ['Emanuele Ballarin', 'Alessio Ansuini', 'Luca Bortolussi'] | ['cs.CV', 'cs.AI', 'cs.CR', 'cs.LG'] | In this work, we propose a novel adversarial defence mechanism for image
classification - CARSO - blending the paradigms of adversarial training and
adversarial purification in a synergistic robustness-enhancing way. The method
builds upon an adversarially-trained classifier, and learns to map its internal
representati... | 2023-05-25T09:04:31Z | 25 pages, 1 figure, 16 tables | null | null | Carefully Blending Adversarial Training, Purification, and Aggregation Improves Adversarial Robustness | ['Emanuele Ballarin', 'A. Ansuini', 'L. Bortolussi'] | 2,023 | null | 0 | 71 | ['Computer Science'] |
2,306.06189 | FasterViT: Fast Vision Transformers with Hierarchical Attention | ['Ali Hatamizadeh', 'Greg Heinrich', 'Hongxu Yin', 'Andrew Tao', 'Jose M. Alvarez', 'Jan Kautz', 'Pavlo Molchanov'] | ['cs.CV', 'cs.AI', 'cs.LG'] | We design a new family of hybrid CNN-ViT neural networks, named FasterViT,
with a focus on high image throughput for computer vision (CV) applications.
FasterViT combines the benefits of fast local representation learning in CNNs
and global modeling properties in ViT. Our newly introduced Hierarchical
Attention (HAT) a... | 2023-06-09T18:41:37Z | ICLR'24 Accepted Paper | null | null | FasterViT: Fast Vision Transformers with Hierarchical Attention | ['Ali Hatamizadeh', 'Greg Heinrich', 'Hongxu Yin', 'Andrew Tao', 'J. Álvarez', 'J. Kautz', 'Pavlo Molchanov'] | 2,023 | International Conference on Learning Representations | 72 | 83 | ['Computer Science'] |
2,306.06289 | SegViTv2: Exploring Efficient and Continual Semantic Segmentation with
Plain Vision Transformers | ['Bowen Zhang', 'Liyang Liu', 'Minh Hieu Phan', 'Zhi Tian', 'Chunhua Shen', 'Yifan Liu'] | ['cs.CV'] | This paper investigates the capability of plain Vision Transformers (ViTs)
for semantic segmentation using the encoder-decoder framework and introduces
\textbf{SegViTv2}. In this study, we introduce a novel Attention-to-Mask (\atm)
module to design a lightweight decoder effective for plain ViT. The proposed
ATM convert... | 2023-06-09T22:29:56Z | IJCV 2023 accepted, 21 pages, 8 figures, 12 tables | null | null | SegViTv2: Exploring Efficient and Continual Semantic Segmentation with Plain Vision Transformers | ['Bowen Zhang', 'Liyang Liu', 'Minh-Hieu Phan', 'Zhi Tian', 'Chunhua Shen', 'Yifan Liu'] | 2,023 | International Journal of Computer Vision | 30 | 95 | ['Computer Science'] |
2,306.06482 | TensorNet: Cartesian Tensor Representations for Efficient Learning of
Molecular Potentials | ['Guillem Simeon', 'Gianni de Fabritiis'] | ['cs.LG', 'physics.chem-ph', 'physics.comp-ph'] | The development of efficient machine learning models for molecular systems
representation is becoming crucial in scientific research. We introduce
TensorNet, an innovative O(3)-equivariant message-passing neural network
architecture that leverages Cartesian tensor representations. By using
Cartesian tensor atomic embed... | 2023-06-10T16:41:18Z | NeurIPS 2023, camera-ready version | null | null | null | null | null | null | null | null | null |
2,306.06546 | High-Fidelity Audio Compression with Improved RVQGAN | ['Rithesh Kumar', 'Prem Seetharaman', 'Alejandro Luebs', 'Ishaan Kumar', 'Kundan Kumar'] | ['cs.SD', 'cs.LG', 'eess.AS'] | Language models have been successfully used to model natural signals, such as
images, speech, and music. A key component of these models is a high quality
neural compression model that can compress high-dimensional natural signals
into lower dimensional discrete tokens. To that end, we introduce a
high-fidelity univers... | 2023-06-11T00:13:00Z | Accepted at NeurIPS 2023 (spotlight) | null | null | High-Fidelity Audio Compression with Improved RVQGAN | ['Rithesh Kumar', 'Prem Seetharaman', 'Alejandro Luebs', 'I. Kumar', 'Kundan Kumar'] | 2,023 | Neural Information Processing Systems | 338 | 47 | ['Computer Science', 'Engineering'] |
2,306.06687 | LAMM: Language-Assisted Multi-Modal Instruction-Tuning Dataset,
Framework, and Benchmark | ['Zhenfei Yin', 'Jiong Wang', 'Jianjian Cao', 'Zhelun Shi', 'Dingning Liu', 'Mukai Li', 'Lu Sheng', 'Lei Bai', 'Xiaoshui Huang', 'Zhiyong Wang', 'Jing Shao', 'Wanli Ouyang'] | ['cs.CV'] | Large language models have emerged as a promising approach towards achieving
general-purpose AI agents. The thriving open-source LLM community has greatly
accelerated the development of agents that support human-machine dialogue
interaction through natural language processing. However, human interaction
with the world ... | 2023-06-11T14:01:17Z | NeurIPS2023 camera ready ; 37 pages, 33 figures. Code available at
https://github.com/OpenLAMM/LAMM ; Project page: https://openlamm.github.io/ | null | null | null | null | null | null | null | null | null |
2,306.06851 | UniPoll: A Unified Social Media Poll Generation Framework via
Multi-Objective Optimization | ['Yixia Li', 'Rong Xiang', 'Yanlin Song', 'Jing Li'] | ['cs.CL'] | Social media platforms are vital for expressing opinions and understanding
public sentiment, yet many analytical tools overlook passive users who mainly
consume content without engaging actively. To address this, we introduce
UniPoll, an advanced framework designed to automatically generate polls from
social media post... | 2023-06-12T03:54:04Z | Accepted by IEEE Transactions on Neural Networks and Learning
Systems. Project page is live at https://uni-poll.github.io . Code are
available at https://github.com/X1AOX1A/UniPoll | null | 10.1109/TNNLS.2024.3512868 | null | null | null | null | null | null | null |
2,306.07174 | Augmenting Language Models with Long-Term Memory | ['Weizhi Wang', 'Li Dong', 'Hao Cheng', 'Xiaodong Liu', 'Xifeng Yan', 'Jianfeng Gao', 'Furu Wei'] | ['cs.CL'] | Existing large language models (LLMs) can only afford fix-sized inputs due to
the input length limit, preventing them from utilizing rich long-context
information from past inputs. To address this, we propose a framework, Language
Models Augmented with Long-Term Memory (LongMem), which enables LLMs to
memorize long his... | 2023-06-12T15:13:39Z | null | null | null | null | null | null | null | null | null | null |
2,306.07197 | AROID: Improving Adversarial Robustness Through Online Instance-Wise
Data Augmentation | ['Lin Li', 'Jianing Qiu', 'Michael Spratling'] | ['cs.CV', 'cs.AI', 'cs.LG'] | Deep neural networks are vulnerable to adversarial examples. Adversarial
training (AT) is an effective defense against adversarial examples. However, AT
is prone to overfitting which degrades robustness substantially. Recently, data
augmentation (DA) was shown to be effective in mitigating robust overfitting if
appropr... | 2023-06-12T15:54:52Z | published at the IJCV in press | null | null | null | null | null | null | null | null | null |
2,306.0728 | Controlling Text-to-Image Diffusion by Orthogonal Finetuning | ['Zeju Qiu', 'Weiyang Liu', 'Haiwen Feng', 'Yuxuan Xue', 'Yao Feng', 'Zhen Liu', 'Dan Zhang', 'Adrian Weller', 'Bernhard Schölkopf'] | ['cs.CV', 'cs.AI', 'cs.GR', 'cs.LG'] | Large text-to-image diffusion models have impressive capabilities in
generating photorealistic images from text prompts. How to effectively guide or
control these powerful models to perform different downstream tasks becomes an
important open problem. To tackle this challenge, we introduce a principled
finetuning metho... | 2023-06-12T17:59:23Z | NeurIPS 2023 (v3: fixed formula typos in Section 3.5, 43 pages, 34
figures, project page: https://oft.wyliu.com/) | null | null | Controlling Text-to-Image Diffusion by Orthogonal Finetuning | ['Zeju Qiu', 'Wei-yu Liu', 'Haiwen Feng', 'Yuxuan Xue', 'Yao Feng', 'Zhen Liu', 'Dan Zhang', 'Adrian Weller', 'B. Scholkopf'] | 2,023 | Neural Information Processing Systems | 159 | 71 | ['Computer Science'] |
2,306.07373 | EriBERTa: A Bilingual Pre-Trained Language Model for Clinical Natural
Language Processing | ['Iker de la Iglesia', 'Aitziber Atutxa', 'Koldo Gojenola', 'Ander Barrena'] | ['cs.CL'] | The utilization of clinical reports for various secondary purposes, including
health research and treatment monitoring, is crucial for enhancing patient
care. Natural Language Processing (NLP) tools have emerged as valuable assets
for extracting and processing relevant information from these reports. However,
the avail... | 2023-06-12T18:56:25Z | null | null | null | null | null | null | null | null | null | null |
2,306.07629 | SqueezeLLM: Dense-and-Sparse Quantization | ['Sehoon Kim', 'Coleman Hooper', 'Amir Gholami', 'Zhen Dong', 'Xiuyu Li', 'Sheng Shen', 'Michael W. Mahoney', 'Kurt Keutzer'] | ['cs.CL', 'cs.LG'] | Generative Large Language Models (LLMs) have demonstrated remarkable results
for a wide range of tasks. However, deploying these models for inference has
been a significant challenge due to their unprecedented resource requirements.
