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2,401.1428 | RomanSetu: Efficiently unlocking multilingual capabilities of Large
Language Models via Romanization | ['Jaavid Aktar Husain', 'Raj Dabre', 'Aswanth Kumar', 'Jay Gala', 'Thanmay Jayakumar', 'Ratish Puduppully', 'Anoop Kunchukuttan'] | ['cs.CL', 'cs.AI'] | This study addresses the challenge of extending Large Language Models (LLMs)
to non-English languages that use non-Roman scripts. We propose an approach
that utilizes the romanized form of text as an interface for LLMs,
hypothesizing that its frequent informal use and shared tokens with English
enhance cross-lingual al... | 2024-01-25T16:11:41Z | Accepted to ACL 2024 | null | null | null | null | null | null | null | null | null |
2,401.14373 | TURNA: A Turkish Encoder-Decoder Language Model for Enhanced
Understanding and Generation | ['Gökçe Uludoğan', 'Zeynep Yirmibeşoğlu Balal', 'Furkan Akkurt', 'Melikşah Türker', 'Onur Güngör', 'Susan Üsküdarlı'] | ['cs.CL', 'cs.AI', 'cs.LG'] | The recent advances in natural language processing have predominantly favored
well-resourced English-centric models, resulting in a significant gap with
low-resource languages. In this work, we introduce the language model TURNA,
which is developed for the low-resource language Turkish and is capable of both
natural la... | 2024-01-25T18:24:13Z | null | null | null | TURNA: A Turkish Encoder-Decoder Language Model for Enhanced Understanding and Generation | ['Gokcce Uludougan', 'Zeynep Yirmibecsouglu Balal', 'Furkan Akkurt', 'Melikcsah Turker', 'Onur Gungor', 'S. Uskudarli'] | 2,024 | Annual Meeting of the Association for Computational Linguistics | 12 | 66 | ['Computer Science'] |
2,401.14391 | Rethinking Patch Dependence for Masked Autoencoders | ['Letian Fu', 'Long Lian', 'Renhao Wang', 'Baifeng Shi', 'Xudong Wang', 'Adam Yala', 'Trevor Darrell', 'Alexei A. Efros', 'Ken Goldberg'] | ['cs.CV'] | In this work, we examine the impact of inter-patch dependencies in the
decoder of masked autoencoders (MAE) on representation learning. We decompose
the decoding mechanism for masked reconstruction into self-attention between
mask tokens and cross-attention between masked and visible tokens. Our findings
reveal that MA... | 2024-01-25T18:49:57Z | Transactions on Machine Learning Research (TMLR) 2025 | null | null | null | null | null | null | null | null | null |
2,401.14398 | pix2gestalt: Amodal Segmentation by Synthesizing Wholes | ['Ege Ozguroglu', 'Ruoshi Liu', 'Dídac Surís', 'Dian Chen', 'Achal Dave', 'Pavel Tokmakov', 'Carl Vondrick'] | ['cs.CV', 'cs.LG'] | We introduce pix2gestalt, a framework for zero-shot amodal segmentation,
which learns to estimate the shape and appearance of whole objects that are
only partially visible behind occlusions. By capitalizing on large-scale
diffusion models and transferring their representations to this task, we learn
a conditional diffu... | 2024-01-25T18:57:36Z | Website: https://gestalt.cs.columbia.edu/ | null | null | null | null | null | null | null | null | null |
2,401.144 | Modular Adaptation of Multilingual Encoders to Written Swiss German
Dialect | ['Jannis Vamvas', 'Noëmi Aepli', 'Rico Sennrich'] | ['cs.CL'] | Creating neural text encoders for written Swiss German is challenging due to
a dearth of training data combined with dialectal variation. In this paper, we
build on several existing multilingual encoders and adapt them to Swiss German
using continued pre-training. Evaluation on three diverse downstream tasks
shows that... | 2024-01-25T18:59:32Z | First Workshop on Modular and Open Multilingual NLP (MOOMIN 2024) | null | null | Modular Adaptation of Multilingual Encoders to Written Swiss German Dialect | ['Jannis Vamvas', 'Noëmi Aepli', 'Rico Sennrich'] | 2,024 | MOOMIN | 0 | 23 | ['Computer Science'] |
2,401.14489 | The Case for Co-Designing Model Architectures with Hardware | ['Quentin Anthony', 'Jacob Hatef', 'Deepak Narayanan', 'Stella Biderman', 'Stas Bekman', 'Junqi Yin', 'Aamir Shafi', 'Hari Subramoni', 'Dhabaleswar Panda'] | ['cs.DC', 'cs.AI'] | While GPUs are responsible for training the vast majority of state-of-the-art
deep learning models, the implications of their architecture are often
overlooked when designing new deep learning (DL) models. As a consequence,
modifying a DL model to be more amenable to the target hardware can
significantly improve the ru... | 2024-01-25T19:50:31Z | null | null | null | null | null | null | null | null | null | null |
2,401.14688 | Taiyi-Diffusion-XL: Advancing Bilingual Text-to-Image Generation with
Large Vision-Language Model Support | ['Xiaojun Wu', 'Dixiang Zhang', 'Ruyi Gan', 'Junyu Lu', 'Ziwei Wu', 'Renliang Sun', 'Jiaxing Zhang', 'Pingjian Zhang', 'Yan Song'] | ['cs.CL'] | Recent advancements in text-to-image models have significantly enhanced image
generation capabilities, yet a notable gap of open-source models persists in
bilingual or Chinese language support. To address this need, we present
Taiyi-Diffusion-XL, a new Chinese and English bilingual text-to-image model
which is develope... | 2024-01-26T07:17:50Z | Taiyi-Diffusion-XL Tech Report | null | null | null | null | null | null | null | null | null |
2,401.14818 | Developing ChemDFM as a large language foundation model for chemistry | ['Zihan Zhao', 'Da Ma', 'Lu Chen', 'Liangtai Sun', 'Zihao Li', 'Yi Xia', 'Bo Chen', 'Hongshen Xu', 'Zichen Zhu', 'Su Zhu', 'Shuai Fan', 'Guodong Shen', 'Kai Yu', 'Xin Chen'] | ['cs.CL', 'cs.DL'] | Artificial intelligence (AI) has played an increasingly important role in
chemical research. However, most models currently used in chemistry are
specialist models that require training and tuning for specific tasks. A more
generic and efficient solution would be an AI model that could address many
tasks and support fr... | 2024-01-26T12:45:55Z | 10 pages, 12 figures, 12 tables. Published on Cell Report Physical
Science, DOI: https://doi.org/10.1016/j.xcrp.2025.102523 | Cell Rep. Phys. Sci. 6 (2025) 102523 | 10.1016/j.xcrp.2025.102523 | null | null | null | null | null | null | null |
2,401.15006 | Airavata: Introducing Hindi Instruction-tuned LLM | ['Jay Gala', 'Thanmay Jayakumar', 'Jaavid Aktar Husain', 'Aswanth Kumar M', 'Mohammed Safi Ur Rahman Khan', 'Diptesh Kanojia', 'Ratish Puduppully', 'Mitesh M. Khapra', 'Raj Dabre', 'Rudra Murthy', 'Anoop Kunchukuttan'] | ['cs.CL', 'cs.AI'] | We announce the initial release of "Airavata," an instruction-tuned LLM for
Hindi. Airavata was created by fine-tuning OpenHathi with diverse,
instruction-tuning Hindi datasets to make it better suited for assistive tasks.
