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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2,305.14342 | Sophia: A Scalable Stochastic Second-order Optimizer for Language Model
Pre-training | ['Hong Liu', 'Zhiyuan Li', 'David Hall', 'Percy Liang', 'Tengyu Ma'] | ['cs.LG', 'cs.CL', 'math.OC'] | Given the massive cost of language model pre-training, a non-trivial
improvement of the optimization algorithm would lead to a material reduction on
the time and cost of training. Adam and its variants have been state-of-the-art
for years, and more sophisticated second-order (Hessian-based) optimizers often
incur too m... | 2023-05-23T17:59:21Z | null | null | null | null | null | null | null | null | null | null |
2,305.14378 | Predicting Stock Market Time-Series Data using CNN-LSTM Neural Network
Model | ['Aadhitya A', 'Rajapriya R', 'Vineetha R S', 'Anurag M Bagde'] | ['q-fin.ST', 'cs.LG'] | Stock market is often important as it represents the ownership claims on
businesses. Without sufficient stocks, a company cannot perform well in
finance. Predicting a stock market performance of a company is nearly hard
because every time the prices of a company stock keeps changing and not
constant. So, its complex to... | 2023-05-21T08:00:23Z | 8 pages, 9 figures, 5 tables | null | null | Predicting Stock Market Time-Series Data using CNN-LSTM Neural Network Model | ['A. Aadhitya', 'R. Rajapriya', 'S. VineethaR', 'Anurag M Bagde'] | 2,023 | arXiv.org | 9 | 20 | ['Economics', 'Computer Science'] |
2,305.14458 | Dancing Between Success and Failure: Edit-level Simplification
Evaluation using SALSA | ['David Heineman', 'Yao Dou', 'Mounica Maddela', 'Wei Xu'] | ['cs.CL'] | Large language models (e.g., GPT-4) are uniquely capable of producing highly
rated text simplification, yet current human evaluation methods fail to provide
a clear understanding of systems' specific strengths and weaknesses. To address
this limitation, we introduce SALSA, an edit-based human annotation framework
that ... | 2023-05-23T18:30:49Z | Accepted to EMNLP 2023 | null | null | null | null | null | null | null | null | null |
2,305.14463 | ReadMe++: Benchmarking Multilingual Language Models for Multi-Domain
Readability Assessment | ['Tarek Naous', 'Michael J. Ryan', 'Anton Lavrouk', 'Mohit Chandra', 'Wei Xu'] | ['cs.CL', 'cs.AI', 'cs.LG'] | We present a comprehensive evaluation of large language models for
multilingual readability assessment. Existing evaluation resources lack domain
and language diversity, limiting the ability for cross-domain and cross-lingual
analyses. This paper introduces ReadMe++, a multilingual multi-domain dataset
with human annot... | 2023-05-23T18:37:30Z | Accepted to EMNLP 2024 Main Conference | null | null | ReadMe++: Benchmarking Multilingual Language Models for Multi-Domain Readability Assessment | ['Tarek Naous', 'Michael Joseph Ryan', 'Mohit Chandra', 'Wei Xu'] | 2,023 | Conference on Empirical Methods in Natural Language Processing | 8 | 101 | ['Computer Science', 'Medicine'] |
2,305.14471 | CGCE: A Chinese Generative Chat Evaluation Benchmark for General and
Financial Domains | ['Xuanyu Zhang', 'Bingbing Li', 'Qing Yang'] | ['cs.CL'] | Generative chat models, such as ChatGPT and GPT-4, have revolutionized
natural language generation (NLG) by incorporating instructions and human
feedback to achieve significant performance improvements. However, the lack of
standardized evaluation benchmarks for chat models, particularly for Chinese
and domain-specific... | 2023-05-23T18:54:15Z | null | null | null | null | null | null | null | null | null | null |
2,305.14481 | FOCUS: Effective Embedding Initialization for Monolingual Specialization
of Multilingual Models | ['Konstantin Dobler', 'Gerard de Melo'] | ['cs.CL'] | Using model weights pretrained on a high-resource language as a warm start
can reduce the need for data and compute to obtain high-quality language models
for other, especially low-resource, languages. However, if we want to use a new
tokenizer specialized for the target language, we cannot transfer the source
model's ... | 2023-05-23T19:21:53Z | Accepted to EMNLP 2023 Main Conference (Long Paper). Code:
https://github.com/konstantinjdobler/focus | null | 10.18653/v1/2023.emnlp-main.829 | null | null | null | null | null | null | null |
2,305.14677 | Optimal Linear Subspace Search: Learning to Construct Fast and
High-Quality Schedulers for Diffusion Models | ['Zhongjie Duan', 'Chengyu Wang', 'Cen Chen', 'Jun Huang', 'Weining Qian'] | ['cs.CV'] | In recent years, diffusion models have become the most popular and powerful
methods in the field of image synthesis, even rivaling human artists in
artistic creativity. However, the key issue currently limiting the application
of diffusion models is its extremely slow generation process. Although several
methods were p... | 2023-05-24T03:33:30Z | 13 pages, 5 figures | null | 10.1145/3583780.3614999 | Optimal Linear Subspace Search: Learning to Construct Fast and High-Quality Schedulers for Diffusion Models | ['Zhongjie Duan', 'Chengyu Wang', 'Cen Chen', 'Jun Huang', 'Weining Qian'] | 2,023 | International Conference on Information and Knowledge Management | 12 | 45 | ['Computer Science'] |
2,305.14688 | ExpertPrompting: Instructing Large Language Models to be Distinguished
Experts | ['Benfeng Xu', 'An Yang', 'Junyang Lin', 'Quan Wang', 'Chang Zhou', 'Yongdong Zhang', 'Zhendong Mao'] | ['cs.CL', 'cs.AI'] | The answering quality of an aligned large language model (LLM) can be
drastically improved if treated with proper crafting of prompts. In this paper,
we propose ExpertPrompting to elicit the potential of LLMs to answer as
distinguished experts. We first utilize In-Context Learning to automatically
synthesize detailed a... | 2023-05-24T03:51:31Z | null | null | null | null | null | null | null | null | null | null |
2,305.14718 | Leftover Lunch: Advantage-based Offline Reinforcement Learning for
Language Models | ['Ashutosh Baheti', 'Ximing Lu', 'Faeze Brahman', 'Ronan Le Bras', 'Maarten Sap', 'Mark Riedl'] | ['cs.CL'] | Reinforcement Learning with Human Feedback (RLHF) is the most prominent
method for Language Model (LM) alignment. However, RLHF is an unstable and
data-hungry process that continually requires new high-quality LM-generated
data for finetuning. We introduce Advantage-Leftover Lunch RL (A-LoL), a new
class of offline pol... | 2023-05-24T04:42:17Z | published at ICLR 2024 | null | null | null | null | null | null | null | null | null |
2,305.1472 | BLIP-Diffusion: Pre-trained Subject Representation for Controllable
Text-to-Image Generation and Editing | ['Dongxu Li', 'Junnan Li', 'Steven C. H. Hoi'] | ['cs.CV', 'cs.AI'] | Subject-driven text-to-image generation models create novel renditions of an
input subject based on text prompts. Existing models suffer from lengthy
fine-tuning and difficulties preserving the subject fidelity. To overcome these
limitations, we introduce BLIP-Diffusion, a new subject-driven image generation
model that... | 2023-05-24T04:51:04Z | null | null | null | BLIP-Diffusion: Pre-trained Subject Representation for Controllable Text-to-Image Generation and Editing | ['Dongxu Li', 'Junnan Li', 'Steven C. H. Hoi'] | 2,023 | Neural Information Processing Systems | 331 | 40 | ['Computer Science'] |
2,305.14734 | Advancements in Arabic Grammatical Error Detection and Correction: An
Empirical Investigation | ['Bashar Alhafni', 'Go Inoue', 'Christian Khairallah', 'Nizar Habash'] | ['cs.CL'] | Grammatical error correction (GEC) is a well-explored problem in English with
many existing models and datasets. However, research on GEC in morphologically
rich languages has been limited due to challenges such as data scarcity and
language complexity. In this paper, we present the first results on Arabic GEC
using tw... | 2023-05-24T05:12:58Z | Accepted to EMNLP 2023 | null | null | null | null | null | null | null | null | null |
2,305.14749 | gRNAde: Geometric Deep Learning for 3D RNA inverse design | ['Chaitanya K. Joshi', 'Arian R. Jamasb', 'Ramon Viñas', 'Charles Harris', 'Simon V. Mathis', 'Alex Morehead', 'Rishabh Anand', 'Pietro Liò'] | ['cs.LG', 'q-bio.BM', 'q-bio.QM'] | Computational RNA design tasks are often posed as inverse problems, where
sequences are designed based on adopting a single desired secondary structure
without considering 3D conformational diversity. We introduce gRNAde, a
geometric RNA design pipeline operating on 3D RNA backbones to design sequences
that explicitly ... | 2023-05-24T05:46:56Z | ICLR 2025 camera-ready version (Spotlight presentation). Previously
titled 'Multi-State RNA Design with Geometric Multi-Graph Neural Networks',
presented at ICML 2023 Computational Biology Workshop | null | null | gRNAde: Geometric Deep Learning for 3D RNA inverse design | ['Chaitanya K. Joshi', 'Arian R. Jamasb', 'Ramón Viñas', 'Charles Harris', 'Simon V. Mathis', 'P. Liò'] | 2,023 | bioRxiv | 18 | 63 | ['Medicine', 'Computer Science', 'Biology'] |
2,305.14761 | UniChart: A Universal Vision-language Pretrained Model for Chart
Comprehension and Reasoning | ['Ahmed Masry', 'Parsa Kavehzadeh', 'Xuan Long Do', 'Enamul Hoque', 'Shafiq Joty'] | ['cs.CL'] | Charts are very popular for analyzing data, visualizing key insights and
answering complex reasoning questions about data. To facilitate chart-based
data analysis using natural language, several downstream tasks have been
introduced recently such as chart question answering and chart summarization.