This has forced existing deployment frameworks to use multi-GPU inference
pipelines, wh... | 2023-06-13T08:57:54Z | ICML 2024 | null | null | null | null | null | null | null | null | null |
2,306.07691 | StyleTTS 2: Towards Human-Level Text-to-Speech through Style Diffusion
and Adversarial Training with Large Speech Language Models | ['Yinghao Aaron Li', 'Cong Han', 'Vinay S. Raghavan', 'Gavin Mischler', 'Nima Mesgarani'] | ['eess.AS', 'cs.AI', 'cs.CL', 'cs.LG', 'cs.SD'] | In this paper, we present StyleTTS 2, a text-to-speech (TTS) model that
leverages style diffusion and adversarial training with large speech language
models (SLMs) to achieve human-level TTS synthesis. StyleTTS 2 differs from its
predecessor by modeling styles as a latent random variable through diffusion
models to gen... | 2023-06-13T11:04:43Z | NeurIPS 2023 | null | null | StyleTTS 2: Towards Human-Level Text-to-Speech through Style Diffusion and Adversarial Training with Large Speech Language Models | ['Yinghao Aaron Li', 'Cong Han', 'Vinay S. Raghavan', 'Gavin Mischler', 'N. Mesgarani'] | 2,023 | Neural Information Processing Systems | 127 | 65 | ['Computer Science', 'Medicine', 'Engineering'] |
2,306.07906 | WebGLM: Towards An Efficient Web-Enhanced Question Answering System with
Human Preferences | ['Xiao Liu', 'Hanyu Lai', 'Hao Yu', 'Yifan Xu', 'Aohan Zeng', 'Zhengxiao Du', 'Peng Zhang', 'Yuxiao Dong', 'Jie Tang'] | ['cs.CL', 'cs.AI'] | We present WebGLM, a web-enhanced question-answering system based on the
General Language Model (GLM). Its goal is to augment a pre-trained large
language model (LLM) with web search and retrieval capabilities while being
efficient for real-world deployments. To achieve this, we develop WebGLM with
strategies for the L... | 2023-06-13T16:57:53Z | Accepted to KDD 2023 | null | null | null | null | null | null | null | null | null |
2,306.07934 | BoardgameQA: A Dataset for Natural Language Reasoning with Contradictory
Information | ['Mehran Kazemi', 'Quan Yuan', 'Deepti Bhatia', 'Najoung Kim', 'Xin Xu', 'Vaiva Imbrasaite', 'Deepak Ramachandran'] | ['cs.CL', 'cs.AI', 'cs.LG'] | Automated reasoning with unstructured natural text is a key requirement for
many potential applications of NLP and for developing robust AI systems.
Recently, Language Models (LMs) have demonstrated complex reasoning capacities
even without any finetuning. However, existing evaluation for automated
reasoning assumes ac... | 2023-06-13T17:39:20Z | null | null | null | BoardgameQA: A Dataset for Natural Language Reasoning with Contradictory Information | ['Mehran Kazemi', 'Quan Yuan', 'Deepti Bhatia', 'Najoung Kim', 'Xin Xu', 'Vaiva Imbrasaite', 'Deepak Ramachandran'] | 2,023 | Neural Information Processing Systems | 50 | 64 | ['Computer Science'] |
2,306.07957 | Hidden Biases of End-to-End Driving Models | ['Bernhard Jaeger', 'Kashyap Chitta', 'Andreas Geiger'] | ['cs.CV', 'cs.AI', 'cs.LG', 'cs.RO'] | End-to-end driving systems have recently made rapid progress, in particular
on CARLA. Independent of their major contribution, they introduce changes to
minor system components. Consequently, the source of improvements is unclear.