Along with the model, we also share the IndicInstruct dataset, which is a
collection of diverse i... | 2024-01-26T17:07:08Z | Work in progress | null | null | null | null | null | null | null | null | null |
2,401.15391 | MultiHop-RAG: Benchmarking Retrieval-Augmented Generation for Multi-Hop
Queries | ['Yixuan Tang', 'Yi Yang'] | ['cs.CL'] | Retrieval-augmented generation (RAG) augments large language models (LLM) by
retrieving relevant knowledge, showing promising potential in mitigating LLM
hallucinations and enhancing response quality, thereby facilitating the great
adoption of LLMs in practice. However, we find that existing RAG systems are
inadequate ... | 2024-01-27T11:41:48Z | Link: https://github.com/yixuantt/MultiHop-RAG/ | null | null | null | null | null | null | null | null | null |
2,401.15896 | M2-Encoder: Advancing Bilingual Image-Text Understanding by Large-scale
Efficient Pretraining | ['Qingpei Guo', 'Furong Xu', 'Hanxiao Zhang', 'Wang Ren', 'Ziping Ma', 'Lin Ju', 'Jian Wang', 'Jingdong Chen', 'Ming Yang'] | ['cs.CV', 'cs.AI'] | Vision-language foundation models like CLIP have revolutionized the field of
artificial intelligence. Nevertheless, VLM models supporting multi-language,
e.g., in both Chinese and English, have lagged due to the relative scarcity of
large-scale pretraining datasets. Toward this end, we introduce a comprehensive
bilingu... | 2024-01-29T05:43:33Z | null | null | null | null | null | null | null | null | null | null |
2,401.15947 | MoE-LLaVA: Mixture of Experts for Large Vision-Language Models | ['Bin Lin', 'Zhenyu Tang', 'Yang Ye', 'Jinfa Huang', 'Junwu Zhang', 'Yatian Pang', 'Peng Jin', 'Munan Ning', 'Jiebo Luo', 'Li Yuan'] | ['cs.CV'] | Recent advances demonstrate that scaling Large Vision-Language Models (LVLMs)
effectively improves downstream task performances. However, existing scaling
methods enable all model parameters to be active for each token in the
calculation, which brings massive training and inferring costs. In this work,
we propose a sim... | 2024-01-29T08:13:40Z | update author | null | null | null | null | null | null | null | null | null |
2,401.16122 | DeFlow: Decoder of Scene Flow Network in Autonomous Driving | ['Qingwen Zhang', 'Yi Yang', 'Heng Fang', 'Ruoyu Geng', 'Patric Jensfelt'] | ['cs.CV', 'cs.RO'] | Scene flow estimation determines a scene's 3D motion field, by predicting the
motion of points in the scene, especially for aiding tasks in autonomous
driving. Many networks with large-scale point clouds as input use voxelization
to create a pseudo-image for real-time running. However, the voxelization
process often re... | 2024-01-29T12:47:55Z | 7 pages, 4 figures, Code check https://github.com/KTH-RPL/deflow,
accepted by ICRA 2024 | null | null | null | null | null | null | null | null | null |
2,401.16182 | LLaMandement: Large Language Models for Summarization of French
Legislative Proposals | ['Joseph Gesnouin', 'Yannis Tannier', 'Christophe Gomes Da Silva', 'Hatim Tapory', 'Camille Brier', 'Hugo Simon', 'Raphael Rozenberg', 'Hermann Woehrel', 'Mehdi El Yakaabi', 'Thomas Binder', 'Guillaume Marie', 'Emilie Caron', 'Mathile Nogueira', 'Thomas Fontas', 'Laure Puydebois', 'Marie Theophile', 'Stephane Morandi',... | ['cs.CL', 'cs.AI'] | This report introduces LLaMandement, a state-of-the-art Large Language Model,
fine-tuned by the French government and designed to enhance the efficiency and
efficacy of processing parliamentary sessions (including the production of
bench memoranda and documents required for interministerial meetings) by
generating neut... | 2024-01-29T14:23:51Z | 21 pages, 9 figures | null | null | LLaMandement: Large Language Models for Summarization of French Legislative Proposals | ['Joseph Gesnouin', 'Yannis Tannier', 'Christophe Gomes Da Silva', 'Hatim Tapory', 'Camille Brier', 'Hugo Simon', 'Raphael Rozenberg', 'Hermann Woehrel', 'Mehdi El Yakaabi', 'Thomas Binder', 'Guillaume Marie', 'Emilie Caron', 'Mathile Nogueira', 'Thomas Fontas', 'Laure Puydebois', 'Marie Theophile', 'Stephane Morandi',... | 2,024 | arXiv.org | 8 | 52 | ['Computer Science'] |
2,401.16224 | Diffutoon: High-Resolution Editable Toon Shading via Diffusion Models | ['Zhongjie Duan', 'Chengyu Wang', 'Cen Chen', 'Weining Qian', 'Jun Huang'] | ['cs.CV'] | Toon shading is a type of non-photorealistic rendering task of animation. Its
primary purpose is to render objects with a flat and stylized appearance. As
diffusion models have ascended to the forefront of image synthesis
methodologies, this paper delves into an innovative form of toon shading based
on diffusion models... | 2024-01-29T15:21:37Z | null | null | null | Diffutoon: High-Resolution Editable Toon Shading via Diffusion Models | ['Zhongjie Duan', 'Chengyu Wang', 'Cen Chen', 'Weining Qian', 'Jun Huang'] | 2,024 | International Joint Conference on Artificial Intelligence | 7 | 46 | ['Computer Science'] |
2,401.16265 | CO2: Efficient Distributed Training with Full Communication-Computation
Overlap | ['Weigao Sun', 'Zhen Qin', 'Weixuan Sun', 'Shidi Li', 'Dong Li', 'Xuyang Shen', 'Yu Qiao', 'Yiran Zhong'] | ['cs.CL', 'cs.DC'] | The fundamental success of large language models hinges upon the efficacious
implementation of large-scale distributed training techniques. Nevertheless,
building a vast, high-performance cluster featuring high-speed communication
interconnectivity is prohibitively costly, and accessible only to prominent