However, most of the... | 2023-05-24T06:11:17Z | null | null | null | null | null | null | null | null | null | null |
2,305.14783 | Disentangled Phonetic Representation for Chinese Spelling Correction | ['Zihong Liang', 'Xiaojun Quan', 'Qifan Wang'] | ['cs.CL'] | Chinese Spelling Correction (CSC) aims to detect and correct erroneous
characters in Chinese texts. Although efforts have been made to introduce
phonetic information (Hanyu Pinyin) in this task, they typically merge phonetic
representations with character representations, which tends to weaken the
representation effect... | 2023-05-24T06:39:12Z | Accepted to ACL 2023 Main Conference | null | null | null | null | null | null | null | null | null |
2,305.14788 | Adapting Language Models to Compress Contexts | ['Alexis Chevalier', 'Alexander Wettig', 'Anirudh Ajith', 'Danqi Chen'] | ['cs.CL'] | Transformer-based language models (LMs) are powerful and widely-applicable
tools, but their usefulness is constrained by a finite context window and the
expensive computational cost of processing long text documents. We propose to
adapt pre-trained LMs into AutoCompressors. These language models are capable
of compress... | 2023-05-24T06:42:44Z | Accepted to EMNLP 2023; added results for Llama-2-7B model | null | null | Adapting Language Models to Compress Contexts | ['Alexis Chevalier', 'Alexander Wettig', 'Anirudh Ajith', 'Danqi Chen'] | 2,023 | Conference on Empirical Methods in Natural Language Processing | 192 | 58 | ['Computer Science'] |
2,305.14904 | Identifying Informational Sources in News Articles | ['Alexander Spangher', 'Nanyun Peng', 'Jonathan May', 'Emilio Ferrara'] | ['cs.CL', 'cs.AI', 'cs.CY'] | News articles are driven by the informational sources journalists use in
reporting. Modeling when, how and why sources get used together in stories can
help us better understand the information we consume and even help journalists
with the task of producing it. In this work, we take steps toward this goal by
constructi... | 2023-05-24T08:56:35Z | 13 pages | null | null | null | null | null | null | null | null | null |
2,305.14964 | Detecting Multidimensional Political Incivility on Social Media | ['Sagi Pendzel', 'Nir Lotan', 'Alon Zoizner', 'Einat Minkov'] | ['cs.CL'] | The rise of social media has been argued to intensify uncivil and hostile
online political discourse. Yet, to date, there is a lack of clarity on what
incivility means in the political sphere. In this work, we utilize a
multidimensional perspective of political incivility, developed in the fields
of political science a... | 2023-05-24T09:57:12Z | null | null | null | null | null | null | null | null | null | null |
2,305.15011 | Bactrian-X: Multilingual Replicable Instruction-Following Models with
Low-Rank Adaptation | ['Haonan Li', 'Fajri Koto', 'Minghao Wu', 'Alham Fikri Aji', 'Timothy Baldwin'] | ['cs.CL'] | Instruction tuning has shown great promise in improving the performance of
large language models. However, research on multilingual instruction tuning has
been limited due to the scarcity of high-quality instruction-response datasets
across different languages. To bridge this gap, we present Bactrian-X, a
comprehensive... | 2023-05-24T10:50:31Z | null | null | null | null | null | null | null | null | null | null |
2,305.15017 | Calc-X and Calcformers: Empowering Arithmetical Chain-of-Thought through
Interaction with Symbolic Systems | ['Marek Kadlčík', 'Michal Štefánik', 'Ondřej Sotolář', 'Vlastimil Martinek'] | ['cs.LG', 'cs.AI', 'cs.CL'] | Despite outstanding performance in many tasks, language models are
notoriously inclined to make factual errors in tasks requiring arithmetic
computation. We address this deficiency by creating Calc-X, a collection of
datasets that demonstrates the appropriate use of a calculator in reasoning
chains. Calc-X is suitable ... | 2023-05-24T10:58:20Z | Published in EMNLP 2023: Main track | null | null | Calc-X and Calcformers: Empowering Arithmetical Chain-of-Thought through Interaction with Symbolic Systems | ['Marek Kadlcík', 'Michal Štefánik'] | 2,023 | Conference on Empirical Methods in Natural Language Processing | 15 | 21 | ['Computer Science'] |
2,305.15062 | Lawyer LLaMA Technical Report | ['Quzhe Huang', 'Mingxu Tao', 'Chen Zhang', 'Zhenwei An', 'Cong Jiang', 'Zhibin Chen', 'Zirui Wu', 'Yansong Feng'] | ['cs.CL', 'cs.AI'] | Large Language Models (LLMs), like LLaMA, have exhibited remarkable
performance across various tasks. Nevertheless, when deployed to specific
domains such as law or medicine, the models still confront the challenge of a
deficiency in domain-specific knowledge and an inadequate capability to
leverage that knowledge to r... | 2023-05-24T11:52:07Z | null | null | null | null | null | null | null | null | null | null |
2,305.15077 | Contrastive Learning of Sentence Embeddings from Scratch | ['Junlei Zhang', 'Zhenzhong Lan', 'Junxian He'] | ['cs.CL'] | Contrastive learning has been the dominant approach to train state-of-the-art
sentence embeddings. Previous studies have typically learned sentence
embeddings either through the use of human-annotated natural language inference
(NLI) data or via large-scale unlabeled sentences in an unsupervised manner.
However, even i... | 2023-05-24T11:56:21Z | Emnlp 2023 | null | null | null | null | null | null | null | null | null |
2,305.15194 | DiffBlender: Scalable and Composable Multimodal Text-to-Image Diffusion
Models | ['Sungnyun Kim', 'Junsoo Lee', 'Kibeom Hong', 'Daesik Kim', 'Namhyuk Ahn'] | ['cs.CV', 'cs.AI', 'cs.LG'] | In this study, we aim to extend the capabilities of diffusion-based
text-to-image (T2I) generation models by incorporating diverse modalities
beyond textual description, such as sketch, box, color palette, and style
embedding, within a single model. We thus design a multimodal T2I diffusion
model, coined as DiffBlender... | 2023-05-24T14:31:20Z | Project page: https://sungnyun.github.io/diffblender/ | null | null | DiffBlender: Scalable and Composable Multimodal Text-to-Image Diffusion Models | ['Sungnyun Kim', 'Junsoo Lee', 'Kibeom Hong', 'Daesik Kim', 'Namhyuk Ahn'] | 2,023 | arXiv.org | 15 | 61 | ['Computer Science'] |
2,305.15225 | SAIL: Search-Augmented Instruction Learning | ['Hongyin Luo', 'Yung-Sung Chuang', 'Yuan Gong', 'Tianhua Zhang', 'Yoon Kim', 'Xixin Wu', 'Danny Fox', 'Helen Meng', 'James Glass'] | ['cs.CL'] | Large language models (LLMs) have been significantly improved by instruction
fine-tuning, but still lack transparency and the ability to utilize up-to-date
knowledge and information. In this work, we propose search-augmented
instruction learning (SAIL), which grounds the language generation and
instruction following ab... | 2023-05-24T15:07:30Z | null | null | null | SAIL: Search-Augmented Instruction Learning | ['Hongyin Luo', 'Yung-Sung Chuang', 'Yuan Gong', 'Tianhua Zhang', 'Yoon Kim', 'Xixin Wu', 'D. Fox', 'H. Meng', 'James R. Glass'] | 2,023 | Conference on Empirical Methods in Natural Language Processing | 27 | 49 | ['Computer Science'] |
2,305.15272 | ViTMatte: Boosting Image Matting with Pretrained Plain Vision
Transformers | ['Jingfeng Yao', 'Xinggang Wang', 'Shusheng Yang', 'Baoyuan Wang'] | ['cs.CV'] | Recently, plain vision Transformers (ViTs) have shown impressive performance
on various computer vision tasks, thanks to their strong modeling capacity and
large-scale pretraining. However, they have not yet conquered the problem of
image matting. We hypothesize that image matting could also be boosted by ViTs
and pres... | 2023-05-24T15:59:35Z | codes: https://github.com/hustvl/ViTMatte | null | null | null | null | null | null | null | null | null |
2,305.15324 | Model evaluation for extreme risks | ['Toby Shevlane', 'Sebastian Farquhar', 'Ben Garfinkel', 'Mary Phuong', 'Jess Whittlestone', 'Jade Leung', 'Daniel Kokotajlo', 'Nahema Marchal', 'Markus Anderljung', 'Noam Kolt', 'Lewis Ho', 'Divya Siddarth', 'Shahar Avin', 'Will Hawkins', 'Been Kim', 'Iason Gabriel', 'Vijay Bolina', 'Jack Clark', 'Yoshua Bengio', 'Pau... | ['cs.AI', 'K.4.1'] | Current approaches to building general-purpose AI systems tend to produce
systems with both beneficial and harmful capabilities. Further progress in AI
development could lead to capabilities that pose extreme risks, such as
offensive cyber capabilities or strong manipulation skills. We explain why
model evaluation is c... | 2023-05-24T16:38:43Z | Fixed typos; added citation | null | null | null | null | null | null | null | null | null |
2,305.15334 | Gorilla: Large Language Model Connected with Massive APIs | ['Shishir G. Patil', 'Tianjun Zhang', 'Xin Wang', 'Joseph E. Gonzalez'] | ['cs.CL', 'cs.AI'] | Large Language Models (LLMs) have seen an impressive wave of advances
recently, with models now excelling in a variety of tasks, such as mathematical
reasoning and program synthesis. However, their potential to effectively use
tools via API calls remains unfulfilled. This is a challenging task even for
today's state-of... | 2023-05-24T16:48:11Z | null | null | null | null | null | null | null | null | null | null |
2,305.15391 | A Neural Space-Time Representation for Text-to-Image Personalization | ['Yuval Alaluf', 'Elad Richardson', 'Gal Metzer', 'Daniel Cohen-Or'] | ['cs.CV'] | A key aspect of text-to-image personalization methods is the manner in which
the target concept is represented within the generative process. This choice
greatly affects the visual fidelity, downstream editability, and disk space
needed to store the learned concept. In this paper, we explore a new
text-conditioning spa... | 2023-05-24T17:53:07Z | Project page available at
https://neuraltextualinversion.github.io/NeTI/ | null | null | null | null | null | null | null | null | null |
2,305.15541 | Harnessing the Power of Large Language Models for Natural Language to
First-Order Logic Translation | ['Yuan Yang', 'Siheng Xiong', 'Ali Payani', 'Ehsan Shareghi', 'Faramarz Fekri'] | ['cs.CL', 'cs.AI'] | Translating natural language sentences to first-order logic (NL-FOL
translation) is a longstanding challenge in the NLP and formal logic
literature. This paper introduces LogicLLaMA, a LLaMA-7B model fine-tuned for
NL-FOL translation using LoRA on a single GPU. LogicLLaMA is capable of
directly translating natural lang... | 2023-05-24T19:59:51Z | null | null | null | Harnessing the Power of Large Language Models for Natural Language to First-Order Logic Translation | ['Yuan Yang', 'Siheng Xiong', 'Ali Payani', 'Ehsan Shareghi', 'F. Fekri'] | 2,023 | Annual Meeting of the Association for Computational Linguistics | 41 | 33 | ['Computer Science'] |
2,305.15798 | BK-SDM: A Lightweight, Fast, and Cheap Version of Stable Diffusion | ['Bo-Kyeong Kim', 'Hyoung-Kyu Song', 'Thibault Castells', 'Shinkook Choi'] | ['cs.LG'] | Text-to-image (T2I) generation with Stable Diffusion models (SDMs) involves
high computing demands due to billion-scale parameters. To enhance efficiency,