We identify two biases that recur in nearly all state-of-the-art methods and
are critical... | 2023-06-13T17:55:17Z | Accepted at ICCV 2023. Camera ready version | null | null | Hidden Biases of End-to-End Driving Models | ['Bernhard Jaeger', 'Kashyap Chitta', 'Andreas Geiger'] | 2,023 | IEEE International Conference on Computer Vision | 69 | 44 | ['Computer Science'] |
2,306.07967 | One-for-All: Generalized LoRA for Parameter-Efficient Fine-tuning | ['Arnav Chavan', 'Zhuang Liu', 'Deepak Gupta', 'Eric Xing', 'Zhiqiang Shen'] | ['cs.LG', 'cs.AI', 'cs.CV'] | We present Generalized LoRA (GLoRA), an advanced approach for universal
parameter-efficient fine-tuning tasks. Enhancing Low-Rank Adaptation (LoRA),
GLoRA employs a generalized prompt module to optimize pre-trained model weights
and adjust intermediate activations, providing more flexibility and capability
across diver... | 2023-06-13T17:59:32Z | Technical report. v2: Add LLaMA-1&2 results. Code and models at
https://github.com/Arnav0400/ViT-Slim/tree/master/GLoRA | null | null | One-for-All: Generalized LoRA for Parameter-Efficient Fine-tuning | ['Arnav Chavan', 'Zhuang Liu', 'D. Gupta', 'Eric P. Xing', 'Zhiqiang Shen'] | 2,023 | arXiv.org | 92 | 49 | ['Computer Science'] |
2,306.08018 | Mol-Instructions: A Large-Scale Biomolecular Instruction Dataset for
Large Language Models | ['Yin Fang', 'Xiaozhuan Liang', 'Ningyu Zhang', 'Kangwei Liu', 'Rui Huang', 'Zhuo Chen', 'Xiaohui Fan', 'Huajun Chen'] | ['q-bio.QM', 'cs.AI', 'cs.CE', 'cs.CL', 'cs.IR', 'cs.LG'] | Large Language Models (LLMs), with their remarkable task-handling
capabilities and innovative outputs, have catalyzed significant advancements
across a spectrum of fields. However, their proficiency within specialized
domains such as biomolecular studies remains limited. To address this
challenge, we introduce Mol-Inst... | 2023-06-13T14:35:34Z | ICLR 2024. Project homepage:
https://github.com/zjunlp/Mol-Instructions | null | null | Mol-Instructions: A Large-Scale Biomolecular Instruction Dataset for Large Language Models | ['Yin Fang', 'Xiaozhuan Liang', 'Ningyu Zhang', 'Kangwei Liu', 'Rui Huang', 'Zhuo Chen', 'Xiaohui Fan', 'Huajun Chen'] | 2,023 | International Conference on Learning Representations | 88 | 80 | ['Computer Science', 'Biology'] |
2,306.08161 | h2oGPT: Democratizing Large Language Models | ['Arno Candel', 'Jon McKinney', 'Philipp Singer', 'Pascal Pfeiffer', 'Maximilian Jeblick', 'Prithvi Prabhu', 'Jeff Gambera', 'Mark Landry', 'Shivam Bansal', 'Ryan Chesler', 'Chun Ming Lee', 'Marcos V. Conde', 'Pasha Stetsenko', 'Olivier Grellier', 'SriSatish Ambati'] | ['cs.CL', 'cs.AI', 'cs.HC', 'cs.IR', 'cs.LG'] | Applications built on top of Large Language Models (LLMs) such as GPT-4
represent a revolution in AI due to their human-level capabilities in natural
language processing. However, they also pose many significant risks such as the
presence of biased, private, or harmful text, and the unauthorized inclusion of
copyrighte... | 2023-06-13T22:19:53Z | Work in progress by H2O.ai, Inc | null | null | h2oGPT: Democratizing Large Language Models | ['A. Candel', 'Jon McKinney', 'Philipp Singer', 'Pascal Pfeiffer', 'Maximilian Jeblick', 'Prithvi Prabhu', 'Jeff Gambera', 'Mark Landry', 'Shivam Bansal', 'Ryan Chesler', 'Chun Ming Lee', 'Marcos V. Conde', 'Pasha Stetsenko', 'O. Grellier', 'SriSatish Ambati'] | 2,023 | arXiv.org | 7 | 4 | ['Computer Science'] |
2,306.08502 | ITALIC: An Italian Intent Classification Dataset | ['Alkis Koudounas', 'Moreno La Quatra', 'Lorenzo Vaiani', 'Luca Colomba', 'Giuseppe Attanasio', 'Eliana Pastor', 'Luca Cagliero', 'Elena Baralis'] | ['cs.CL', 'cs.SD', 'eess.AS'] | Recent large-scale Spoken Language Understanding datasets focus predominantly
on English and do not account for language-specific phenomena such as
particular phonemes or words in different lects. We introduce ITALIC, the first
large-scale speech dataset designed for intent classification in Italian. The
dataset compri... | 2023-06-14T13:36:24Z | Accepted at INTERSPEECH 2023. Data and code at
https://github.com/RiTA-nlp/ITALIC | null | 10.21437/Interspeech.2023-1980 | ITALIC: An Italian Intent Classification Dataset | ['Alkis Koudounas', 'Moreno La Quatra', 'Lorenzo Vaiani', 'Luca Colomba', 'Giuseppe Attanasio', 'Eliana Pastor', 'Luca Cagliero', 'Elena Baralis'] | 2,023 | Interspeech | 25 | 21 | ['Computer Science', 'Engineering'] |
2,306.08526 | AlbMoRe: A Corpus of Movie Reviews for Sentiment Analysis in Albanian | ['Erion Çano'] | ['cs.CL', 'cs.AI', 'cs.LG'] | Lack of available resources such as text corpora for low-resource languages
seriously hinders research on natural language processing and computational
linguistics. This paper presents AlbMoRe, a corpus of 800 sentiment annotated
movie reviews in Albanian. Each text is labeled as positive or negative and can
be used fo... | 2023-06-14T14:21:55Z | 4 pages, 3 tables | null | null | AlbMoRe: A Corpus of Movie Reviews for Sentiment Analysis in Albanian | ['Erion cCano'] | 2,023 | null | 3 | 19 | ['Computer Science'] |
2,306.08543 | MiniLLM: Knowledge Distillation of Large Language Models | ['Yuxian Gu', 'Li Dong', 'Furu Wei', 'Minlie Huang'] | ['cs.CL', 'cs.AI'] | Knowledge Distillation (KD) is a promising technique for reducing the high
computational demand of large language models (LLMs). However, previous KD
methods are primarily applied to white-box classification models or training
small models to imitate black-box model APIs like ChatGPT. How to effectively
distill the kno... | 2023-06-14T14:44:03Z | Published as a conference paper in ICLR 2024 | null | null | null | null | null | null | null | null | null |
2,306.08568 | WizardCoder: Empowering Code Large Language Models with Evol-Instruct | ['Ziyang Luo', 'Can Xu', 'Pu Zhao', 'Qingfeng Sun', 'Xiubo Geng', 'Wenxiang Hu', 'Chongyang Tao', 'Jing Ma', 'Qingwei Lin', 'Daxin Jiang'] | ['cs.CL', 'cs.AI'] | Code Large Language Models (Code LLMs), such as StarCoder, have demonstrated
exceptional performance in code-related tasks. However, most existing models
are solely pre-trained on extensive raw code data without instruction
fine-tuning. In this paper, we introduce WizardCoder, which empowers Code LLMs
with complex inst... | 2023-06-14T15:18:48Z | Large Language model, Code Generation, Code LLMs.This paper has been
accepted to ICLR 2024. Please cite the ICLR version | The Twelfth International Conference on Learning Representations
(ICLR 2024) | null | WizardCoder: Empowering Code Large Language Models with Evol-Instruct | ['Ziyang Luo', 'Can Xu', 'Pu Zhao', 'Qingfeng Sun', 'Xiubo Geng', 'Wenxiang Hu', 'Chongyang Tao', 'Jing Ma', 'Qingwei Lin', 'Daxin Jiang'] | 2,023 | International Conference on Learning Representations | 698 | 49 | ['Computer Science'] |
2,306.0862 | Anticipatory Music Transformer | ['John Thickstun', 'David Hall', 'Chris Donahue', 'Percy Liang'] | ['cs.SD', 'cs.LG', 'eess.AS', 'stat.ML'] | We introduce anticipation: a method for constructing a controllable
generative model of a temporal point process (the event process) conditioned
asynchronously on realizations of a second, correlated process (the control
process). We achieve this by interleaving sequences of events and controls,
such that controls appe... | 2023-06-14T16:27:53Z | TMLR accepted version | null | null | Anticipatory Music Transformer | ['John Thickstun', 'D. Hall', 'Chris Donahue', 'Percy Liang'] | 2,023 | Trans. Mach. Learn. Res. | 16 | 122 | ['Computer Science', 'Engineering', 'Mathematics'] |
2,306.08637 | TAPIR: Tracking Any Point with per-frame Initialization and temporal
Refinement | ['Carl Doersch', 'Yi Yang', 'Mel Vecerik', 'Dilara Gokay', 'Ankush Gupta', 'Yusuf Aytar', 'Joao Carreira', 'Andrew Zisserman'] | ['cs.CV'] | We present a novel model for Tracking Any Point (TAP) that effectively tracks
any queried point on any physical surface throughout a video sequence. Our
approach employs two stages: (1) a matching stage, which independently locates
a suitable candidate point match for the query point on every other frame, and
(2) a ref... | 2023-06-14T17:07:51Z | Published at ICCV 2023 | null | null | null | null | null | null | null | null | null |
2,306.08685 | World-to-Words: Grounded Open Vocabulary Acquisition through Fast
Mapping in Vision-Language Models | ['Ziqiao Ma', 'Jiayi Pan', 'Joyce Chai'] | ['cs.CL', 'cs.AI', 'cs.CV'] | The ability to connect language units to their referents in the physical
world, referred to as grounding, is crucial to learning and understanding
grounded meanings of words. While humans demonstrate fast mapping in new word
learning, it remains unclear whether modern vision-language models can truly
represent language... | 2023-06-14T18:10:05Z | ACL 2023 Outstanding Paper | null | null | null | null | null | null | null | null | null |
2,306.08832 | Contrasting Intra-Modal and Ranking Cross-Modal Hard Negatives to
Enhance Visio-Linguistic Compositional Understanding | ['Le Zhang', 'Rabiul Awal', 'Aishwarya Agrawal'] | ['cs.CV'] | Vision-Language Models (VLMs), such as CLIP, exhibit strong image-text
comprehension abilities, facilitating advances in several downstream tasks such
as zero-shot image classification, image-text retrieval, and text-to-image
generation. However, the compositional reasoning abilities of existing VLMs
remains subpar. Th... | 2023-06-15T03:26:28Z | CVPR 2024 | null | null | null | null | null | null | null | null | null |
2,306.08887 | SplatFlow: Learning Multi-frame Optical Flow via Splatting | ['Bo Wang', 'Yifan Zhang', 'Jian Li', 'Yang Yu', 'Zhenping Sun', 'Li Liu', 'Dewen Hu'] | ['cs.CV'] | The occlusion problem remains a crucial challenge in optical flow estimation
(OFE). Despite the recent significant progress brought about by deep learning,
most existing deep learning OFE methods still struggle to handle occlusions; in
particular, those based on two frames cannot correctly handle occlusions
because occ... | 2023-06-15T06:41:21Z | null | International Journal of Computer Vision (IJCV), 2024 | 10.1007/s11263-024-01993-0 | null | null | null | null | null | null | null |
2,306.092 | ChessGPT: Bridging Policy Learning and Language Modeling | ['Xidong Feng', 'Yicheng Luo', 'Ziyan Wang', 'Hongrui Tang', 'Mengyue Yang', 'Kun Shao', 'David Mguni', 'Yali Du', 'Jun Wang'] | ['cs.LG', 'cs.AI'] | When solving decision-making tasks, humans typically depend on information
from two key sources: (1) Historical policy data, which provides interaction
replay from the environment, and (2) Analytical insights in natural language
form, exposing the invaluable thought process or strategic considerations.