entities. In ... | 2024-01-29T16:12:31Z | ICLR 2024 Spotlight. Yiran Zhong is the corresponding author. Code is
available at: https://github.com/OpenNLPLab/CO2 | null | null | null | null | null | null | null | null | null |
2,401.1642 | InternLM-XComposer2: Mastering Free-form Text-Image Composition and
Comprehension in Vision-Language Large Model | ['Xiaoyi Dong', 'Pan Zhang', 'Yuhang Zang', 'Yuhang Cao', 'Bin Wang', 'Linke Ouyang', 'Xilin Wei', 'Songyang Zhang', 'Haodong Duan', 'Maosong Cao', 'Wenwei Zhang', 'Yining Li', 'Hang Yan', 'Yang Gao', 'Xinyue Zhang', 'Wei Li', 'Jingwen Li', 'Kai Chen', 'Conghui He', 'Xingcheng Zhang', 'Yu Qiao', 'Dahua Lin', 'Jiaqi Wan... | ['cs.CV', 'cs.CL'] | We introduce InternLM-XComposer2, a cutting-edge vision-language model
excelling in free-form text-image composition and comprehension. This model
goes beyond conventional vision-language understanding, adeptly crafting
interleaved text-image content from diverse inputs like outlines, detailed
textual specifications, a... | 2024-01-29T18:59:02Z | Code and models are available at
https://github.com/InternLM/InternLM-XComposer | null | null | InternLM-XComposer2: Mastering Free-form Text-Image Composition and Comprehension in Vision-Language Large Model | ['Xiao-wen Dong', 'Pan Zhang', 'Yuhang Zang', 'Yuhang Cao', 'Bin Wang', 'Linke Ouyang', 'Xilin Wei', 'Songyang Zhang', 'Haodong Duan', 'Maosong Cao', 'Wenwei Zhang', 'Yining Li', 'Hang Yan', 'Yang Gao', 'Xinyue Zhang', 'Wei Li', 'Jingwen Li', 'Kai Chen', 'Conghui He', 'Xingcheng Zhang', 'Yu Qiao', 'Dahua Lin', 'Jiaqi W... | 2,024 | arXiv.org | 268 | 92 | ['Computer Science'] |
2,401.16421 | Two Stones Hit One Bird: Bilevel Positional Encoding for Better Length
Extrapolation | ['Zhenyu He', 'Guhao Feng', 'Shengjie Luo', 'Kai Yang', 'Liwei Wang', 'Jingjing Xu', 'Zhi Zhang', 'Hongxia Yang', 'Di He'] | ['cs.LG', 'cs.AI', 'cs.CL', 'stat.ML'] | In this work, we leverage the intrinsic segmentation of language sequences
and design a new positional encoding method called Bilevel Positional Encoding
(BiPE). For each position, our BiPE blends an intra-segment encoding and an
inter-segment encoding. The intra-segment encoding identifies the locations
within a segme... | 2024-01-29T18:59:07Z | 17 pages, 7 figures, 8 tables; ICML 2024 Camera Ready version; Code:
https://github.com/zhenyuhe00/BiPE | null | null | null | null | null | null | null | null | null |
2,401.16437 | A Benchmark Dataset for Tornado Detection and Prediction using
Full-Resolution Polarimetric Weather Radar Data | ['Mark S. Veillette', 'James M. Kurdzo', 'Phillip M. Stepanian', 'John Y. N. Cho', 'Siddharth Samsi', 'Joseph McDonald'] | ['physics.ao-ph', 'cs.LG'] | Weather radar is the primary tool used by forecasters to detect and warn for
tornadoes in near-real time. In order to assist forecasters in warning the
public, several algorithms have been developed to automatically detect tornadic
signatures in weather radar observations. Recently, Machine Learning (ML)
algorithms, wh... | 2024-01-26T21:47:39Z | 37 pages, 15 Figures, 2 Tables | null | null | null | null | null | null | null | null | null |
2,401.16456 | SHViT: Single-Head Vision Transformer with Memory Efficient Macro Design | ['Seokju Yun', 'Youngmin Ro'] | ['cs.CV'] | Recently, efficient Vision Transformers have shown great performance with low
latency on resource-constrained devices. Conventionally, they use 4x4 patch
embeddings and a 4-stage structure at the macro level, while utilizing
sophisticated attention with multi-head configuration at the micro level. This
paper aims to ad... | 2024-01-29T09:12:23Z | CVPR 2024 | null | null | null | null | null | null | null | null | null |
2,401.16468 | InstructIR: High-Quality Image Restoration Following Human Instructions | ['Marcos V. Conde', 'Gregor Geigle', 'Radu Timofte'] | ['cs.CV', 'cs.LG', 'eess.IV'] | Image restoration is a fundamental problem that involves recovering a
high-quality clean image from its degraded observation. All-In-One image
restoration models can effectively restore images from various types and levels
of degradation using degradation-specific information as prompts to guide the
restoration model. ... | 2024-01-29T18:53:33Z | European Conference on Computer Vision (ECCV) 2024 | null | null | InstructIR: High-Quality Image Restoration Following Human Instructions | ['Marcos V. Conde', 'Gregor Geigle', 'R. Timofte'] | 2,024 | European Conference on Computer Vision | 58 | 109 | ['Computer Science', 'Engineering'] |
2,401.1664 | TeenyTinyLlama: open-source tiny language models trained in Brazilian
Portuguese | ['Nicholas Kluge Corrêa', 'Sophia Falk', 'Shiza Fatimah', 'Aniket Sen', 'Nythamar de Oliveira'] | ['cs.CL', 'cs.LG'] | Large language models (LLMs) have significantly advanced natural language
processing, but their progress has yet to be equal across languages. While most
LLMs are trained in high-resource languages like English, multilingual models
generally underperform monolingual ones. Additionally, aspects of their
multilingual fou... | 2024-01-30T00:25:54Z | 21 pages, 5 figures | Machine Learning With Applications, 16, 100558 | 10.1016/j.mlwa.2024.100558 | null | null | null | null | null | null | null |
2,401.16658 | OWSM v3.1: Better and Faster Open Whisper-Style Speech Models based on