recent studies have reduced sampling steps and applied network quantization
while retaining the original architectures. The lack of architectural reduction
attempts ... | 2023-05-25T07:28:28Z | ECCV 2024 Camera-Ready Version | null | 10.1007/978-3-031-72949-2 | Computer Vision - ECCV 2024 - 18th European Conference, Milan, Italy, September 29-October 4, 2024, Proceedings, Part LIV | ['Bo-Kyeong Kim', 'Hyoung-Kyu Song', 'Thibault Castells', 'Shinkook Choi'] | 2,023 | European Conference on Computer Vision | 11 | 89 | ['Computer Science'] |
2,305.16023 | NaSGEC: a Multi-Domain Chinese Grammatical Error Correction Dataset from
Native Speaker Texts | ['Yue Zhang', 'Bo Zhang', 'Haochen Jiang', 'Zhenghua Li', 'Chen Li', 'Fei Huang', 'Min Zhang'] | ['cs.CL'] | We introduce NaSGEC, a new dataset to facilitate research on Chinese
grammatical error correction (CGEC) for native speaker texts from multiple
domains. Previous CGEC research primarily focuses on correcting texts from a
single domain, especially learner essays. To broaden the target domain, we
annotate multiple refere... | 2023-05-25T13:05:52Z | Accepted by ACL 2023 (Findings, long paper) | null | null | null | null | null | null | null | null | null |
2,305.16037 | GenerateCT: Text-Conditional Generation of 3D Chest CT Volumes | ['Ibrahim Ethem Hamamci', 'Sezgin Er', 'Anjany Sekuboyina', 'Enis Simsar', 'Alperen Tezcan', 'Ayse Gulnihan Simsek', 'Sevval Nil Esirgun', 'Furkan Almas', 'Irem Dogan', 'Muhammed Furkan Dasdelen', 'Chinmay Prabhakar', 'Hadrien Reynaud', 'Sarthak Pati', 'Christian Bluethgen', 'Mehmet Kemal Ozdemir', 'Bjoern Menze'] | ['cs.CV'] | GenerateCT, the first approach to generating 3D medical imaging conditioned
on free-form medical text prompts, incorporates a text encoder and three key
components: a novel causal vision transformer for encoding 3D CT volumes, a
text-image transformer for aligning CT and text tokens, and a text-conditional
super-resolu... | 2023-05-25T13:16:39Z | null | null | null | GenerateCT: Text-Conditional Generation of 3D Chest CT Volumes | ['Ibrahim Ethem Hamamci', 'Sezgin Er', 'Enis Simsar', 'A. Sekuboyina', 'Chinmay Prabhakar', 'A. Tezcan', 'Ayse Gulnihan Simsek', 'S. Esirgun', 'Furkan Almas', 'Irem Dougan', 'M. F. Dasdelen', 'Hadrien Reynaud', 'Sarthak Pati', 'Christian Bluethgen', 'M. K. Ozdemir', 'Bjoern H Menze'] | 2,023 | European Conference on Computer Vision | 24 | 48 | ['Computer Science'] |
2,305.16066 | Guided Attention for Next Active Object @ EGO4D STA Challenge | ['Sanket Thakur', 'Cigdem Beyan', 'Pietro Morerio', 'Vittorio Murino', 'Alessio Del Bue'] | ['cs.CV'] | In this technical report, we describe the Guided-Attention mechanism based
solution for the short-term anticipation (STA) challenge for the EGO4D
challenge. It combines the object detections, and the spatiotemporal features
extracted from video clips, enhancing the motion and contextual information,
and further decodin... | 2023-05-25T13:56:30Z | Winner of CVPR@2023 Ego4D STA challenge. arXiv admin note:
substantial text overlap with arXiv:2305.12953 | null | null | null | null | null | null | null | null | null |
2,305.16264 | Scaling Data-Constrained Language Models | ['Niklas Muennighoff', 'Alexander M. Rush', 'Boaz Barak', 'Teven Le Scao', 'Aleksandra Piktus', 'Nouamane Tazi', 'Sampo Pyysalo', 'Thomas Wolf', 'Colin Raffel'] | ['cs.CL', 'cs.AI', 'cs.LG'] | The current trend of scaling language models involves increasing both
parameter count and training dataset size. Extrapolating this trend suggests
that training dataset size may soon be limited by the amount of text data
available on the internet. Motivated by this limit, we investigate scaling
language models in data-... | 2023-05-25T17:18:55Z | 50 pages (9 main), 39 figures, 15 tables | null | null | null | null | null | null | null | null | null |
2,305.163 | Landmark Attention: Random-Access Infinite Context Length for
Transformers | ['Amirkeivan Mohtashami', 'Martin Jaggi'] | ['cs.CL', 'cs.LG'] | While Transformers have shown remarkable success in natural language
processing, their attention mechanism's large memory requirements have limited
their ability to handle longer contexts. Prior approaches, such as recurrent
memory or retrieval-based augmentation, have either compromised the
random-access flexibility o... | 2023-05-25T17:53:42Z | Published as a conference paper at NeurIPS 2023 - 37th Conference on
Neural Information Processing Systems | null | null | null | null | null | null | null | null | null |
2,305.16307 | IndicTrans2: Towards High-Quality and Accessible Machine Translation
Models for all 22 Scheduled Indian Languages | ['Jay Gala', 'Pranjal A. Chitale', 'Raghavan AK', 'Varun Gumma', 'Sumanth Doddapaneni', 'Aswanth Kumar', 'Janki Nawale', 'Anupama Sujatha', 'Ratish Puduppully', 'Vivek Raghavan', 'Pratyush Kumar', 'Mitesh M. Khapra', 'Raj Dabre', 'Anoop Kunchukuttan'] | ['cs.CL'] | India has a rich linguistic landscape with languages from 4 major language
families spoken by over a billion people. 22 of these languages are listed in
the Constitution of India (referred to as scheduled languages) are the focus of
this work. Given the linguistic diversity, high-quality and accessible Machine
Translat... | 2023-05-25T17:57:43Z | Accepted at TMLR | null | null | null | null | null | null | null | null | null |
2,305.16315 | NAP: Neural 3D Articulation Prior | ['Jiahui Lei', 'Congyue Deng', 'Bokui Shen', 'Leonidas Guibas', 'Kostas Daniilidis'] | ['cs.CV'] | We propose Neural 3D Articulation Prior (NAP), the first 3D deep generative
model to synthesize 3D articulated object models. Despite the extensive
research on generating 3D objects, compositions, or scenes, there remains a
lack of focus on capturing the distribution of articulated objects, a common
object category for... | 2023-05-25T17:59:35Z | project page: https://www.cis.upenn.edu/~leijh/projects/nap | null | null | null | null | null | null | null | null | null |
2,305.16355 | PandaGPT: One Model To Instruction-Follow Them All | ['Yixuan Su', 'Tian Lan', 'Huayang Li', 'Jialu Xu', 'Yan Wang', 'Deng Cai'] | ['cs.CL', 'cs.CV'] | We present PandaGPT, an approach to emPower large lANguage moDels with visual
and Auditory instruction-following capabilities. Our pilot experiments show
that PandaGPT can perform complex tasks such as detailed image description
generation, writing stories inspired by videos, and answering questions about
audios. More ... | 2023-05-25T04:16:07Z | Technical report, work in progress. Our project page is at
https://panda-gpt.github.io/ | null | null | PandaGPT: One Model To Instruction-Follow Them All | ['Yixuan Su', 'Tian Lan', 'Huayang Li', 'Jialu Xu', 'Yan Wang', 'Deng Cai'] | 2,023 | Tsinghua Interdisciplinary Workshop on Logic, Language and Meaning | 295 | 37 | ['Computer Science'] |
2,305.16504 | On the Tool Manipulation Capability of Open-source Large Language Models | ['Qiantong Xu', 'Fenglu Hong', 'Bo Li', 'Changran Hu', 'Zhengyu Chen', 'Jian Zhang'] | ['cs.CL', 'cs.AI', 'cs.LG'] | Recent studies on software tool manipulation with large language models
(LLMs) mostly rely on closed model APIs. The industrial adoption of these
models is substantially constrained due to the security and robustness risks in
exposing information to closed LLM API services. In this paper, we ask can we
enhance open-sou... | 2023-05-25T22:10:20Z | null | null | null | On the Tool Manipulation Capability of Open-source Large Language Models | ['Qiantong Xu', 'Fenglu Hong', 'B. Li', 'Changran Hu', 'Zheng Chen', 'Jian Zhang'] | 2,023 | arXiv.org | 78 | 68 | ['Computer Science'] |
2,305.16636 | DataFinder: Scientific Dataset Recommendation from Natural Language
Descriptions | ['Vijay Viswanathan', 'Luyu Gao', 'Tongshuang Wu', 'Pengfei Liu', 'Graham Neubig'] | ['cs.IR', 'cs.CL', 'cs.DL'] | Modern machine learning relies on datasets to develop and validate research
ideas. Given the growth of publicly available data, finding the right dataset
to use is increasingly difficult. Any research question imposes explicit and
implicit constraints on how well a given dataset will enable researchers to
answer this q... | 2023-05-26T05:22:36Z | To appear at ACL 2023. Code published at
https://github.com/viswavi/datafinder | null | null | DataFinder: Scientific Dataset Recommendation from Natural Language Descriptions | ['Vijay Viswanathan', 'Luyu Gao', 'Tongshuang Sherry Wu', 'Pengfei Liu', 'Graham Neubig'] | 2,023 | Annual Meeting of the Association for Computational Linguistics | 13 | 53 | ['Computer Science'] |
2,305.16739 | AlignScore: Evaluating Factual Consistency with a Unified Alignment
Function | ['Yuheng Zha', 'Yichi Yang', 'Ruichen Li', 'Zhiting Hu'] | ['cs.CL'] | Many text generation applications require the generated text to be factually
consistent with input information. Automatic evaluation of factual consistency
is challenging. Previous work has developed various metrics that often depend
on specific functions, such as natural language inference (NLI) or question
answering ... | 2023-05-26T08:41:59Z | 19 pages, 5 figures, ACL2023 | null | null | null | null | null | null | null | null | null |
2,305.16765 | Backpack Language Models | ['John Hewitt', 'John Thickstun', 'Christopher D. Manning', 'Percy Liang'] | ['cs.CL'] | We present Backpacks: a new neural architecture that marries strong modeling
performance with an interface for interpretability and control. Backpacks learn
multiple non-contextual sense vectors for each word in a vocabulary, and
represent a word in a sequence as a context-dependent, non-negative linear
combination of ... | 2023-05-26T09:26:23Z | ACL 2023 Camera-Ready | null | null | Backpack Language Models | ['John Hewitt', 'John Thickstun', 'Christopher D. Manning', 'Percy Liang'] | 2,023 | Annual Meeting of the Association for Computational Linguistics | 16 | 59 | ['Computer Science'] |
2,305.16799 | To Revise or Not to Revise: Learning to Detect Improvable Claims for
Argumentative Writing Support | ['Gabriella Skitalinskaya', 'Henning Wachsmuth'] | ['cs.CL'] | Optimizing the phrasing of argumentative text is crucial in higher education
and professional development. However, assessing whether and how the different
claims in a text should be revised is a hard task, especially for novice
writers. In this work, we explore the main challenges to identifying
argumentative claims i... | 2023-05-26T10:19:54Z | Accepted as a long paper at ACL 2023 | null | null | null | null | null | null | null | null | null |
2,305.16944 | Learning to Imagine: Visually-Augmented Natural Language Generation | ['Tianyi Tang', 'Yushuo Chen', 'Yifan Du', 'Junyi Li', 'Wayne Xin Zhao', 'Ji-Rong Wen'] | ['cs.CL'] | People often imagine relevant scenes to aid in the writing process. In this
work, we aim to utilize visual information for composition in the same manner
as humans. We propose a method, LIVE, that makes pre-trained language models
(PLMs) Learn to Imagine for Visuallyaugmented natural language gEneration.