Despite this, th... | 2023-06-15T15:35:31Z | Published as a conference article in NeurIPS 2023 | null | null | ChessGPT: Bridging Policy Learning and Language Modeling | ['Xidong Feng', 'Yicheng Luo', 'Ziyan Wang', 'Hongrui Tang', 'Mengyue Yang', 'Kun Shao', 'D. Mguni', 'Yali Du', 'Jun Wang'] | 2,023 | Neural Information Processing Systems | 44 | 61 | ['Computer Science'] |
2,306.09212 | CMMLU: Measuring massive multitask language understanding in Chinese | ['Haonan Li', 'Yixuan Zhang', 'Fajri Koto', 'Yifei Yang', 'Hai Zhao', 'Yeyun Gong', 'Nan Duan', 'Timothy Baldwin'] | ['cs.CL'] | As the capabilities of large language models (LLMs) continue to advance,
evaluating their performance becomes increasingly crucial and challenging. This
paper aims to bridge this gap by introducing CMMLU, a comprehensive Chinese
benchmark that covers various subjects, including natural science, social
sciences, enginee... | 2023-06-15T15:49:51Z | null | null | null | CMMLU: Measuring massive multitask language understanding in Chinese | ['Haonan Li', 'Yixuan Zhang', 'Fajri Koto', 'Yifei Yang', 'Hai Zhao', 'Yeyun Gong', 'Nan Duan', 'Tim Baldwin'] | 2,023 | Annual Meeting of the Association for Computational Linguistics | 274 | 50 | ['Computer Science'] |
2,306.09237 | One Law, Many Languages: Benchmarking Multilingual Legal Reasoning for
Judicial Support | ['Ronja Stern', 'Vishvaksenan Rasiah', 'Veton Matoshi', 'Srinanda Brügger Bose', 'Matthias Stürmer', 'Ilias Chalkidis', 'Daniel E. Ho', 'Joel Niklaus'] | ['cs.CL', 'cs.AI', 'cs.LG', '68T50', 'I.2'] | Recent strides in Large Language Models (LLMs) have saturated many Natural
Language Processing (NLP) benchmarks, emphasizing the need for more challenging
ones to properly assess LLM capabilities. However, domain-specific and
multilingual benchmarks are rare because they require in-depth expertise to
develop. Still, mo... | 2023-06-15T16:19:15Z | null | null | null | One Law, Many Languages: Benchmarking Multilingual Legal Reasoning for Judicial Support | ['Vishvaksenan Rasiah', 'Ronja Stern', 'Veton Matoshi', 'Matthias Sturmer', 'Ilias Chalkidis', 'Daniel Ho', 'Joel Niklaus'] | 2,023 | null | 11 | 0 | ['Computer Science'] |
2,306.09364 | TSMixer: Lightweight MLP-Mixer Model for Multivariate Time Series
Forecasting | ['Vijay Ekambaram', 'Arindam Jati', 'Nam Nguyen', 'Phanwadee Sinthong', 'Jayant Kalagnanam'] | ['cs.LG', 'cs.AI', 'I.2'] | Transformers have gained popularity in time series forecasting for their
ability to capture long-sequence interactions. However, their high memory and
computing requirements pose a critical bottleneck for long-term forecasting. To
address this, we propose TSMixer, a lightweight neural architecture exclusively
composed ... | 2023-06-14T06:26:23Z | Accepted in the Proceedings of the 29th ACM SIGKDD Conference on
Knowledge Discovery and Data Mining (KDD 23), Research Track. Delayed release
in arXiv to comply with the conference policies on the double-blind review
process. This paper has been submitted to the KDD peer-review process on Feb
02, 2023 | null | 10.1145/3580305.3599533 | null | null | null | null | null | null | null |
2,306.09683 | Scaling Open-Vocabulary Object Detection | ['Matthias Minderer', 'Alexey Gritsenko', 'Neil Houlsby'] | ['cs.CV'] | Open-vocabulary object detection has benefited greatly from pretrained
vision-language models, but is still limited by the amount of available
detection training data. While detection training data can be expanded by using
Web image-text pairs as weak supervision, this has not been done at scales
comparable to image-le... | 2023-06-16T08:27:46Z | null | null | null | null | null | null | null | null | null | null |
2,306.09802 | RED$^{\rm FM}$: a Filtered and Multilingual Relation Extraction Dataset | ['Pere-Lluís Huguet Cabot', 'Simone Tedeschi', 'Axel-Cyrille Ngonga Ngomo', 'Roberto Navigli'] | ['cs.CL'] | Relation Extraction (RE) is a task that identifies relationships between
entities in a text, enabling the acquisition of relational facts and bridging
the gap between natural language and structured knowledge. However, current RE
models often rely on small datasets with low coverage of relation types,
particularly when... | 2023-06-16T12:29:59Z | ACL 2023. Please cite authors correctly using both lastnames ("Huguet
Cabot", "Ngonga Ngomo") | null | null | null | null | null | null | null | null | null |
2,306.09968 | ClinicalGPT: Large Language Models Finetuned with Diverse Medical Data
and Comprehensive Evaluation | ['Guangyu Wang', 'Guoxing Yang', 'Zongxin Du', 'Longjun Fan', 'Xiaohu Li'] | ['cs.CL'] | Large language models have exhibited exceptional performance on various
Natural Language Processing (NLP) tasks, leveraging techniques such as the
pre-training, and instruction fine-tuning. Despite these advances, their
effectiveness in medical applications is limited, due to challenges such as
factual inaccuracies, re... | 2023-06-16T16:56:32Z | null | null | null | null | null | null | null | null | null | null |
2,306.10315 | FutureTOD: Teaching Future Knowledge to Pre-trained Language Model for
Task-Oriented Dialogue | ['Weihao Zeng', 'Keqing He', 'Yejie Wang', 'Chen Zeng', 'Jingang Wang', 'Yunsen Xian', 'Weiran Xu'] | ['cs.CL'] | Pre-trained language models based on general text enable huge success in the
NLP scenario. But the intrinsical difference of linguistic patterns between
general text and task-oriented dialogues makes existing pre-trained language
models less useful in practice. Current dialogue pre-training methods rely on a
contrastiv... | 2023-06-17T10:40:07Z | ACL 2023 Main Conference | null | null | null | null | null | null | null | null | null |
2,306.10968 | BayLing: Bridging Cross-lingual Alignment and Instruction Following
through Interactive Translation for Large Language Models | ['Shaolei Zhang', 'Qingkai Fang', 'Zhuocheng Zhang', 'Zhengrui Ma', 'Yan Zhou', 'Langlin Huang', 'Mengyu Bu', 'Shangtong Gui', 'Yunji Chen', 'Xilin Chen', 'Yang Feng'] | ['cs.CL', 'cs.AI'] | Large language models (LLMs) have demonstrated remarkable prowess in language
understanding and generation. Advancing from foundation LLMs to
instructionfollowing LLMs, instruction tuning plays a vital role in aligning
LLMs to human preferences. However, the existing LLMs are usually focused on
English, leading to infe... | 2023-06-19T14:30:52Z | Try BayLing's online demo at http://nlp.ict.ac.cn/bayling/demo | null | null | BayLing: Bridging Cross-lingual Alignment and Instruction Following through Interactive Translation for Large Language Models | ['Shaolei Zhang', 'Qingkai Fang', 'Zhuocheng Zhang', 'Zhengrui Ma', 'Yan Zhou', 'Langlin Huang', 'Mengyu Bu', 'Shangtong Gui', 'Yunji Chen', 'Xilin Chen', 'Yang Feng'] | 2,023 | arXiv.org | 42 | 29 | ['Computer Science'] |