E-Branchformer | ['Yifan Peng', 'Jinchuan Tian', 'William Chen', 'Siddhant Arora', 'Brian Yan', 'Yui Sudo', 'Muhammad Shakeel', 'Kwanghee Choi', 'Jiatong Shi', 'Xuankai Chang', 'Jee-weon Jung', 'Shinji Watanabe'] | ['cs.CL', 'eess.AS'] | Recent studies have highlighted the importance of fully open foundation
models. The Open Whisper-style Speech Model (OWSM) is an initial step towards
reproducing OpenAI Whisper using public data and open-source toolkits. However,
previous versions of OWSM (v1 to v3) are still based on standard Transformer,
which might ... | 2024-01-30T01:22:18Z | Accepted at INTERSPEECH 2024. Webpage:
https://www.wavlab.org/activities/2024/owsm/ | null | null | OWSM v3.1: Better and Faster Open Whisper-Style Speech Models based on E-Branchformer | ['Yifan Peng', 'Jinchuan Tian', 'William Chen', 'Siddhant Arora', 'Brian Yan', 'Yui Sudo', 'Muhammad Shakeel', 'Kwanghee Choi', 'Jiatong Shi', 'Xuankai Chang', 'Jee-weon Jung', 'Shinji Watanabe'] | 2,024 | Interspeech | 54 | 59 | ['Computer Science', 'Engineering'] |
2,401.16818 | H2O-Danube-1.8B Technical Report | ['Philipp Singer', 'Pascal Pfeiffer', 'Yauhen Babakhin', 'Maximilian Jeblick', 'Nischay Dhankhar', 'Gabor Fodor', 'Sri Satish Ambati'] | ['cs.CL', 'cs.LG'] | We present H2O-Danube, a series of small 1.8B language models consisting of
H2O-Danube-1.8B, trained on 1T tokens, and the incremental improved
H2O-Danube2-1.8B trained on an additional 2T tokens. Our models exhibit highly
competitive metrics across a multitude of benchmarks and, as of the time of
this writing, H2O-Dan... | 2024-01-30T08:45:08Z | null | null | null | null | null | null | null | null | null | null |
2,401.1723 | ESPnet-SPK: full pipeline speaker embedding toolkit with reproducible
recipes, self-supervised front-ends, and off-the-shelf models | ['Jee-weon Jung', 'Wangyou Zhang', 'Jiatong Shi', 'Zakaria Aldeneh', 'Takuya Higuchi', 'Barry-John Theobald', 'Ahmed Hussen Abdelaziz', 'Shinji Watanabe'] | ['cs.SD', 'cs.AI', 'eess.AS'] | This paper introduces ESPnet-SPK, a toolkit designed with several objectives
for training speaker embedding extractors. First, we provide an open-source
platform for researchers in the speaker recognition community to effortlessly
build models. We provide several models, ranging from x-vector to recent
SKA-TDNN. Throug... | 2024-01-30T18:18:27Z | 5 pages, 3 figures, 7 tables, Interspeech 2024 | null | null | null | null | null | null | null | null | null |
2,401.1727 | YOLO-World: Real-Time Open-Vocabulary Object Detection | ['Tianheng Cheng', 'Lin Song', 'Yixiao Ge', 'Wenyu Liu', 'Xinggang Wang', 'Ying Shan'] | ['cs.CV'] | The You Only Look Once (YOLO) series of detectors have established themselves
as efficient and practical tools. However, their reliance on predefined and
trained object categories limits their applicability in open scenarios.
Addressing this limitation, we introduce YOLO-World, an innovative approach
that enhances YOLO... | 2024-01-30T18:59:38Z | Work still in progress. Code & models are available at:
https://github.com/AILab-CVC/YOLO-World | null | null | YOLO-World: Real-Time Open-Vocabulary Object Detection | ['Tianheng Cheng', 'Lin Song', 'Yixiao Ge', 'Wenyu Liu', 'Xinggang Wang', 'Ying Shan'] | 2,024 | Computer Vision and Pattern Recognition | 301 | 69 | ['Computer Science'] |
2,401.17396 | Fine-tuning Transformer-based Encoder for Turkish Language Understanding
Tasks | ['Savas Yildirim'] | ['cs.CL', 'cs.AI'] | Deep learning-based and lately Transformer-based language models have been
dominating the studies of natural language processing in the last years. Thanks
to their accurate and fast fine-tuning characteristics, they have outperformed
traditional machine learning-based approaches and achieved state-of-the-art
results fo... | 2024-01-30T19:27:04Z | null | null | null | Fine-tuning Transformer-based Encoder for Turkish Language Understanding Tasks | ['Savaş Yıldırım'] | 2,024 | arXiv.org | 7 | 34 | ['Computer Science'] |
2,401.17851 | Instruction-Guided Scene Text Recognition | ['Yongkun Du', 'Zhineng Chen', 'Yuchen Su', 'Caiyan Jia', 'Yu-Gang Jiang'] | ['cs.CV'] | Multi-modal models have shown appealing performance in visual recognition
tasks, as free-form text-guided training evokes the ability to understand
fine-grained visual content. However, current models cannot be trivially
applied to scene text recognition (STR) due to the compositional difference
between natural and tex... | 2024-01-31T14:13:01Z | Accepted by TPAMI | null | null | null | null | null | null | null | null | null |
2,401.17948 | HyperZ$\cdot$Z$\cdot$W Operator Connects Slow-Fast Networks for Full
Context Interaction | ['Harvie Zhang'] | ['cs.CV'] | The self-attention mechanism utilizes large implicit weight matrices,
programmed through dot product-based activations with very few trainable
parameters, to enable long sequence modeling. In this paper, we investigate the
possibility of discarding residual learning by employing large implicit kernels
to achieve full c... | 2024-01-31T15:57:21Z | 10 pages, 6 figures, 5 tables | null | null | null | null | null | null | null | null | null |
2,401.18034 | Paramanu: A Family of Novel Efficient Generative Foundation Language
Models for Indian Languages | ['Mitodru Niyogi', 'Arnab Bhattacharya'] | ['cs.CL', 'cs.AI'] | We present "Paramanu", a family of novel language models (LM) for Indian
languages, consisting of auto-regressive monolingual, bilingual, and