First, we imag... | 2023-05-26T13:59:45Z | Accepted by ACL 2023 | null | null | null | null | null | null | null | null | null |
2,305.16958 | MixCE: Training Autoregressive Language Models by Mixing Forward and
Reverse Cross-Entropies | ['Shiyue Zhang', 'Shijie Wu', 'Ozan Irsoy', 'Steven Lu', 'Mohit Bansal', 'Mark Dredze', 'David Rosenberg'] | ['cs.CL', 'cs.AI', 'cs.LG'] | Autoregressive language models are trained by minimizing the cross-entropy of
the model distribution Q relative to the data distribution P -- that is,
minimizing the forward cross-entropy, which is equivalent to maximum likelihood
estimation (MLE). We have observed that models trained in this way may
"over-generalize",... | 2023-05-26T14:14:51Z | ACL 2023 (22 pages) | null | null | null | null | null | null | null | null | null |
2,305.1696 | Training Socially Aligned Language Models on Simulated Social
Interactions | ['Ruibo Liu', 'Ruixin Yang', 'Chenyan Jia', 'Ge Zhang', 'Denny Zhou', 'Andrew M. Dai', 'Diyi Yang', 'Soroush Vosoughi'] | ['cs.CL', 'cs.AI', 'cs.CY', 'cs.HC'] | Social alignment in AI systems aims to ensure that these models behave
according to established societal values. However, unlike humans, who derive
consensus on value judgments through social interaction, current language
models (LMs) are trained to rigidly replicate their training corpus in
isolation, leading to subpa... | 2023-05-26T14:17:36Z | Code, data, and models can be downloaded via
https://github.com/agi-templar/Stable-Alignment | null | null | Training Socially Aligned Language Models on Simulated Social Interactions | ['Ruibo Liu', 'Ruixin Yang', 'Chenyan Jia', 'Ge Zhang', 'Denny Zhou', 'Andrew M. Dai', 'Diyi Yang', 'Soroush Vosoughi'] | 2,023 | International Conference on Learning Representations | 56 | 79 | ['Computer Science'] |
2,305.17438 | On the Importance of Backbone to the Adversarial Robustness of Object
Detectors | ['Xiao Li', 'Hang Chen', 'Xiaolin Hu'] | ['cs.CV', 'cs.AI', 'cs.CR', 'cs.LG'] | Object detection is a critical component of various security-sensitive
applications, such as autonomous driving and video surveillance. However,
existing object detectors are vulnerable to adversarial attacks, which poses a
significant challenge to their reliability and security. Through experiments,
first, we found th... | 2023-05-27T10:26:23Z | Accepted by IEEE TIFS | null | null | null | null | null | null | null | null | null |
2,305.17493 | The Curse of Recursion: Training on Generated Data Makes Models Forget | ['Ilia Shumailov', 'Zakhar Shumaylov', 'Yiren Zhao', 'Yarin Gal', 'Nicolas Papernot', 'Ross Anderson'] | ['cs.LG', 'cs.AI', 'cs.CL', 'cs.CR', 'cs.CV'] | Stable Diffusion revolutionised image creation from descriptive text. GPT-2,
GPT-3(.5) and GPT-4 demonstrated astonishing performance across a variety of
language tasks. ChatGPT introduced such language models to the general public.
It is now clear that large language models (LLMs) are here to stay, and will
bring abou... | 2023-05-27T15:10:41Z | Fixed typos in eqn 4,5 | null | null | null | null | null | null | null | null | null |
2,305.17718 | FuseCap: Leveraging Large Language Models for Enriched Fused Image
Captions | ['Noam Rotstein', 'David Bensaid', 'Shaked Brody', 'Roy Ganz', 'Ron Kimmel'] | ['cs.CV', 'cs.AI', 'cs.CL'] | The advent of vision-language pre-training techniques enhanced substantial
progress in the development of models for image captioning. However, these
models frequently produce generic captions and may omit semantically important
image details. This limitation can be traced back to the image-text datasets;
while their c... | 2023-05-28T13:16:03Z | null | null | null | null | null | null | null | null | null | null |
2,305.17721 | Rethinking Masked Language Modeling for Chinese Spelling Correction | ['Hongqiu Wu', 'Shaohua Zhang', 'Yuchen Zhang', 'Hai Zhao'] | ['cs.CL'] | In this paper, we study Chinese Spelling Correction (CSC) as a joint decision
made by two separate models: a language model and an error model. Through
empirical analysis, we find that fine-tuning BERT tends to over-fit the error
model while under-fit the language model, resulting in poor generalization to
out-of-distr... | 2023-05-28T13:19:12Z | Accepted by ACL'2023 | null | null | null | null | null | null | null | null | null |
2,305.17746 | Whitening-based Contrastive Learning of Sentence Embeddings | ['Wenjie Zhuo', 'Yifan Sun', 'Xiaohan Wang', 'Linchao Zhu', 'Yi Yang'] | ['cs.CL'] | This paper presents a whitening-based contrastive learning method for
sentence embedding learning (WhitenedCSE), which combines contrastive learning
with a novel shuffled group whitening. Generally, contrastive learning pulls
distortions of a single sample (i.e., positive samples) close and push negative
samples far aw... | 2023-05-28T14:58:10Z | ACL 2023 Main Conference(Oral) | null | null | WhitenedCSE: Whitening-based Contrastive Learning of Sentence Embeddings | ['Wenjie Zhuo', 'Yifan Sun', 'Xiaohan Wang', 'Linchao Zhu', 'Yezhou Yang'] | 2,023 | Annual Meeting of the Association for Computational Linguistics | 21 | 54 | ['Computer Science'] |
2,305.18098 | BigTranslate: Augmenting Large Language Models with Multilingual
Translation Capability over 100 Languages | ['Wen Yang', 'Chong Li', 'Jiajun Zhang', 'Chengqing Zong'] | ['cs.CL'] | Large language models (LLMs) demonstrate promising translation performance
among various natural languages. However, many LLMs especially the open-sourced
ones, such as BLOOM and LLaMA, are English-dominant and support only dozens of
natural languages, making the potential of LLMs on language translation less
explored.... | 2023-05-29T14:07:52Z | 16 pages, 4 figures. Our model is available at
https://github.com/ZNLP/BigTranslate | null | null | null | null | null | null | null | null | null |
2,305.18149 | Multiscale Positive-Unlabeled Detection of AI-Generated Texts | ['Yuchuan Tian', 'Hanting Chen', 'Xutao Wang', 'Zheyuan Bai', 'Qinghua Zhang', 'Ruifeng Li', 'Chao Xu', 'Yunhe Wang'] | ['cs.CL', 'cs.AI'] | Recent releases of Large Language Models (LLMs), e.g. ChatGPT, are
astonishing at generating human-like texts, but they may impact the
authenticity of texts. Previous works proposed methods to detect these
AI-generated texts, including simple ML classifiers, pretrained-model-based
zero-shot methods, and finetuned langu... | 2023-05-29T15:25:00Z | ICLR2024 (Spotlight) | null | null | null | null | null | null | null | null | null |
2,305.18203 | Concept Decomposition for Visual Exploration and Inspiration | ['Yael Vinker', 'Andrey Voynov', 'Daniel Cohen-Or', 'Ariel Shamir'] | ['cs.CV'] | A creative idea is often born from transforming, combining, and modifying
ideas from existing visual examples capturing various concepts. However, one
cannot simply copy the concept as a whole, and inspiration is achieved by
examining certain aspects of the concept. Hence, it is often necessary to
separate a concept in... | 2023-05-29T16:56:56Z | https://inspirationtree.github.io/inspirationtree/ | null | null | null | null | null | null | null | null | null |
2,305.18283 | CommonAccent: Exploring Large Acoustic Pretrained Models for Accent
Classification Based on Common Voice | ['Juan Zuluaga-Gomez', 'Sara Ahmed', 'Danielius Visockas', 'Cem Subakan'] | ['cs.CL', 'cs.AI', 'cs.LG', 'eess.AS'] | Despite the recent advancements in Automatic Speech Recognition (ASR), the
recognition of accented speech still remains a dominant problem. In order to
create more inclusive ASR systems, research has shown that the integration of
accent information, as part of a larger ASR framework, can lead to the
mitigation of accen... | 2023-05-29T17:53:35Z | To appear in Proceedings of the Annual Conference of the
International Speech Communication Association, INTERSPEECH 2023 | null | null | null | null | null | null | null | null | null |
2,305.1829 | Direct Preference Optimization: Your Language Model is Secretly a Reward