2,306.10998 | RepoFusion: Training Code Models to Understand Your Repository | ['Disha Shrivastava', 'Denis Kocetkov', 'Harm de Vries', 'Dzmitry Bahdanau', 'Torsten Scholak'] | ['cs.LG', 'cs.AI', 'cs.PL', 'cs.SE'] | Despite the huge success of Large Language Models (LLMs) in coding assistants
like GitHub Copilot, these models struggle to understand the context present in
the repository (e.g., imports, parent classes, files with similar names, etc.),
thereby producing inaccurate code completions. This effect is more pronounced
when... | 2023-06-19T15:05:31Z | null | null | null | RepoFusion: Training Code Models to Understand Your Repository | ['Disha Shrivastava', 'Denis Kocetkov', 'H. D. Vries', 'Dzmitry Bahdanau', 'Torsten Scholak'] | 2,023 | arXiv.org | 29 | 42 | ['Computer Science'] |
2,306.11207 | Quilt-1M: One Million Image-Text Pairs for Histopathology | ['Wisdom Oluchi Ikezogwo', 'Mehmet Saygin Seyfioglu', 'Fatemeh Ghezloo', 'Dylan Stefan Chan Geva', 'Fatwir Sheikh Mohammed', 'Pavan Kumar Anand', 'Ranjay Krishna', 'Linda Shapiro'] | ['cs.CV', 'cs.CL', 'cs.LG'] | Recent accelerations in multi-modal applications have been made possible with
the plethora of image and text data available online. However, the scarcity of
analogous data in the medical field, specifically in histopathology, has slowed
comparable progress. To enable similar representation learning for
histopathology, ... | 2023-06-20T00:14:47Z | null | null | null | null | null | null | null | null | null | null |
2,306.11247 | DICES Dataset: Diversity in Conversational AI Evaluation for Safety | ['Lora Aroyo', 'Alex S. Taylor', 'Mark Diaz', 'Christopher M. Homan', 'Alicia Parrish', 'Greg Serapio-Garcia', 'Vinodkumar Prabhakaran', 'Ding Wang'] | ['cs.HC'] | Machine learning approaches often require training and evaluation datasets
with a clear separation between positive and negative examples. This risks
simplifying and even obscuring the inherent subjectivity present in many tasks.
Preserving such variance in content and diversity in datasets is often
expensive and labor... | 2023-06-20T03:00:12Z | null | null | null | null | null | null | null | null | null | null |
2,306.11249 | OpenSTL: A Comprehensive Benchmark of Spatio-Temporal Predictive
Learning | ['Cheng Tan', 'Siyuan Li', 'Zhangyang Gao', 'Wenfei Guan', 'Zedong Wang', 'Zicheng Liu', 'Lirong Wu', 'Stan Z. Li'] | ['cs.CV', 'cs.AI'] | Spatio-temporal predictive learning is a learning paradigm that enables
models to learn spatial and temporal patterns by predicting future frames from
given past frames in an unsupervised manner. Despite remarkable progress in
recent years, a lack of systematic understanding persists due to the diverse
settings, comple... | 2023-06-20T03:02:14Z | Accepted by NeurIPS 2023. 33 pages, 17 figures, 19 tables. Under
review. For more details, please refer to
https://github.com/chengtan9907/OpenSTL | null | null | OpenSTL: A Comprehensive Benchmark of Spatio-Temporal Predictive Learning | ['Cheng Tan', 'Siyuan Li', 'Zhangyang Gao', 'Wen-Cai Guan', 'Zedong Wang', 'Zicheng Liu', 'Lirong Wu', 'Stan Z. Li'] | 2,023 | Neural Information Processing Systems | 63 | 68 | ['Computer Science'] |
2,306.11372 | Democratizing LLMs for Low-Resource Languages by Leveraging their
English Dominant Abilities with Linguistically-Diverse Prompts | ['Xuan-Phi Nguyen', 'Sharifah Mahani Aljunied', 'Shafiq Joty', 'Lidong Bing'] | ['cs.CL', 'cs.AI'] | Large language models (LLMs) are known to effectively perform tasks by simply
observing few exemplars. However, in low-resource languages, obtaining such
hand-picked exemplars can still be challenging, where unsupervised techniques
may be necessary. Moreover, competent generative capabilities of LLMs are
observed only ... | 2023-06-20T08:27:47Z | ACL 2024 Main Conference | null | null | Democratizing LLMs for Low-Resource Languages by Leveraging their English Dominant Abilities with Linguistically-Diverse Prompts | ['Xuan-Phi Nguyen', 'Sharifah Mahani Aljunied', 'Shafiq R. Joty', 'Lidong Bing'] | 2,023 | Annual Meeting of the Association for Computational Linguistics | 39 | 57 | ['Computer Science'] |
2,306.11644 | Textbooks Are All You Need | ['Suriya Gunasekar', 'Yi Zhang', 'Jyoti Aneja', 'Caio César Teodoro Mendes', 'Allie Del Giorno', 'Sivakanth Gopi', 'Mojan Javaheripi', 'Piero Kauffmann', 'Gustavo de Rosa', 'Olli Saarikivi', 'Adil Salim', 'Shital Shah', 'Harkirat Singh Behl', 'Xin Wang', 'Sébastien Bubeck', 'Ronen Eldan', 'Adam Tauman Kalai', 'Yin Tat ... | ['cs.CL', 'cs.AI', 'cs.LG'] | We introduce phi-1, a new large language model for code, with significantly
smaller size than competing models: phi-1 is a Transformer-based model with
1.3B parameters, trained for 4 days on 8 A100s, using a selection of ``textbook
quality" data from the web (6B tokens) and synthetically generated textbooks
and exercis... | 2023-06-20T16:14:25Z | 26 pages; changed color scheme of plot. fixed minor typos and added
couple clarifications | null | null | null | null | null | null | null | null | null |
2,306.11695 | A Simple and Effective Pruning Approach for Large Language Models | ['Mingjie Sun', 'Zhuang Liu', 'Anna Bair', 'J. Zico Kolter'] | ['cs.CL', 'cs.AI', 'cs.LG'] | As their size increases, Large Languages Models (LLMs) are natural candidates
for network pruning methods: approaches that drop a subset of network weights
while striving to preserve performance. Existing methods, however, require
either retraining, which is rarely affordable for billion-scale LLMs, or
solving a weight... | 2023-06-20T17:18:20Z | ICLR 2024. Website at https://eric-mingjie.github.io/wanda/home.html | null | null | A Simple and Effective Pruning Approach for Large Language Models | ['Mingjie Sun', 'Zhuang Liu', 'Anna Bair', 'J. Z. Kolter'] | 2,023 | International Conference on Learning Representations | 443 | 107 | ['Computer Science'] |
2,306.11925 | LVM-Med: Learning Large-Scale Self-Supervised Vision Models for Medical
Imaging via Second-order Graph Matching | ['Duy M. H. Nguyen', 'Hoang Nguyen', 'Nghiem T. Diep', 'Tan N. Pham', 'Tri Cao', 'Binh T. Nguyen', 'Paul Swoboda', 'Nhat Ho', 'Shadi Albarqouni', 'Pengtao Xie', 'Daniel Sonntag', 'Mathias Niepert'] | ['cs.CV'] | Obtaining large pre-trained models that can be fine-tuned to new tasks with
limited annotated samples has remained an open challenge for medical imaging
data. While pre-trained deep networks on ImageNet and vision-language
foundation models trained on web-scale data are prevailing approaches, their