multilingual models pretrained from scratch. Currently, it covers 10 languages
(Assamese, Bangla, Hindi, Konkani, Maithili, Marathi, Odia, Sanskrit, Tamil,
Telugu) across 5 scrip... | 2024-01-31T17:58:10Z | null | null | null | null | null | null | null | null | null | null |
2,401.18058 | LongAlign: A Recipe for Long Context Alignment of Large Language Models | ['Yushi Bai', 'Xin Lv', 'Jiajie Zhang', 'Yuze He', 'Ji Qi', 'Lei Hou', 'Jie Tang', 'Yuxiao Dong', 'Juanzi Li'] | ['cs.CL', 'cs.LG'] | Extending large language models to effectively handle long contexts requires
instruction fine-tuning on input sequences of similar length. To address this,
we present LongAlign -- a recipe of the instruction data, training, and
evaluation for long context alignment. First, we construct a long
instruction-following data... | 2024-01-31T18:29:39Z | null | null | null | null | null | null | null | null | null | null |
2,401.18079 | KVQuant: Towards 10 Million Context Length LLM Inference with KV Cache
Quantization | ['Coleman Hooper', 'Sehoon Kim', 'Hiva Mohammadzadeh', 'Michael W. Mahoney', 'Yakun Sophia Shao', 'Kurt Keutzer', 'Amir Gholami'] | ['cs.LG'] | LLMs are seeing growing use for applications which require large context
windows, and with these large context windows KV cache activations surface as
the dominant contributor to memory consumption during inference. Quantization
is a promising approach for compressing KV cache activations; however, existing
solutions f... | 2024-01-31T18:58:14Z | NeurIPS 2024 | null | null | KVQuant: Towards 10 Million Context Length LLM Inference with KV Cache Quantization | ['Coleman Hooper', 'Sehoon Kim', 'Hiva Mohammadzadeh', 'Michael W. Mahoney', 'Y. Shao', 'Kurt Keutzer', 'A. Gholami'] | 2,024 | Neural Information Processing Systems | 224 | 51 | ['Computer Science'] |
2,402.00075 | D-Nikud: Enhancing Hebrew Diacritization with LSTM and Pretrained Models | ['Adi Rosenthal', 'Nadav Shaked'] | ['cs.CL'] | D-Nikud, a novel approach to Hebrew diacritization that integrates the
strengths of LSTM networks and BERT-based (transformer) pre-trained model.
Inspired by the methodologies employed in Nakdimon, we integrate it with the
TavBERT pre-trained model, our system incorporates advanced architectural
choices and diverse tra... | 2024-01-30T22:07:12Z | null | null | null | null | null | null | null | null | null | null |
2,402.00126 | Common Sense Reasoning for Deepfake Detection | ['Yue Zhang', 'Ben Colman', 'Xiao Guo', 'Ali Shahriyari', 'Gaurav Bharaj'] | ['cs.CV', 'cs.CL'] | State-of-the-art deepfake detection approaches rely on image-based features
extracted via neural networks. While these approaches trained in a supervised
manner extract likely fake features, they may fall short in representing
unnatural `non-physical' semantic facial attributes -- blurry hairlines, double
eyebrows, rig... | 2024-01-31T19:11:58Z | null | null | null | Common Sense Reasoning for Deep Fake Detection | ['Yue Zhang', 'Ben Colman', 'Ali Shahriyari', 'Gaurav Bharaj'] | 2,024 | European Conference on Computer Vision | 35 | 67 | ['Computer Science'] |
2,402.00159 | Dolma: an Open Corpus of Three Trillion Tokens for Language Model
Pretraining Research | ['Luca Soldaini', 'Rodney Kinney', 'Akshita Bhagia', 'Dustin Schwenk', 'David Atkinson', 'Russell Authur', 'Ben Bogin', 'Khyathi Chandu', 'Jennifer Dumas', 'Yanai Elazar', 'Valentin Hofmann', 'Ananya Harsh Jha', 'Sachin Kumar', 'Li Lucy', 'Xinxi Lyu', 'Nathan Lambert', 'Ian Magnusson', 'Jacob Morrison', 'Niklas Muennig... | ['cs.CL'] | Information about pretraining corpora used to train the current
best-performing language models is seldom discussed: commercial models rarely
detail their data, and even open models are often released without accompanying
training data or recipes to reproduce them. As a result, it is challenging to
conduct and advance ... | 2024-01-31T20:29:50Z | Accepted at ACL 2024; Dataset: https://hf.co/datasets/allenai/dolma;
Code: https://github.com/allenai/dolma | null | null | null | null | null | null | null | null | null |
2,402.0016 | Emergency Department Decision Support using Clinical Pseudo-notes | ['Simon A. Lee', 'Sujay Jain', 'Alex Chen', 'Kyoka Ono', 'Jennifer Fang', 'Akos Rudas', 'Jeffrey N. Chiang'] | ['cs.CL'] | In this work, we introduce the Multiple Embedding Model for EHR (MEME), an
approach that serializes multimodal EHR tabular data into text using
pseudo-notes, mimicking clinical text generation. This conversion not only
preserves better representations of categorical data and learns contexts but
also enables the effecti... | 2024-01-31T20:31:56Z | null | npj Digital Medicine 8 (1), 394, 2025 | 10.1038/s41746-025-01777-x | Emergency Department Decision Support using Clinical Pseudo-notes | ['Simon A. Lee', 'Sujay Jain', 'Alex Chen', 'Kyoka Ono', 'Jennifer Fang', 'Á. Rudas', 'Jeffrey N. Chiang'] | 2,024 | null | 12 | 54 | ['Computer Science'] |
2,402.00281 | Guided Interpretable Facial Expression Recognition via Spatial Action
Unit Cues | ['Soufiane Belharbi', 'Marco Pedersoli', 'Alessandro Lameiras Koerich', 'Simon Bacon', 'Eric Granger'] | ['cs.CV'] | Although state-of-the-art classifiers for facial expression recognition (FER)
can achieve a high level of accuracy, they lack interpretability, an important
feature for end-users. Experts typically associate spatial action units (\aus)
from a codebook to facial regions for the visual interpretation of expressions.