Model | ['Rafael Rafailov', 'Archit Sharma', 'Eric Mitchell', 'Stefano Ermon', 'Christopher D. Manning', 'Chelsea Finn'] | ['cs.LG', 'cs.AI', 'cs.CL'] | While large-scale unsupervised language models (LMs) learn broad world
knowledge and some reasoning skills, achieving precise control of their
behavior is difficult due to the completely unsupervised nature of their
training. Existing methods for gaining such steerability collect human labels
of the relative quality of... | 2023-05-29T17:57:46Z | null | null | null | Direct Preference Optimization: Your Language Model is Secretly a Reward Model | ['Rafael Rafailov', 'Archit Sharma', 'E. Mitchell', 'Stefano Ermon', 'Christopher D. Manning', 'Chelsea Finn'] | 2,023 | Neural Information Processing Systems | 4,190 | 60 | ['Computer Science'] |
2,305.18474 | Make-An-Audio 2: Temporal-Enhanced Text-to-Audio Generation | ['Jiawei Huang', 'Yi Ren', 'Rongjie Huang', 'Dongchao Yang', 'Zhenhui Ye', 'Chen Zhang', 'Jinglin Liu', 'Xiang Yin', 'Zejun Ma', 'Zhou Zhao'] | ['cs.SD', 'cs.LG', 'cs.MM', 'eess.AS'] | Large diffusion models have been successful in text-to-audio (T2A) synthesis
tasks, but they often suffer from common issues such as semantic misalignment
and poor temporal consistency due to limited natural language understanding and
data scarcity. Additionally, 2D spatial structures widely used in T2A works
lead to u... | 2023-05-29T10:41:28Z | null | null | null | Make-An-Audio 2: Temporal-Enhanced Text-to-Audio Generation | ['Jia-Bin Huang', 'Yi Ren', 'Rongjie Huang', 'Dongchao Yang', 'Zhenhui Ye', 'Chen Zhang', 'Jinglin Liu', 'Xiang Yin', 'Zejun Ma', 'Zhou Zhao'] | 2,023 | arXiv.org | 64 | 56 | ['Computer Science', 'Engineering'] |
2,305.18701 | Optimizing Attention and Cognitive Control Costs Using
Temporally-Layered Architectures | ['Devdhar Patel', 'Terrence Sejnowski', 'Hava Siegelmann'] | ['cs.AI', 'cs.SY', 'eess.SY'] | The current reinforcement learning framework focuses exclusively on
performance, often at the expense of efficiency. In contrast, biological
control achieves remarkable performance while also optimizing computational
energy expenditure and decision frequency. We propose a Decision Bounded Markov
Decision Process (DB-MD... | 2023-05-30T02:59:06Z | 50 Pages, 9 Figures, 6 Tables. Replacement after being published in
the journal Neural Computation | Neural Computation, 1-30 (2024) | 10.1162/neco_a_01718 | Optimizing Attention and Cognitive Control Costs Using Temporally Layered Architectures | ['Devdhar Patel', 'T. Sejnowski', 'H. Siegelmann'] | 2,023 | Neural Computation | 2 | 52 | ['Computer Science', 'Engineering', 'Medicine'] |
2,305.18802 | LibriTTS-R: A Restored Multi-Speaker Text-to-Speech Corpus | ['Yuma Koizumi', 'Heiga Zen', 'Shigeki Karita', 'Yifan Ding', 'Kohei Yatabe', 'Nobuyuki Morioka', 'Michiel Bacchiani', 'Yu Zhang', 'Wei Han', 'Ankur Bapna'] | ['eess.AS', 'cs.SD'] | This paper introduces a new speech dataset called ``LibriTTS-R'' designed for
text-to-speech (TTS) use. It is derived by applying speech restoration to the
LibriTTS corpus, which consists of 585 hours of speech data at 24 kHz sampling
rate from 2,456 speakers and the corresponding texts. The constituent samples
of Libr... | 2023-05-30T07:30:21Z | Accepted to Interspeech 2023 | null | null | null | null | null | null | null | null | null |
2,305.18939 | DEPLAIN: A German Parallel Corpus with Intralingual Translations into
Plain Language for Sentence and Document Simplification | ['Regina Stodden', 'Omar Momen', 'Laura Kallmeyer'] | ['cs.CL'] | Text simplification is an intralingual translation task in which documents,
or sentences of a complex source text are simplified for a target audience. The
success of automatic text simplification systems is highly dependent on the
quality of parallel data used for training and evaluation. To advance sentence
simplific... | 2023-05-30T11:07:46Z | Accepted to ACL 2023 | null | 10.18653/v1/2023.acl-long.908 | DEplain: A German Parallel Corpus with Intralingual Translations into Plain Language for Sentence and Document Simplification | ['Regina Stodden', 'Omar Momen', 'Laura Kallmeyer'] | 2,023 | Annual Meeting of the Association for Computational Linguistics | 15 | 72 | ['Computer Science'] |
2,305.19269 | Make-A-Voice: Unified Voice Synthesis With Discrete Representation | ['Rongjie Huang', 'Chunlei Zhang', 'Yongqi Wang', 'Dongchao Yang', 'Luping Liu', 'Zhenhui Ye', 'Ziyue Jiang', 'Chao Weng', 'Zhou Zhao', 'Dong Yu'] | ['eess.AS', 'cs.AI', 'cs.CL', 'cs.SD'] | Various applications of voice synthesis have been developed independently
despite the fact that they generate "voice" as output in common. In addition,
the majority of voice synthesis models currently rely on annotated audio data,
but it is crucial to scale them to self-supervised datasets in order to
effectively captu... | 2023-05-30T17:59:26Z | null | null | null | Make-A-Voice: Unified Voice Synthesis With Discrete Representation | ['Rongjie Huang', 'Chunlei Zhang', 'Yongqiang Wang', 'Dongchao Yang', 'Lu Liu', 'Zhenhui Ye', 'Ziyue Jiang', 'Chao Weng', 'Zhou Zhao', 'Dong Yu'] | 2,023 | arXiv.org | 27 | 47 | ['Engineering', 'Computer Science'] |
2,305.1937 | Blockwise Parallel Transformer for Large Context Models | ['Hao Liu', 'Pieter Abbeel'] | ['cs.CL', 'cs.LG'] | Transformers have emerged as the cornerstone of state-of-the-art natural
language processing models, showcasing exceptional performance across a wide
range of AI applications. However, the memory demands posed by the
self-attention mechanism and the large feedforward network in Transformers
limit their ability to handl... | 2023-05-30T19:25:51Z | null | null | null | Blockwise Parallel Transformer for Large Context Models | ['Hao Liu', 'P. Abbeel'] | 2,023 | null | 11 | 61 | ['Computer Science'] |
2,305.19435 | AdANNS: A Framework for Adaptive Semantic Search | ['Aniket Rege', 'Aditya Kusupati', 'Sharan Ranjit S', 'Alan Fan', 'Qingqing Cao', 'Sham Kakade', 'Prateek Jain', 'Ali Farhadi'] | ['cs.LG', 'cs.IR'] | Web-scale search systems learn an encoder to embed a given query which is
then hooked into an approximate nearest neighbor search (ANNS) pipeline to
retrieve similar data points. To accurately capture tail queries and data
points, learned representations typically are rigid, high-dimensional vectors
that are generally ... | 2023-05-30T22:05:47Z | 25 pages, 15 figures. NeurIPS 2023 camera ready publication | null | null | AdANNS: A Framework for Adaptive Semantic Search | ['Aniket Rege', 'Aditya Kusupati', 'S. SharanRanjit', 'Alan Fan', 'Qingqing Cao', 'S. Kakade', 'Prateek Jain', 'Ali Farhadi'] | 2,023 | Neural Information Processing Systems | 6 | 56 | ['Computer Science'] |
2,305.19466 | The Impact of Positional Encoding on Length Generalization in
Transformers | ['Amirhossein Kazemnejad', 'Inkit Padhi', 'Karthikeyan Natesan Ramamurthy', 'Payel Das', 'Siva Reddy'] | ['cs.CL', 'cs.AI', 'cs.LG'] | Length generalization, the ability to generalize from small training context
sizes to larger ones, is a critical challenge in the development of
Transformer-based language models. Positional encoding (PE) has been identified
as a major factor influencing length generalization, but the exact impact of
different PE schem... | 2023-05-31T00:29:55Z | Accepted at NeurIPS 2023; 15 pages and 22 pages Appendix | null | null | The Impact of Positional Encoding on Length Generalization in Transformers | ['Amirhossein Kazemnejad', 'Inkit Padhi', 'K. Ramamurthy', 'Payel Das', 'Siva Reddy'] | 2,023 | Neural Information Processing Systems | 209 | 62 | ['Computer Science'] |
2,305.19689 | Assessing Word Importance Using Models Trained for Semantic Tasks | ['Dávid Javorský', 'Ondřej Bojar', 'François Yvon'] | ['cs.CL'] | Many NLP tasks require to automatically identify the most significant words
in a text. In this work, we derive word significance from models trained to
solve semantic task: Natural Language Inference and Paraphrase Identification.