effectiveness on med... | 2023-06-20T22:21:34Z | Accepted at NeurIPS 2023 | null | null | LVM-Med: Learning Large-Scale Self-Supervised Vision Models for Medical Imaging via Second-order Graph Matching | ['D. M. Nguyen', 'Hoang Nguyen', 'N. T. Diep', 'T. Pham', 'T. Cao', 'Binh Duc Nguyen', 'P. Swoboda', 'Nhat Ho', 'Shadi Albarqouni', 'Pengtao Xie', 'Daniel Sonntag', 'Mathias Niepert'] | 2,023 | Neural Information Processing Systems | 55 | 140 | ['Computer Science'] |
2,306.12059 | EquiformerV2: Improved Equivariant Transformer for Scaling to
Higher-Degree Representations | ['Yi-Lun Liao', 'Brandon Wood', 'Abhishek Das', 'Tess Smidt'] | ['cs.LG', 'cs.AI', 'physics.comp-ph'] | Equivariant Transformers such as Equiformer have demonstrated the efficacy of
applying Transformers to the domain of 3D atomistic systems. However, they are
limited to small degrees of equivariant representations due to their
computational complexity. In this paper, we investigate whether these
architectures can scale ... | 2023-06-21T07:01:38Z | Published as a conference paper at ICLR 2024 | null | null | EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations | ['Yidong Liao', 'Brandon Wood', 'Abhishek Das', 'T. Smidt'] | 2,023 | International Conference on Learning Representations | 159 | 80 | ['Computer Science', 'Physics'] |
2,306.12156 | Fast Segment Anything | ['Xu Zhao', 'Wenchao Ding', 'Yongqi An', 'Yinglong Du', 'Tao Yu', 'Min Li', 'Ming Tang', 'Jinqiao Wang'] | ['cs.CV', 'cs.AI'] | The recently proposed segment anything model (SAM) has made a significant
influence in many computer vision tasks. It is becoming a foundation step for
many high-level tasks, like image segmentation, image caption, and image
editing. However, its huge computation costs prevent it from wider applications
in industry sce... | 2023-06-21T10:08:29Z | Technical Report. The code is released at
https://github.com/CASIA-IVA-Lab/FastSAM | null | null | null | null | null | null | null | null | null |
2,306.1242 | LMFlow: An Extensible Toolkit for Finetuning and Inference of Large
Foundation Models | ['Shizhe Diao', 'Rui Pan', 'Hanze Dong', 'Ka Shun Shum', 'Jipeng Zhang', 'Wei Xiong', 'Tong Zhang'] | ['cs.CL', 'cs.AI'] | Foundation models have demonstrated a great ability to achieve general
human-level intelligence far beyond traditional approaches. As the technique
keeps attracting attention from the AI community, an increasing number of
foundation models are becoming publicly accessible. However, a significant
shortcoming of most of ... | 2023-06-21T17:58:25Z | Published in NAACL 2024 Demo Track | null | null | null | null | null | null | null | null | null |
2,306.12766 | Mapping and Cleaning Open Commonsense Knowledge Bases with Generative
Translation | ['Julien Romero', 'Simon Razniewski'] | ['cs.CL'] | Structured knowledge bases (KBs) are the backbone of many
know\-ledge-intensive applications, and their automated construction has
received considerable attention. In particular, open information extraction
(OpenIE) is often used to induce structure from a text. However, although it
allows high recall, the extracted kn... | 2023-06-22T09:42:54Z | null | null | null | null | null | null | null | null | null | null |
2,306.12802 | Otter-Knowledge: benchmarks of multimodal knowledge graph representation
learning from different sources for drug discovery | ['Hoang Thanh Lam', 'Marco Luca Sbodio', 'Marcos Martínez Galindo', 'Mykhaylo Zayats', 'Raúl Fernández-Díaz', 'Víctor Valls', 'Gabriele Picco', 'Cesar Berrospi Ramis', 'Vanessa López'] | ['cs.LG', 'cs.AI', 'q-bio.BM'] | Recent research on predicting the binding affinity between drug molecules and
proteins use representations learned, through unsupervised learning techniques,
from large databases of molecule SMILES and protein sequences. While these
representations have significantly enhanced the predictions, they are usually
based on ... | 2023-06-22T11:01:41Z | null | null | null | Otter-Knowledge: benchmarks of multimodal knowledge graph representation learning from different sources for drug discovery | ['Hoang Thanh Lam', 'M. Sbodio', 'Marcos Martínez Galindo', 'Mykhaylo Zayats', "Ra'ul Fern'andez-D'iaz", 'Victor Valls', 'Gabriele Picco', 'Cesar Berrospi Ramis', "V. L'opez"] | 2,023 | arXiv.org | 8 | 38 | ['Computer Science', 'Biology'] |
2,306.12991 | Speech Emotion Diarization: Which Emotion Appears When? | ['Yingzhi Wang', 'Mirco Ravanelli', 'Alya Yacoubi'] | ['cs.CL'] | Speech Emotion Recognition (SER) typically relies on utterance-level
solutions. However, emotions conveyed through speech should be considered as
discrete speech events with definite temporal boundaries, rather than
attributes of the entire utterance. To reflect the fine-grained nature of
speech emotions, we propose a ... | 2023-06-22T15:47:36Z | Accepted to ASRU 2023 | null | null | null | null | null | null | null | null | null |
2,306.13643 | LightGlue: Local Feature Matching at Light Speed | ['Philipp Lindenberger', 'Paul-Edouard Sarlin', 'Marc Pollefeys'] | ['cs.CV'] | We introduce LightGlue, a deep neural network that learns to match local
features across images. We revisit multiple design decisions of SuperGlue, the
state of the art in sparse matching, and derive simple but effective
improvements. Cumulatively, they make LightGlue more efficient - in terms of
both memory and comput... | 2023-06-23T17:52:54Z | null | null | null | LightGlue: Local Feature Matching at Light Speed | ['Philipp Lindenberger', 'Paul-Edouard Sarlin', 'M. Pollefeys'] | 2,023 | IEEE International Conference on Computer Vision | 456 | 84 | ['Computer Science'] |
2,306.13649 | On-Policy Distillation of Language Models: Learning from Self-Generated
Mistakes | ['Rishabh Agarwal', 'Nino Vieillard', 'Yongchao Zhou', 'Piotr Stanczyk', 'Sabela Ramos', 'Matthieu Geist', 'Olivier Bachem'] | ['cs.LG', 'cs.AI', 'cs.CL'] | Knowledge distillation (KD) is widely used for compressing a teacher model to
reduce its inference cost and memory footprint, by training a smaller student
model. However, current KD methods for auto-regressive sequence models suffer
from distribution mismatch between output sequences seen during training and
those gen... | 2023-06-23T17:56:26Z | Accepted at ICLR 2024. First two authors contributed equally | null | null | null | null | null | null | null | null | null |
2,306.13888 | L3Cube-MahaSent-MD: A Multi-domain Marathi Sentiment Analysis Dataset
and Transformer Models | ['Aabha Pingle', 'Aditya Vyawahare', 'Isha Joshi', 'Rahul Tangsali', 'Raviraj Joshi'] | ['cs.CL', 'cs.LG'] | The exploration of sentiment analysis in low-resource languages, such as
Marathi, has been limited due to the availability of suitable datasets. In this
work, we present L3Cube-MahaSent-MD, a multi-domain Marathi sentiment analysis
dataset, with four different domains - movie reviews, general tweets, TV show