In t... | 2024-02-01T02:13:49Z | 15 pages, 11 figures, 3 tables, International Conference on Automatic
Face and Gesture Recognition (FG 2024) | null | null | Guided Interpretable Facial Expression Recognition via Spatial Action Unit Cues | ['Soufiane Belharbi', 'Marco Pedersoli', 'A. Koerich', 'Simon Bacon', 'Eric Granger'] | 2,024 | IEEE International Conference on Automatic Face & Gesture Recognition | 14 | 94 | ['Computer Science'] |
2,402.003 | Self-supervised learning of video representations from a child's
perspective | ['A. Emin Orhan', 'Wentao Wang', 'Alex N. Wang', 'Mengye Ren', 'Brenden M. Lake'] | ['cs.CV', 'cs.LG', 'cs.NE', 'q-bio.NC'] | Children learn powerful internal models of the world around them from a few
years of egocentric visual experience. Can such internal models be learned from
a child's visual experience with highly generic learning algorithms or do they
require strong inductive biases? Recent advances in collecting large-scale,
longitudi... | 2024-02-01T03:27:26Z | v3 updates results with significantly improved models; v2 was
published as a conference paper at CogSci 2024; code & models available from
https://github.com/eminorhan/video-models | null | null | Self-supervised learning of video representations from a child's perspective | ['A. Orhan', 'Wentao Wang', 'Alex N. Wang', 'Mengye Ren', 'B. Lake'] | 2,024 | arXiv.org | 4 | 23 | ['Computer Science', 'Biology'] |
2,402.00453 | Instruction Makes a Difference | ['Tosin Adewumi', 'Nudrat Habib', 'Lama Alkhaled', 'Elisa Barney'] | ['cs.CV', 'cs.CL'] | We introduce Instruction Document Visual Question Answering (iDocVQA) dataset
and Large Language Document (LLaDoc) model, for training Language-Vision (LV)
models for document analysis and predictions on document images, respectively.
Usually, deep neural networks for the DocVQA task are trained on datasets
lacking ins... | 2024-02-01T09:43:30Z | Accepted at the 16th IAPR International Workshop On Document Analysis
Systems (DAS) | null | null | Instruction Makes a Difference | ['Tosin P. Adewumi', 'Nudrat Habib', 'Lama Alkhaled', 'Elisa Barney'] | 2,024 | International Workshop on Document Analysis Systems | 1 | 47 | ['Computer Science'] |
2,402.00691 | Comparative Study of Large Language Model Architectures on Frontier | ['Junqi Yin', 'Avishek Bose', 'Guojing Cong', 'Isaac Lyngaas', 'Quentin Anthony'] | ['cs.DC'] | Large language models (LLMs) have garnered significant attention in both the
AI community and beyond. Among these, the Generative Pre-trained Transformer
(GPT) has emerged as the dominant architecture, spawning numerous variants.
However, these variants have undergone pre-training under diverse conditions,
including va... | 2024-02-01T15:50:37Z | null | null | null | Comparative Study of Large Language Model Architectures on Frontier | ['Junqi Yin', 'A. Bose', 'Guojing Cong', 'Isaac Lyngaas', 'Quentin Anthony'] | 2,024 | IEEE International Parallel and Distributed Processing Symposium | 7 | 47 | ['Computer Science'] |
2,402.00769 | AnimateLCM: Computation-Efficient Personalized Style Video Generation
without Personalized Video Data | ['Fu-Yun Wang', 'Zhaoyang Huang', 'Weikang Bian', 'Xiaoyu Shi', 'Keqiang Sun', 'Guanglu Song', 'Yu Liu', 'Hongsheng Li'] | ['cs.CV', 'cs.LG'] | This paper introduces an effective method for computation-efficient
personalized style video generation without requiring access to any
personalized video data. It reduces the necessary generation time of similarly
sized video diffusion models from 25 seconds to around 1 second while
maintaining the same level of perfo... | 2024-02-01T16:58:11Z | Accepted as a Short Paper by SIGGRAPH ASIA 2024 Technical
Communications. This is a short version of the original work. Project Page:
https://animatelcm.github.io/ | null | null | null | null | null | null | null | null | null |
2,402.00786 | CroissantLLM: A Truly Bilingual French-English Language Model | ['Manuel Faysse', 'Patrick Fernandes', 'Nuno M. Guerreiro', 'António Loison', 'Duarte M. Alves', 'Caio Corro', 'Nicolas Boizard', 'João Alves', 'Ricardo Rei', 'Pedro H. Martins', 'Antoni Bigata Casademunt', 'François Yvon', 'André F. T. Martins', 'Gautier Viaud', 'Céline Hudelot', 'Pierre Colombo'] | ['cs.CL', 'cs.LG'] | We introduce CroissantLLM, a 1.3B language model pretrained on a set of 3T
English and French tokens, to bring to the research and industrial community a
high-performance, fully open-sourced bilingual model that runs swiftly on
consumer-grade local hardware. To that end, we pioneer the approach of training
an intrinsic... | 2024-02-01T17:17:55Z | null | null | null | CroissantLLM: A Truly Bilingual French-English Language Model | ['Manuel Faysse', 'Patrick Fernandes', 'Nuno M. Guerreiro', 'António Loison', 'Duarte M. Alves', 'Caio Corro', 'Nicolas Boizard', 'João Alves', 'Ricardo Rei', 'P. Martins', 'Antoni Bigata Casademunt', 'François Yvon', 'André Martins', 'Gautier Viaud', "C'eline Hudelot", 'Pierre Colombo'] | 2,024 | Trans. Mach. Learn. Res. | 37 | 84 | ['Computer Science'] |
2,402.00838 | OLMo: Accelerating the Science of Language Models | ['Dirk Groeneveld', 'Iz Beltagy', 'Pete Walsh', 'Akshita Bhagia', 'Rodney Kinney', 'Oyvind Tafjord', 'Ananya Harsh Jha', 'Hamish Ivison', 'Ian Magnusson', 'Yizhong Wang', 'Shane Arora', 'David Atkinson', 'Russell Authur', 'Khyathi Raghavi Chandu', 'Arman Cohan', 'Jennifer Dumas', 'Yanai Elazar', 'Yuling Gu', 'Jack Hess... | ['cs.CL'] | Language models (LMs) have become ubiquitous in both NLP research and in
commercial product offerings. As their commercial importance has surged, the
most powerful models have become closed off, gated behind proprietary
interfaces, with important details of their training data, architectures, and
development undisclose... | 2024-02-01T18:28:55Z | null | null | null | null | null | null | null | null | null | null |
2,402.00841 | Tiny Titans: Can Smaller Large Language Models Punch Above Their Weight
in the Real World for Meeting Summarization? | ['Xue-Yong Fu', 'Md Tahmid Rahman Laskar', 'Elena Khasanova', 'Cheng Chen', 'Shashi Bhushan TN'] | ['cs.CL'] | Large Language Models (LLMs) have demonstrated impressive capabilities to
solve a wide range of tasks without being explicitly fine-tuned on
task-specific datasets. However, deploying LLMs in the real world is not
trivial, as it requires substantial computing resources. In this paper, we