Using an attribution method aimed to explain the predictions of these models,
we derive i... | 2023-05-31T09:34:26Z | Published in the Findings of ACL 2023 | null | null | null | null | null | null | null | null | null |
2,305.1984 | BEIR-PL: Zero Shot Information Retrieval Benchmark for the Polish
Language | ['Konrad Wojtasik', 'Vadim Shishkin', 'Kacper Wołowiec', 'Arkadiusz Janz', 'Maciej Piasecki'] | ['cs.IR', 'cs.AI', 'cs.CL'] | The BEIR dataset is a large, heterogeneous benchmark for Information
Retrieval (IR) in zero-shot settings, garnering considerable attention within
the research community. However, BEIR and analogous datasets are predominantly
restricted to the English language. Our objective is to establish extensive
large-scale resour... | 2023-05-31T13:29:07Z | null | null | null | BEIR-PL: Zero Shot Information Retrieval Benchmark for the Polish Language | ['Konrad Wojtasik', 'Vadim Shishkin', 'Kacper Wolowiec', 'Arkadiusz Janz', 'Maciej Piasecki'] | 2,023 | International Conference on Language Resources and Evaluation | 11 | 52 | ['Computer Science'] |
2,305.19974 | Correcting Semantic Parses with Natural Language through Dynamic Schema
Encoding | ['Parker Glenn', 'Parag Pravin Dakle', 'Preethi Raghavan'] | ['cs.CL'] | In addressing the task of converting natural language to SQL queries, there
are several semantic and syntactic challenges. It becomes increasingly
important to understand and remedy the points of failure as the performance of
semantic parsing systems improve. We explore semantic parse correction with
natural language f... | 2023-05-31T16:01:57Z | ACL 2023 Workshop on NLP for Conversational AI | null | null | Correcting Semantic Parses with Natural Language through Dynamic Schema Encoding | ['Parker Glenn', 'Parag Dakle', 'Preethi Raghavan'] | 2,023 | NLP4CONVAI | 3 | 33 | ['Computer Science'] |
2,305.2005 | Let's Verify Step by Step | ['Hunter Lightman', 'Vineet Kosaraju', 'Yura Burda', 'Harri Edwards', 'Bowen Baker', 'Teddy Lee', 'Jan Leike', 'John Schulman', 'Ilya Sutskever', 'Karl Cobbe'] | ['cs.LG', 'cs.AI', 'cs.CL'] | In recent years, large language models have greatly improved in their ability
to perform complex multi-step reasoning. However, even state-of-the-art models
still regularly produce logical mistakes. To train more reliable models, we can
turn either to outcome supervision, which provides feedback for a final result,
or ... | 2023-05-31T17:24:00Z | null | null | null | Let's Verify Step by Step | ['Hunter Lightman', 'Vineet Kosaraju', 'Yura Burda', 'Harrison Edwards', 'Bowen Baker', 'Teddy Lee', 'Jan Leike', 'John Schulman', 'I. Sutskever', 'K. Cobbe'] | 2,023 | International Conference on Learning Representations | 1,241 | 33 | ['Computer Science'] |
2,306.00103 | ManagerTower: Aggregating the Insights of Uni-Modal Experts for
Vision-Language Representation Learning | ['Xiao Xu', 'Bei Li', 'Chenfei Wu', 'Shao-Yen Tseng', 'Anahita Bhiwandiwalla', 'Shachar Rosenman', 'Vasudev Lal', 'Wanxiang Che', 'Nan Duan'] | ['cs.CV', 'cs.CL', 'cs.LG'] | Two-Tower Vision-Language (VL) models have shown promising improvements on
various downstream VL tasks. Although the most advanced work improves
performance by building bridges between encoders, it suffers from ineffective
layer-by-layer utilization of uni-modal representations and cannot flexibly
exploit different lev... | 2023-05-31T18:23:57Z | Accepted by ACL 2023 Main Conference, Oral | null | null | null | null | null | null | null | null | null |
2,306.00107 | MERT: Acoustic Music Understanding Model with Large-Scale
Self-supervised Training | ['Yizhi Li', 'Ruibin Yuan', 'Ge Zhang', 'Yinghao Ma', 'Xingran Chen', 'Hanzhi Yin', 'Chenghao Xiao', 'Chenghua Lin', 'Anton Ragni', 'Emmanouil Benetos', 'Norbert Gyenge', 'Roger Dannenberg', 'Ruibo Liu', 'Wenhu Chen', 'Gus Xia', 'Yemin Shi', 'Wenhao Huang', 'Zili Wang', 'Yike Guo', 'Jie Fu'] | ['cs.SD', 'cs.AI', 'cs.CL', 'cs.LG', 'eess.AS'] | Self-supervised learning (SSL) has recently emerged as a promising paradigm
for training generalisable models on large-scale data in the fields of vision,
text, and speech. Although SSL has been proven effective in speech and audio,
its application to music audio has yet to be thoroughly explored. This is
partially due... | 2023-05-31T18:27:43Z | accepted by ICLR 2024 | null | null | MERT: Acoustic Music Understanding Model with Large-Scale Self-supervised Training | ['Yizhi Li', 'Ruibin Yuan', 'Ge Zhang', 'Yi Ma', 'Xingran Chen', 'Hanzhi Yin', 'Chen-Li Lin', 'A. Ragni', 'Emmanouil Benetos', 'N. Gyenge', 'R. Dannenberg', 'Ruibo Liu', 'Wenhu Chen', 'Gus G. Xia', 'Yemin Shi', 'Wen-Fen Huang', 'Yi-Ting Guo', 'Jie Fu'] | 2,023 | International Conference on Learning Representations | 130 | 64 | ['Computer Science', 'Engineering'] |
2,306.0011 | MuseCoco: Generating Symbolic Music from Text | ['Peiling Lu', 'Xin Xu', 'Chenfei Kang', 'Botao Yu', 'Chengyi Xing', 'Xu Tan', 'Jiang Bian'] | ['cs.SD', 'cs.AI', 'cs.CL', 'cs.LG', 'cs.MM', 'eess.AS'] | Generating music from text descriptions is a user-friendly mode since the
text is a relatively easy interface for user engagement. While some approaches
utilize texts to control music audio generation, editing musical elements in
generated audio is challenging for users. In contrast, symbolic music offers
ease of editi... | 2023-05-31T18:34:16Z | null | null | null | null | null | null | null | null | null | null |
2,306.00121 | Multilingual Multi-Figurative Language Detection | ['Huiyuan Lai', 'Antonio Toral', 'Malvina Nissim'] | ['cs.CL'] | Figures of speech help people express abstract concepts and evoke stronger
emotions than literal expressions, thereby making texts more creative and
engaging. Due to its pervasive and fundamental character, figurative language
understanding has been addressed in Natural Language Processing, but it's
highly understudied... | 2023-05-31T18:52:41Z | Accepted to ACL 2023 (Findings) | null | null | Multilingual Multi-Figurative Language Detection | ['Huiyuan Lai', 'Antonio Toral', 'M. Nissim'] | 2,023 | Annual Meeting of the Association for Computational Linguistics | 1 | 50 | ['Computer Science'] |
2,306.00124 | Pre-Trained Language-Meaning Models for Multilingual Parsing and
Generation | ['Chunliu Wang', 'Huiyuan Lai', 'Malvina Nissim', 'Johan Bos'] | ['cs.CL'] | Pre-trained language models (PLMs) have achieved great success in NLP and
have recently been used for tasks in computational semantics. However, these
tasks do not fully benefit from PLMs since meaning representations are not
explicitly included in the pre-training stage. We introduce multilingual
pre-trained language-... | 2023-05-31T19:00:33Z | Accepted by ACL2023 findings | null | null | Pre-Trained Language-Meaning Models for Multilingual Parsing and Generation | ['Chunliu Wang', 'Huiyuan Lai', 'M. Nissim', 'Johan Bos'] | 2,023 | Annual Meeting of the Association for Computational Linguistics | 13 | 55 | ['Computer Science'] |
2,306.00437 | Responsibility Perspective Transfer for Italian Femicide News | ['Gosse Minnema', 'Huiyuan Lai', 'Benedetta Muscato', 'Malvina Nissim'] | ['cs.CL'] | Different ways of linguistically expressing the same real-world event can
lead to different perceptions of what happened. Previous work has shown that
different descriptions of gender-based violence (GBV) influence the reader's
perception of who is to blame for the violence, possibly reinforcing
stereotypes which see t... | 2023-06-01T08:27:00Z | Accepted for publication in Findings of ACL 2023 | null | null | Responsibility Perspective Transfer for Italian Femicide News | ['Gosse Minnema', 'Huiyuan Lai', 'Benedetta Muscato', 'M. Nissim'] | 2,023 | Annual Meeting of the Association for Computational Linguistics | 3 | 29 | ['Computer Science'] |
2,306.00637 | Wuerstchen: An Efficient Architecture for Large-Scale Text-to-Image
Diffusion Models | ['Pablo Pernias', 'Dominic Rampas', 'Mats L. Richter', 'Christopher J. Pal', 'Marc Aubreville'] | ['cs.CV'] | We introduce W\"urstchen, a novel architecture for text-to-image synthesis
that combines competitive performance with unprecedented cost-effectiveness for
large-scale text-to-image diffusion models. A key contribution of our work is
to develop a latent diffusion technique in which we learn a detailed but
extremely comp... | 2023-06-01T13:00:53Z | Corresponding to "W\"urstchen v2" | The Twelfth International Conference on Learning Representations
(ICLR), 2024 | null | null | null | null | null | null | null | null |
2,306.00745 | Column Type Annotation using ChatGPT | ['Keti Korini', 'Christian Bizer'] | ['cs.CL'] | Column type annotation is the task of annotating the columns of a relational
table with the semantic type of the values contained in each column. Column
type annotation is an important pre-processing step for data search and data
integration in the context of data lakes. State-of-the-art column type
annotation methods ... | 2023-06-01T14:40:52Z | null | null | null | Column Type Annotation using ChatGPT | ['Keti Korini', 'Christian Bizer'] | 2,023 | VLDB Workshops | 28 | 37 | ['Computer Science'] |
2,306.00814 | Vocos: Closing the gap between time-domain and Fourier-based neural
vocoders for high-quality audio synthesis | ['Hubert Siuzdak'] | ['cs.SD', 'cs.LG', 'eess.AS'] | Recent advancements in neural vocoding are predominantly driven by Generative
Adversarial Networks (GANs) operating in the time-domain. While effective, this
approach neglects the inductive bias offered by time-frequency representations,
resulting in reduntant and computionally-intensive upsampling operations.