subtitles,... | 2023-06-24T07:27:53Z | Accepted at DMLR Workshop @ ICML 2023 | null | null | L3Cube-MahaSent-MD: A Multi-domain Marathi Sentiment Analysis Dataset and Transformer Models | ['Aabha Pingle', 'Aditya Vyawahare', 'Isha Joshi', 'Rahul Tangsali', 'Raviraj Joshi'] | 2,023 | Pacific Asia Conference on Language, Information and Computation | 9 | 27 | ['Computer Science'] |
2,306.1403 | My Boli: Code-mixed Marathi-English Corpora, Pretrained Language Models
and Evaluation Benchmarks | ['Tanmay Chavan', 'Omkar Gokhale', 'Aditya Kane', 'Shantanu Patankar', 'Raviraj Joshi'] | ['cs.CL', 'cs.LG'] | The research on code-mixed data is limited due to the unavailability of
dedicated code-mixed datasets and pre-trained language models. In this work, we
focus on the low-resource Indian language Marathi which lacks any prior work in
code-mixing. We present L3Cube-MeCorpus, a large code-mixed Marathi-English
(Mr-En) corp... | 2023-06-24T18:17:38Z | null | null | null | My Boli: Code-mixed Marathi-English Corpora, Pretrained Language Models and Evaluation Benchmarks | ['Tanmay Chavan', 'Omkar Gokhale', 'Aditya Kane', 'Shantanu Patankar', 'Raviraj Joshi'] | 2,023 | International Joint Conference on Natural Language Processing | 3 | 22 | ['Computer Science'] |
2,306.14256 | A Multilingual Translator to SQL with Database Schema Pruning to Improve
Self-Attention | ['Marcelo Archanjo Jose', 'Fabio Gagliardi Cozman'] | ['cs.AI', '68T07, 68T50', 'I.2.7; H.3.3'] | Long sequences of text are challenging in the context of transformers, due to
quadratic memory increase in the self-attention mechanism. As this issue
directly affects the translation from natural language to SQL queries (as
techniques usually take as input a concatenated text with the question and the
database schema)... | 2023-06-25T14:28:12Z | This preprint has not undergone peer review or any post-submission
improvements or corrections. The Version of Record of this article is
published in International Journal of Information Technology, and is
available online at https://doi.org/10.1007/s41870-023-01342-3 . SharedIt
link: https://rdcu.be/dff19 | null | 10.1007/s41870-023-01342-3 | null | null | null | null | null | null | null |
2,306.14289 | Faster Segment Anything: Towards Lightweight SAM for Mobile Applications | ['Chaoning Zhang', 'Dongshen Han', 'Yu Qiao', 'Jung Uk Kim', 'Sung-Ho Bae', 'Seungkyu Lee', 'Choong Seon Hong'] | ['cs.CV'] | Segment Anything Model (SAM) has attracted significant attention due to its
impressive zero-shot transfer performance and high versatility for numerous
vision applications (like image editing with fine-grained control). Many of
such applications need to be run on resource-constraint edge devices, like
mobile phones. In... | 2023-06-25T16:37:25Z | First work to make SAM lightweight for mobile applications | null | null | Faster Segment Anything: Towards Lightweight SAM for Mobile Applications | ['Chaoning Zhang', 'Dongshen Han', 'Yu Qiao', 'Jung Uk Kim', 'S. Bae', 'Seungkyu Lee', 'Choong-Seon Hong'] | 2,023 | arXiv.org | 364 | 41 | ['Computer Science'] |
2,306.14291 | Hyp-OW: Exploiting Hierarchical Structure Learning with Hyperbolic
Distance Enhances Open World Object Detection | ['Thang Doan', 'Xin Li', 'Sima Behpour', 'Wenbin He', 'Liang Gou', 'Liu Ren'] | ['cs.CV', 'cs.LG'] | Open World Object Detection (OWOD) is a challenging and realistic task that
extends beyond the scope of standard Object Detection task. It involves
detecting both known and unknown objects while integrating learned knowledge
for future tasks. However, the level of "unknownness" varies significantly
depending on the con... | 2023-06-25T16:45:20Z | Accepted at AAAI 2024 || keywords: Open World Object Detection,
Hyperbolic Distance, Unknown Detection, Deformable Transformers, Hierarchical
Representation Learning | null | null | null | null | null | null | null | null | null |
2,306.14517 | Cross-Lingual Cross-Age Group Adaptation for Low-Resource Elderly Speech
Emotion Recognition | ['Samuel Cahyawijaya', 'Holy Lovenia', 'Willy Chung', 'Rita Frieske', 'Zihan Liu', 'Pascale Fung'] | ['cs.CL', 'cs.SD', 'eess.AS'] | Speech emotion recognition plays a crucial role in human-computer
interactions. However, most speech emotion recognition research is biased
toward English-speaking adults, which hinders its applicability to other
demographic groups in different languages and age groups. In this work, we
analyze the transferability of e... | 2023-06-26T08:48:08Z | Accepted in INTERSPEECH 2023 | null | null | Cross-Lingual Cross-Age Group Adaptation for Low-Resource Elderly Speech Emotion Recognition | ['Samuel Cahyawijaya', 'Holy Lovenia', 'Willy Chung', 'Rita Frieske', 'Zihan Liu', 'Pascale Fung'] | 2,023 | arXiv.org | 1 | 52 | ['Computer Science', 'Engineering'] |
2,306.14592 | Transfer Learning across Several Centuries: Machine and Historian
Integrated Method to Decipher Royal Secretary's Diary | ['Sojung Lucia Kim', 'Taehong Jang', 'Joonmo Ahn', 'Hyungil Lee', 'Jaehyuk Lee'] | ['cs.CL', 'cs.DL'] | A named entity recognition and classification plays the first and foremost
important role in capturing semantics in data and anchoring in translation as
well as downstream study for history. However, NER in historical text has faced
challenges such as scarcity of annotated corpus, multilanguage variety, various
noise, ... | 2023-06-26T11:00:35Z | 7 pages, 9 figures | null | null | Transfer Learning across Several Centuries: Machine and Historian Integrated Method to Decipher Royal Secretary's Diary | ['Sojung Lucia Kim', 'Tae Young Jang', 'Joonmo Ahn', 'Hyungi Lee', 'Jaehyuk Lee'] | 2,023 | arXiv.org | 1 | 22 | ['Computer Science'] |
2,306.14795 | MotionGPT: Human Motion as a Foreign Language | ['Biao Jiang', 'Xin Chen', 'Wen Liu', 'Jingyi Yu', 'Gang Yu', 'Tao Chen'] | ['cs.CV', 'cs.CL', 'cs.GR'] | Though the advancement of pre-trained large language models unfolds, the
exploration of building a unified model for language and other multi-modal
data, such as motion, remains challenging and untouched so far. Fortunately,
human motion displays a semantic coupling akin to human language, often
perceived as a form of ... | 2023-06-26T15:53:02Z | Project Page: https://github.com/OpenMotionLab/MotionGPT | null | null | MotionGPT: Human Motion as a Foreign Language | ['Biao Jiang', 'Xin Chen', 'Wen Liu', 'Jingyi Yu', 'Gang Yu', 'Tao Chen'] | 2,023 | Neural Information Processing Systems | 297 | 73 | ['Computer Science'] |
2,306.14895 | Large Multimodal Models: Notes on CVPR 2023 Tutorial | ['Chunyuan Li'] | ['cs.CV'] | This tutorial note summarizes the presentation on ``Large Multimodal Models:
Towards Building and Surpassing Multimodal GPT-4'', a part of CVPR 2023
tutorial on ``Recent Advances in Vision Foundation Models''. The tutorial