investigate whether smaller, co... | 2024-02-01T18:31:34Z | Accepted by NAACL 2024 (Industry Track). The first two authors
contributed equally to this work | null | null | Tiny Titans: Can Smaller Large Language Models Punch Above Their Weight in the Real World for Meeting Summarization? | ['Xue-Yong Fu', 'Md Tahmid Rahman Laskar', 'Elena Khasanova', 'Cheng Chen', 'TN ShashiBhushan'] | 2,024 | North American Chapter of the Association for Computational Linguistics | 23 | 27 | ['Computer Science'] |
2,402.00847 | BootsTAP: Bootstrapped Training for Tracking-Any-Point | ['Carl Doersch', 'Pauline Luc', 'Yi Yang', 'Dilara Gokay', 'Skanda Koppula', 'Ankush Gupta', 'Joseph Heyward', 'Ignacio Rocco', 'Ross Goroshin', 'João Carreira', 'Andrew Zisserman'] | ['cs.CV', 'stat.ML'] | To endow models with greater understanding of physics and motion, it is
useful to enable them to perceive how solid surfaces move and deform in real
scenes. This can be formalized as Tracking-Any-Point (TAP), which requires the
algorithm to track any point on solid surfaces in a video, potentially densely
in space and ... | 2024-02-01T18:38:55Z | null | null | null | null | null | null | null | null | null | null |
2,402.00856 | Towards Efficient Exact Optimization of Language Model Alignment | ['Haozhe Ji', 'Cheng Lu', 'Yilin Niu', 'Pei Ke', 'Hongning Wang', 'Jun Zhu', 'Jie Tang', 'Minlie Huang'] | ['cs.CL'] | The alignment of language models with human preferences is vital for their
application in real-world tasks. The problem is formulated as optimizing the
model's policy to maximize the expected reward that reflects human preferences
with minimal deviation from the initial policy. While considered as a
straightforward sol... | 2024-02-01T18:51:54Z | 24 pages, 9 figures | Forty-first International Conference on Machine Learning (ICML
2024) | null | null | null | null | null | null | null | null |
2,402.00892 | EVA-GAN: Enhanced Various Audio Generation via Scalable Generative
Adversarial Networks | ['Shijia Liao', 'Shiyi Lan', 'Arun George Zachariah'] | ['cs.SD', 'cs.AI', 'cs.LG', 'eess.AS'] | The advent of Large Models marks a new era in machine learning, significantly
outperforming smaller models by leveraging vast datasets to capture and
synthesize complex patterns. Despite these advancements, the exploration into
scaling, especially in the audio generation domain, remains limited, with
previous efforts d... | 2024-01-31T03:31:03Z | null | null | null | EVA-GAN: Enhanced Various Audio Generation via Scalable Generative Adversarial Networks | ['Shijia Liao', 'Shiyi Lan', 'Arun George Zachariah'] | 2,024 | arXiv.org | 1 | 25 | ['Computer Science', 'Engineering'] |
2,402.01002 | AI-generated faces influence gender stereotypes and racial
homogenization | ['Nouar AlDahoul', 'Talal Rahwan', 'Yasir Zaki'] | ['cs.CV', 'cs.AI'] | Text-to-image generative AI models such as Stable Diffusion are used daily by
millions worldwide. However, the extent to which these models exhibit racial
and gender stereotypes is not yet fully understood. Here, we document
significant biases in Stable Diffusion across six races, two genders, 32
professions, and eight... | 2024-02-01T20:32:14Z | 47 pages, 19 figures | null | null | null | null | null | null | null | null | null |
2,402.0103 | Executable Code Actions Elicit Better LLM Agents | ['Xingyao Wang', 'Yangyi Chen', 'Lifan Yuan', 'Yizhe Zhang', 'Yunzhu Li', 'Hao Peng', 'Heng Ji'] | ['cs.CL', 'cs.AI'] | Large Language Model (LLM) agents, capable of performing a broad range of
actions, such as invoking tools and controlling robots, show great potential in
tackling real-world challenges. LLM agents are typically prompted to produce
actions by generating JSON or text in a pre-defined format, which is usually
limited by c... | 2024-02-01T21:38:58Z | Accepted by ICML 2024; Code, data, model, and demo are available at
https://github.com/xingyaoww/code-act | null | null | null | null | null | null | null | null | null |
2,402.01053 | Plan-Grounded Large Language Models for Dual Goal Conversational
Settings | ['Diogo Glória-Silva', 'Rafael Ferreira', 'Diogo Tavares', 'David Semedo', 'João Magalhães'] | ['cs.CL', 'cs.AI'] | Training Large Language Models (LLMs) to follow user instructions has been
shown to supply the LLM with ample capacity to converse fluently while being
aligned with humans. Yet, it is not completely clear how an LLM can lead a
plan-grounded conversation in mixed-initiative settings where instructions flow
in both direc... | 2024-02-01T22:56:39Z | null | null | null | null | null | null | null | null | null | null |
2,402.01306 | KTO: Model Alignment as Prospect Theoretic Optimization | ['Kawin Ethayarajh', 'Winnie Xu', 'Niklas Muennighoff', 'Dan Jurafsky', 'Douwe Kiela'] | ['cs.LG', 'cs.AI'] | Kahneman & Tversky's $\textit{prospect theory}$ tells us that humans perceive
random variables in a biased but well-defined manner (1992); for example,
humans are famously loss-averse. We show that objectives for aligning LLMs with
human feedback implicitly incorporate many of these biases -- the success of
these objec... | 2024-02-02T10:53:36Z | ICML 2024 | null | null | null | null | null | null | null | null | null |
2,402.01469 | AMOR: A Recipe for Building Adaptable Modular Knowledge Agents Through
Process Feedback | ['Jian Guan', 'Wei Wu', 'Zujie Wen', 'Peng Xu', 'Hongning Wang', 'Minlie Huang'] | ['cs.CL'] | The notable success of large language models (LLMs) has sparked an upsurge in
building language agents to complete various complex tasks. We present AMOR, an
agent framework based on open-source LLMs, which reasons with external
knowledge bases and adapts to specific domains through human supervision to the
reasoning p... | 2024-02-02T14:56:48Z | NeurIPS 2024 | null | null | AMOR: A Recipe for Building Adaptable Modular Knowledge Agents Through Process Feedback | ['Jian Guan', 'Wei Wu', 'Zujie Wen', 'Peng Xu', 'Hongning Wang', 'Minlie Huang'] | 2,024 | Neural Information Processing Systems | 20 | 57 | ['Computer Science'] |
2,402.01528 | Decoding Speculative Decoding | ['Minghao Yan', 'Saurabh Agarwal', 'Shivaram Venkataraman'] | ['cs.LG', 'cs.CL'] | Speculative Decoding is a widely used technique to speed up inference for
Large Language Models (LLMs) without sacrificing quality. When performing
inference, speculative decoding uses a smaller draft model to generate
speculative tokens and then uses the target LLM to verify those draft tokens.