Fourier-... | 2023-06-01T15:40:32Z | null | null | null | null | null | null | null | null | null | null |
2,306.0089 | LLaVA-Med: Training a Large Language-and-Vision Assistant for
Biomedicine in One Day | ['Chunyuan Li', 'Cliff Wong', 'Sheng Zhang', 'Naoto Usuyama', 'Haotian Liu', 'Jianwei Yang', 'Tristan Naumann', 'Hoifung Poon', 'Jianfeng Gao'] | ['cs.CV', 'cs.CL'] | Conversational generative AI has demonstrated remarkable promise for
empowering biomedical practitioners, but current investigations focus on
unimodal text. Multimodal conversational AI has seen rapid progress by
leveraging billions of image-text pairs from the public web, but such
general-domain vision-language models... | 2023-06-01T16:50:07Z | 17 pages; Website: https://aka.ms/llava-med | null | null | null | null | null | null | null | null | null |
2,306.00917 | Vocabulary-free Image Classification | ['Alessandro Conti', 'Enrico Fini', 'Massimiliano Mancini', 'Paolo Rota', 'Yiming Wang', 'Elisa Ricci'] | ['cs.CV'] | Recent advances in large vision-language models have revolutionized the image
classification paradigm. Despite showing impressive zero-shot capabilities, a
pre-defined set of categories, a.k.a. the vocabulary, is assumed at test time
for composing the textual prompts. However, such assumption can be impractical
when th... | 2023-06-01T17:19:43Z | Accepted at NeurIPS2023, 19 pages, 8 figures, code is available at
https://github.com/altndrr/vic | null | null | null | null | null | null | null | null | null |
2,306.00926 | Inserting Anybody in Diffusion Models via Celeb Basis | ['Ge Yuan', 'Xiaodong Cun', 'Yong Zhang', 'Maomao Li', 'Chenyang Qi', 'Xintao Wang', 'Ying Shan', 'Huicheng Zheng'] | ['cs.CV'] | Exquisite demand exists for customizing the pretrained large text-to-image
model, $\textit{e.g.}$, Stable Diffusion, to generate innovative concepts, such
as the users themselves. However, the newly-added concept from previous
customization methods often shows weaker combination abilities than the
original ones even gi... | 2023-06-01T17:30:24Z | Project page: http://celeb-basis.github.io ; Github repository:
https://github.com/ygtxr1997/CelebBasis | null | null | null | null | null | null | null | null | null |
2,306.00958 | LIV: Language-Image Representations and Rewards for Robotic Control | ['Yecheng Jason Ma', 'William Liang', 'Vaidehi Som', 'Vikash Kumar', 'Amy Zhang', 'Osbert Bastani', 'Dinesh Jayaraman'] | ['cs.RO', 'cs.AI', 'cs.LG'] | We present Language-Image Value learning (LIV), a unified objective for
vision-language representation and reward learning from action-free videos with
text annotations. Exploiting a novel connection between dual reinforcement
learning and mutual information contrastive learning, the LIV objective trains
a multi-modal ... | 2023-06-01T17:52:23Z | Extended version of ICML 2023 camera-ready; Project website:
https://penn-pal-lab.github.io/LIV/ | null | null | LIV: Language-Image Representations and Rewards for Robotic Control | ['Yecheng Jason Ma', 'William Liang', 'Vaidehi Som', 'Vikash Kumar', 'Amy Zhang', 'Osbert Bastani', 'Dinesh Jayaraman'] | 2,023 | International Conference on Machine Learning | 130 | 69 | ['Computer Science'] |
2,306.00973 | Intelligent Grimm -- Open-ended Visual Storytelling via Latent Diffusion
Models | ['Chang Liu', 'Haoning Wu', 'Yujie Zhong', 'Xiaoyun Zhang', 'Yanfeng Wang', 'Weidi Xie'] | ['cs.CV'] | Generative models have recently exhibited exceptional capabilities in
text-to-image generation, but still struggle to generate image sequences
coherently. In this work, we focus on a novel, yet challenging task of
generating a coherent image sequence based on a given storyline, denoted as
open-ended visual storytelling... | 2023-06-01T17:58:50Z | Accepted by CVPR 2024. Project Page:
https://haoningwu3639.github.io/StoryGen_Webpage/ | null | null | Intelligent Grimm - Open-ended Visual Storytelling via Latent Diffusion Models | ['Chang Liu', 'Haoning Wu', 'Yujie Zhong', 'Xiaoyu Zhang', 'Weidi Xie'] | 2,023 | Computer Vision and Pattern Recognition | 44 | 72 | ['Computer Science'] |
2,306.00978 | AWQ: Activation-aware Weight Quantization for LLM Compression and
Acceleration | ['Ji Lin', 'Jiaming Tang', 'Haotian Tang', 'Shang Yang', 'Wei-Ming Chen', 'Wei-Chen Wang', 'Guangxuan Xiao', 'Xingyu Dang', 'Chuang Gan', 'Song Han'] | ['cs.CL'] | Large language models (LLMs) have transformed numerous AI applications.
On-device LLM is becoming increasingly important: running LLMs locally on edge
devices can reduce the cloud computing cost and protect users' privacy.
However, the astronomical model size and the limited hardware resource pose
significant deploymen... | 2023-06-01T17:59:10Z | MLSys 2024 Best Paper Award. Code available at:
https://github.com/mit-han-lab/llm-awq | null | null | null | null | null | null | null | null | null |
2,306.00983 | StyleDrop: Text-to-Image Generation in Any Style | ['Kihyuk Sohn', 'Nataniel Ruiz', 'Kimin Lee', 'Daniel Castro Chin', 'Irina Blok', 'Huiwen Chang', 'Jarred Barber', 'Lu Jiang', 'Glenn Entis', 'Yuanzhen Li', 'Yuan Hao', 'Irfan Essa', 'Michael Rubinstein', 'Dilip Krishnan'] | ['cs.CV', 'cs.AI'] | Pre-trained large text-to-image models synthesize impressive images with an
appropriate use of text prompts. However, ambiguities inherent in natural
language and out-of-distribution effects make it hard to synthesize image
styles, that leverage a specific design pattern, texture or material. In this
paper, we introduc... | 2023-06-01T17:59:51Z | Preprint. Project page at https://styledrop.github.io | null | null | null | null | null | null | null | null | null |
2,306.00989 | Hiera: A Hierarchical Vision Transformer without the Bells-and-Whistles | ['Chaitanya Ryali', 'Yuan-Ting Hu', 'Daniel Bolya', 'Chen Wei', 'Haoqi Fan', 'Po-Yao Huang', 'Vaibhav Aggarwal', 'Arkabandhu Chowdhury', 'Omid Poursaeed', 'Judy Hoffman', 'Jitendra Malik', 'Yanghao Li', 'Christoph Feichtenhofer'] | ['cs.CV', 'cs.LG'] | Modern hierarchical vision transformers have added several vision-specific
components in the pursuit of supervised classification performance. While these
components lead to effective accuracies and attractive FLOP counts, the added
complexity actually makes these transformers slower than their vanilla ViT
counterparts... | 2023-06-01T17:59:58Z | ICML 2023 Oral version. Code+Models:
https://github.com/facebookresearch/hiera | null | null | null | null | null | null | null | null | null |
2,306.01116 | The RefinedWeb Dataset for Falcon LLM: Outperforming Curated Corpora
with Web Data, and Web Data Only | ['Guilherme Penedo', 'Quentin Malartic', 'Daniel Hesslow', 'Ruxandra Cojocaru', 'Alessandro Cappelli', 'Hamza Alobeidli', 'Baptiste Pannier', 'Ebtesam Almazrouei', 'Julien Launay'] | ['cs.CL', 'cs.AI'] | Large language models are commonly trained on a mixture of filtered web data
and curated high-quality corpora, such as social media conversations, books, or
technical papers. This curation process is believed to be necessary to produce
performant models with broad zero-shot generalization abilities. However, as
larger ... | 2023-06-01T20:03:56Z | null | null | null | null | null | null | null | null | null | null |
2,306.01533 | Enhance Temporal Relations in Audio Captioning with Sound Event
Detection | ['Zeyu Xie', 'Xuenan Xu', 'Mengyue Wu', 'Kai Yu'] | ['cs.SD', 'eess.AS'] | Automated audio captioning aims at generating natural language descriptions
for given audio clips, not only detecting and classifying sounds, but also
summarizing the relationships between audio events. Recent research advances in
audio captioning have introduced additional guidance to improve the accuracy of
audio eve... | 2023-06-02T13:36:34Z | Interspeech 2023 | null | 10.21437/Interspeech.2023-1614 | null | null | null | null | null | null | null |
2,306.01545 | PassGPT: Password Modeling and (Guided) Generation with Large Language
Models | ['Javier Rando', 'Fernando Perez-Cruz', 'Briland Hitaj'] | ['cs.CL', 'cs.AI', 'cs.CR'] | Large language models (LLMs) successfully model natural language from vast
amounts of text without the need for explicit supervision. In this paper, we
investigate the efficacy of LLMs in modeling passwords. We present PassGPT, a
LLM trained on password leaks for password generation. PassGPT outperforms
existing method... | 2023-06-02T13:49:53Z | null | null | null | PassGPT: Password Modeling and (Guided) Generation with Large Language Models | ['Javier Rando', 'F. Pérez-Cruz', 'B. Hitaj'] | 2,023 | European Symposium on Research in Computer Security | 10 | 53 | ['Computer Science'] |
2,306.01567 | Segment Anything in High Quality | ['Lei Ke', 'Mingqiao Ye', 'Martin Danelljan', 'Yifan Liu', 'Yu-Wing Tai', 'Chi-Keung Tang', 'Fisher Yu'] | ['cs.CV'] | The recent Segment Anything Model (SAM) represents a big leap in scaling up
segmentation models, allowing for powerful zero-shot capabilities and flexible
prompting. Despite being trained with 1.1 billion masks, SAM's mask prediction
quality falls short in many cases, particularly when dealing with objects that
have in... | 2023-06-02T14:23:59Z | NeurIPS 2023. We propose HQ-SAM to upgrade SAM for high-quality
zero-shot segmentation. Github: https://github.com/SysCV/SAM-HQ | null | null | Segment Anything in High Quality | ['Lei Ke', 'Mingqiao Ye', 'Martin Danelljan', 'Yifan Liu', 'Yu-Wing Tai', 'Chi-Keung Tang', 'F. Yu'] | 2,023 | Neural Information Processing Systems | 341 | 59 | ['Computer Science'] |
2,306.01708 | TIES-Merging: Resolving Interference When Merging Models | ['Prateek Yadav', 'Derek Tam', 'Leshem Choshen', 'Colin Raffel', 'Mohit Bansal'] | ['cs.LG', 'cs.AI', 'cs.CL', 'cs.CV'] | Transfer learning - i.e., further fine-tuning a pre-trained model on a
downstream task - can confer significant advantages, including improved
downstream performance, faster convergence, and better sample efficiency. These
advantages have led to a proliferation of task-specific fine-tuned models,
which typically can on... | 2023-06-02T17:31:32Z | Published at NeurIPS 2023, 23 Pages, 13 Figures, 14 Tables | null | null | TIES-Merging: Resolving Interference When Merging Models | ['Prateek Yadav', 'Derek Tam', 'Leshem Choshen', 'Colin Raffel', 'Mohit Bansal'] | 2,023 | Neural Information Processing Systems | 319 | 90 | ['Computer Science'] |
2,306.02018 | VideoComposer: Compositional Video Synthesis with Motion Controllability | ['Xiang Wang', 'Hangjie Yuan', 'Shiwei Zhang', 'Dayou Chen', 'Jiuniu Wang', 'Yingya Zhang', 'Yujun Shen', 'Deli Zhao', 'Jingren Zhou'] | ['cs.CV'] | The pursuit of controllability as a higher standard of visual content
creation has yielded remarkable progress in customizable image synthesis.