consists of three parts. We first introduce the background on recent GPT-like
large models for vi... | 2023-06-26T17:59:31Z | 27 pages, 24 figures; Tutorial website:
https://vlp-tutorial.github.io/ | null | null | Large Multimodal Models: Notes on CVPR 2023 Tutorial | ['Chunyuan Li'] | 2,023 | arXiv.org | 20 | 65 | ['Computer Science'] |
2,306.15006 | DNABERT-2: Efficient Foundation Model and Benchmark For Multi-Species
Genome | ['Zhihan Zhou', 'Yanrong Ji', 'Weijian Li', 'Pratik Dutta', 'Ramana Davuluri', 'Han Liu'] | ['q-bio.GN', 'cs.AI', 'cs.CE', 'cs.CL'] | Decoding the linguistic intricacies of the genome is a crucial problem in
biology, and pre-trained foundational models such as DNABERT and Nucleotide
Transformer have made significant strides in this area. Existing works have
largely hinged on k-mer, fixed-length permutations of A, T, C, and G, as the
token of the geno... | 2023-06-26T18:43:46Z | Accepted by ICLR 2024 | null | null | DNABERT-2: Efficient Foundation Model and Benchmark For Multi-Species Genome | ['Zhihan Zhou', 'Yanrong Ji', 'Weijian Li', 'Pratik Dutta', 'R. Davuluri', 'Han Liu'] | 2,023 | arXiv.org | 199 | 38 | ['Biology', 'Computer Science'] |
2,306.1535 | CellViT: Vision Transformers for Precise Cell Segmentation and
Classification | ['Fabian Hörst', 'Moritz Rempe', 'Lukas Heine', 'Constantin Seibold', 'Julius Keyl', 'Giulia Baldini', 'Selma Ugurel', 'Jens Siveke', 'Barbara Grünwald', 'Jan Egger', 'Jens Kleesiek'] | ['eess.IV', 'cs.CV', 'cs.LG'] | Nuclei detection and segmentation in hematoxylin and eosin-stained (H&E)
tissue images are important clinical tasks and crucial for a wide range of
applications. However, it is a challenging task due to nuclei variances in
staining and size, overlapping boundaries, and nuclei clustering. While
convolutional neural netw... | 2023-06-27T10:03:15Z | 18 pages, 5 figures, appendix included | null | null | null | null | null | null | null | null | null |
2,306.15447 | Are aligned neural networks adversarially aligned? | ['Nicholas Carlini', 'Milad Nasr', 'Christopher A. Choquette-Choo', 'Matthew Jagielski', 'Irena Gao', 'Anas Awadalla', 'Pang Wei Koh', 'Daphne Ippolito', 'Katherine Lee', 'Florian Tramer', 'Ludwig Schmidt'] | ['cs.CL', 'cs.AI', 'cs.CR', 'cs.LG'] | Large language models are now tuned to align with the goals of their
creators, namely to be "helpful and harmless." These models should respond
helpfully to user questions, but refuse to answer requests that could cause
harm. However, adversarial users can construct inputs which circumvent attempts
at alignment. In thi... | 2023-06-26T17:18:44Z | null | null | null | Are aligned neural networks adversarially aligned? | ['Nicholas Carlini', 'Milad Nasr', 'Christopher A. Choquette-Choo', 'Matthew Jagielski', 'Irena Gao', 'Anas Awadalla', 'Pang Wei Koh', 'Daphne Ippolito', 'Katherine Lee', 'Florian Tramèr', 'Ludwig Schmidt'] | 2,023 | Neural Information Processing Systems | 254 | 57 | ['Computer Science'] |
2,306.15595 | Extending Context Window of Large Language Models via Positional
Interpolation | ['Shouyuan Chen', 'Sherman Wong', 'Liangjian Chen', 'Yuandong Tian'] | ['cs.CL', 'cs.AI', 'cs.LG'] | We present Position Interpolation (PI) that extends the context window sizes
of RoPE-based pretrained LLMs such as LLaMA models to up to 32768 with minimal
fine-tuning (within 1000 steps), while demonstrating strong empirical results
on various tasks that require long context, including passkey retrieval,
language mode... | 2023-06-27T16:26:26Z | Fix template issues | null | null | Extending Context Window of Large Language Models via Positional Interpolation | ['Shouyuan Chen', 'Sherman Wong', 'Liangjian Chen', 'Yuandong Tian'] | 2,023 | arXiv.org | 544 | 47 | ['Computer Science'] |
2,306.15604 | Constructing Multilingual Code Search Dataset Using Neural Machine
Translation | ['Ryo Sekizawa', 'Nan Duan', 'Shuai Lu', 'Hitomi Yanaka'] | ['cs.CL', 'cs.SE'] | Code search is a task to find programming codes that semantically match the
given natural language queries. Even though some of the existing datasets for
this task are multilingual on the programming language side, their query data
are only in English. In this research, we create a multilingual code search
dataset in f... | 2023-06-27T16:42:36Z | To appear in the Proceedings of the ACL2023 Student Research Workshop
(SRW) | null | null | null | null | null | null | null | null | null |
2,306.15626 | LeanDojo: Theorem Proving with Retrieval-Augmented Language Models | ['Kaiyu Yang', 'Aidan M. Swope', 'Alex Gu', 'Rahul Chalamala', 'Peiyang Song', 'Shixing Yu', 'Saad Godil', 'Ryan Prenger', 'Anima Anandkumar'] | ['cs.LG', 'cs.AI', 'cs.LO', 'stat.ML'] | Large language models (LLMs) have shown promise in proving formal theorems
using proof assistants such as Lean. However, existing methods are difficult to
reproduce or build on, due to private code, data, and large compute
requirements. This has created substantial barriers to research on machine
learning methods for t... | 2023-06-27T17:05:32Z | Accepted to NeurIPS 2023 (Datasets and Benchmarks Track) as an oral
presentation. Data, code, and models available at https://leandojo.org/ | null | null | null | null | null | null | null | null | null |
2,306.15658 | CLIPA-v2: Scaling CLIP Training with 81.1% Zero-shot ImageNet Accuracy
within a \$10,000 Budget; An Extra \$4,000 Unlocks 81.8% Accuracy | ['Xianhang Li', 'Zeyu Wang', 'Cihang Xie'] | ['cs.CV'] | The recent work CLIPA presents an inverse scaling law for CLIP training --
whereby the larger the image/text encoders used, the shorter the sequence
length of image/text tokens that can be applied in training. This finding
enables us to train high-performance CLIP models with significantly reduced
computations. Buildin... | 2023-06-27T17:51:06Z | Tech Report. Code is available at https://github.com/UCSC-VLAA/CLIPA | null | null | null | null | null | null | null | null | null |
2,306.15687 | Voicebox: Text-Guided Multilingual Universal Speech Generation at Scale | ['Matthew Le', 'Apoorv Vyas', 'Bowen Shi', 'Brian Karrer', 'Leda Sari', 'Rashel Moritz', 'Mary Williamson', 'Vimal Manohar', 'Yossi Adi', 'Jay Mahadeokar', 'Wei-Ning Hsu'] | ['eess.AS', 'cs.CL', 'cs.LG', 'cs.SD'] | Large-scale generative models such as GPT and DALL-E have revolutionized the
research community. These models not only generate high fidelity outputs, but
are also generalists which can solve tasks not explicitly taught. In contrast,
speech generative models are still primitive in terms of scale and task
generalization... | 2023-06-23T16:23:24Z | Accepted to NeurIPS 2023 | null | null | null | null | null | null | null | null | null |
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