However, achieving controllable video synthesis remains challenging due to the
large variation of temporal dynamics and the requirement of cross-frame
temporal consistency. Bas... | 2023-06-03T06:29:02Z | The first four authors contributed equally. Project page:
https://videocomposer.github.io | null | null | null | null | null | null | null | null | null |
2,306.02069 | MultiLegalPile: A 689GB Multilingual Legal Corpus | ['Joel Niklaus', 'Veton Matoshi', 'Matthias Stürmer', 'Ilias Chalkidis', 'Daniel E. Ho'] | ['cs.CL', 'cs.AI', 'cs.LG', '68T50', 'I.2'] | Large, high-quality datasets are crucial for training Large Language Models
(LLMs). However, so far, there are few datasets available for specialized
critical domains such as law and the available ones are often only for the
English language. We curate and release MultiLegalPile, a 689GB corpus in 24
languages from 17 ... | 2023-06-03T10:10:38Z | Accepted to ACL 2024 | null | null | MultiLegalPile: A 689GB Multilingual Legal Corpus | ['Joel Niklaus', 'Veton Matoshi', 'Matthias Sturmer', 'Ilias Chalkidis', 'Daniel E. Ho'] | 2,023 | Annual Meeting of the Association for Computational Linguistics | 44 | 79 | ['Computer Science'] |
2,306.02231 | Fine-Tuning Language Models with Advantage-Induced Policy Alignment | ['Banghua Zhu', 'Hiteshi Sharma', 'Felipe Vieira Frujeri', 'Shi Dong', 'Chenguang Zhu', 'Michael I. Jordan', 'Jiantao Jiao'] | ['cs.CL', 'cs.AI', 'cs.LG', 'cs.SY', 'eess.SY'] | Reinforcement learning from human feedback (RLHF) has emerged as a reliable
approach to aligning large language models (LLMs) to human preferences. Among
the plethora of RLHF techniques, proximal policy optimization (PPO) is of the
most widely used methods. Despite its popularity, however, PPO may suffer from
mode coll... | 2023-06-04T01:59:40Z | null | null | null | Fine-Tuning Language Models with Advantage-Induced Policy Alignment | ['Banghua Zhu', 'Hiteshi Sharma', 'F. Frujeri', 'Shi Dong', 'Chenguang Zhu', 'Michael I. Jordan', 'Jiantao Jiao'] | 2,023 | arXiv.org | 41 | 37 | ['Computer Science', 'Engineering'] |
2,306.02254 | A Technical Report for Polyglot-Ko: Open-Source Large-Scale Korean
Language Models | ['Hyunwoong Ko', 'Kichang Yang', 'Minho Ryu', 'Taekyoon Choi', 'Seungmu Yang', 'Jiwung Hyun', 'Sungho Park', 'Kyubyong Park'] | ['cs.CL'] | Polyglot is a pioneering project aimed at enhancing the non-English language
performance of multilingual language models. Despite the availability of
various multilingual models such as mBERT (Devlin et al., 2019), XGLM (Lin et
al., 2022), and BLOOM (Scao et al., 2022), researchers and developers often
resort to buildi... | 2023-06-04T04:04:04Z | null | null | null | A Technical Report for Polyglot-Ko: Open-Source Large-Scale Korean Language Models | ['H. Ko', 'Kichang Yang', 'Minho Ryu', 'Taekyoon Choi', 'Seungmu Yang', 'Jiwung Hyun', 'Sung-Yong Park', 'Kyubyong Park'] | 2,023 | arXiv.org | 30 | 18 | ['Computer Science'] |
2,306.02317 | SpellMapper: A non-autoregressive neural spellchecker for ASR
customization with candidate retrieval based on n-gram mappings | ['Alexandra Antonova', 'Evelina Bakhturina', 'Boris Ginsburg'] | ['cs.CL', 'cs.AI', 'cs.SD', 'eess.AS'] | Contextual spelling correction models are an alternative to shallow fusion to
improve automatic speech recognition (ASR) quality given user vocabulary. To
deal with large user vocabularies, most of these models include candidate
retrieval mechanisms, usually based on minimum edit distance between fragments
of ASR hypot... | 2023-06-04T10:00:12Z | Accepted by INTERSPEECH 2023 | null | null | SpellMapper: A non-autoregressive neural spellchecker for ASR customization with candidate retrieval based on n-gram mappings | ['Alexandra Antonova', 'E. Bakhturina', 'Boris Ginsburg'] | 2,023 | Interspeech | 6 | 25 | ['Computer Science', 'Engineering'] |
2,306.02507 | Deep learning powered real-time identification of insects using citizen
science data | ['Shivani Chiranjeevi', 'Mojdeh Sadaati', 'Zi K Deng', 'Jayanth Koushik', 'Talukder Z Jubery', 'Daren Mueller', 'Matthew E O Neal', 'Nirav Merchant', 'Aarti Singh', 'Asheesh K Singh', 'Soumik Sarkar', 'Arti Singh', 'Baskar Ganapathysubramanian'] | ['cs.CV'] | Insect-pests significantly impact global agricultural productivity and
quality. Effective management involves identifying the full insect community,
including beneficial insects and harmful pests, to develop and implement
integrated pest management strategies. Automated identification of insects
under real-world condit... | 2023-06-04T23:56:53Z | null | null | null | Deep learning powered real-time identification of insects using citizen science data | ['Shivani Chiranjeevi', 'Mojdeh Sadaati', 'Ziqing Deng', 'Jayanth Koushik', 'T. Jubery', 'D. Mueller', 'Matthew E O Neal', 'Nirav C. Merchant', 'Aarti Singh', 'Ashutosh Kumar Singh', 'S. Sarkar', 'Arti Singh', 'B. Ganapathysubramanian'] | 2,023 | arXiv.org | 14 | 42 | ['Computer Science'] |
2,306.02561 | LLM-Blender: Ensembling Large Language Models with Pairwise Ranking and
Generative Fusion | ['Dongfu Jiang', 'Xiang Ren', 'Bill Yuchen Lin'] | ['cs.CL', 'cs.AI', 'cs.LG'] | We present LLM-Blender, an ensembling framework designed to attain
consistently superior performance by leveraging the diverse strengths of
multiple open-source large language models (LLMs). Our framework consists of
two modules: PairRanker and GenFuser, addressing the observation that optimal
LLMs for different exampl... | 2023-06-05T03:32:26Z | Accepted to ACL 2023 (main conference); Project website:
https://yuchenlin.xyz/LLM-Blender/ V3 update: fix a few typos and update a
few citations; V2 update: The experiments on summarization, translation, and
constrained generation tasks in the prior version have been moved to the
appendix | null | null | LLM-Blender: Ensembling Large Language Models with Pairwise Ranking and Generative Fusion | ['Dongfu Jiang', 'Xiang Ren', 'Bill Yuchen Lin'] | 2,023 | Annual Meeting of the Association for Computational Linguistics | 334 | 53 | ['Computer Science'] |
2,306.02707 | Orca: Progressive Learning from Complex Explanation Traces of GPT-4 | ['Subhabrata Mukherjee', 'Arindam Mitra', 'Ganesh Jawahar', 'Sahaj Agarwal', 'Hamid Palangi', 'Ahmed Awadallah'] | ['cs.CL', 'cs.LG'] | Recent research has focused on enhancing the capability of smaller models
through imitation learning, drawing on the outputs generated by large
foundation models (LFMs). A number of issues impact the quality of these
models, ranging from limited imitation signals from shallow LFM outputs; small
scale homogeneous traini... | 2023-06-05T08:58:39Z | null | null | null | null | null | null | null | null | null | null |
2,306.02771 | Identifying the style by a qualified reader on a short fragment of
generated poetry | ['Boris Orekhov'] | ['cs.CL', 'cs.AI', 'cs.LG'] | Style is an important concept in today's challenges in natural language
generating. After the success in the field of image style transfer, the task of
text style transfer became actual and attractive. Researchers are also
interested in the tasks of style reproducing in generation of the poetic text.
Evaluation of styl... | 2023-06-05T10:55:15Z | 6 pages, 2 tables | null | null | null | null | null | null | null | null | null |
2,306.02796 | MCTS: A Multi-Reference Chinese Text Simplification Dataset | ['Ruining Chong', 'Luming Lu', 'Liner Yang', 'Jinran Nie', 'Zhenghao Liu', 'Shuo Wang', 'Shuhan Zhou', 'Yaoxin Li', 'Erhong Yang'] | ['cs.CL'] | Text simplification aims to make the text easier to understand by applying
rewriting transformations. There has been very little research on Chinese text
simplification for a long time. The lack of generic evaluation data is an
essential reason for this phenomenon. In this paper, we introduce MCTS, a
multi-reference Ch... | 2023-06-05T11:46:36Z | Accepted to COLING 2024 | null | null | MCTS: A Multi-Reference Chinese Text Simplification Dataset | ['Ruining Chong', 'Luming Lu', 'Liner Yang', 'Jinran Nie', 'Shuhan Zhou', 'Yaoxin Li', 'Erhong Yang'] | 2,023 | International Conference on Language Resources and Evaluation | 1 | 42 | ['Computer Science'] |
2,306.02858 | Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video
Understanding | ['Hang Zhang', 'Xin Li', 'Lidong Bing'] | ['cs.CL', 'cs.CV', 'cs.SD', 'eess.AS'] | We present Video-LLaMA a multi-modal framework that empowers Large Language
Models (LLMs) with the capability of understanding both visual and auditory
content in the video. Video-LLaMA bootstraps cross-modal training from the
frozen pre-trained visual and audio encoders and the frozen LLMs. Unlike
previous works that ... | 2023-06-05T13:17:27Z | Accepted by EMNLP 2023's demo track; Code, Pretrained Model, and
Dataset: https://github.com/DAMO-NLP-SG/Video-LLaMA | null | null | Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding | ['Hang Zhang', 'Xin Li', 'Lidong Bing'] | 2,023 | Conference on Empirical Methods in Natural Language Processing | 1,068 | 42 | ['Computer Science', 'Engineering'] |
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