The speedup provided by... | 2024-02-02T16:15:24Z | Proceedings of the 2025 Conference of the North American Chapter of
the Association for Computational Linguistics: Human Language Technologies
(NAACL 2025) | null | null | null | null | null | null | null | null | null |
2,402.01613 | Nomic Embed: Training a Reproducible Long Context Text Embedder | ['Zach Nussbaum', 'John X. Morris', 'Brandon Duderstadt', 'Andriy Mulyar'] | ['cs.CL', 'cs.AI'] | This technical report describes the training of nomic-embed-text-v1, the
first fully reproducible, open-source, open-weights, open-data, 8192 context
length English text embedding model that outperforms both OpenAI Ada-002 and
OpenAI text-embedding-3-small on the short-context MTEB benchmark and the long
context LoCo b... | 2024-02-02T18:23:18Z | Accepted to TMLR https://openreview.net/forum?id=IPmzyQSiQE | null | null | Nomic Embed: Training a Reproducible Long Context Text Embedder | ['Zach Nussbaum', 'John X. Morris', 'Brandon Duderstadt', 'Andriy Mulyar'] | 2,024 | Trans. Mach. Learn. Res. | 124 | 76 | ['Computer Science'] |
2,402.01728 | Hardware Phi-1.5B: A Large Language Model Encodes Hardware Domain
Specific Knowledge | ['Weimin Fu', 'Shijie Li', 'Yifang Zhao', 'Haocheng Ma', 'Raj Dutta', 'Xuan Zhang', 'Kaichen Yang', 'Yier Jin', 'Xiaolong Guo'] | ['cs.CL', 'cs.AI', 'cs.AR'] | In the rapidly evolving semiconductor industry, where research, design,
verification, and manufacturing are intricately linked, the potential of Large
Language Models to revolutionize hardware design and security verification is
immense. The primary challenge, however, lies in the complexity of hardware
specific issues... | 2024-01-27T22:49:43Z | 6 pages, 6 figures | 29th IEEE/ACM Asia and South Pacific Design Automation Conference
(ASP-DAC); 2024 January; Incheon Songdo Convensia, South Korea | null | Hardware Phi-1.5B: A Large Language Model Encodes Hardware Domain Specific Knowledge | ['Weimin Fu', 'Shijie Li', 'Yifang Zhao', 'Haocheng Ma', 'R. Dutta', 'Xuan Zhang', 'Kaichen Yang', 'Yier Jin', 'Xiaolong Guo'] | 2,024 | Asia and South Pacific Design Automation Conference | 10 | 37 | ['Computer Science'] |
2,402.01758 | Aalap: AI Assistant for Legal & Paralegal Functions in India | ['Aman Tiwari', 'Prathamesh Kalamkar', 'Atreyo Banerjee', 'Saurabh Karn', 'Varun Hemachandran', 'Smita Gupta'] | ['cs.CY', 'cs.AI', 'cs.CL'] | Using proprietary Large Language Models on legal tasks poses challenges due
to data privacy issues, domain data heterogeneity, domain knowledge
sophistication, and domain objectives uniqueness. We created Aalalp, a
fine-tuned Mistral 7B model on instructions data related to specific Indian
legal tasks. The performance ... | 2024-01-30T12:39:58Z | null | null | null | Aalap: AI Assistant for Legal & Paralegal Functions in India | ['Aman Tiwari', 'Prathamesh Kalamkar', 'Atreyo Banerjee', 'S. Karn', 'V. Hemachandran', 'Smita Gupta'] | 2,024 | arXiv.org | 1 | 30 | ['Computer Science'] |
2,402.01771 | BlackMamba: Mixture of Experts for State-Space Models | ['Quentin Anthony', 'Yury Tokpanov', 'Paolo Glorioso', 'Beren Millidge'] | ['cs.CL', 'cs.AI', 'cs.DC', 'cs.LG'] | State-space models (SSMs) have recently demonstrated competitive performance
to transformers at large-scale language modeling benchmarks while achieving
linear time and memory complexity as a function of sequence length. Mamba, a
recently released SSM model, shows impressive performance in both language
modeling and lo... | 2024-02-01T07:15:58Z | null | null | null | null | null | null | null | null | null | null |
2,402.01831 | Audio Flamingo: A Novel Audio Language Model with Few-Shot Learning and
Dialogue Abilities | ['Zhifeng Kong', 'Arushi Goel', 'Rohan Badlani', 'Wei Ping', 'Rafael Valle', 'Bryan Catanzaro'] | ['cs.SD', 'cs.LG', 'eess.AS'] | Augmenting large language models (LLMs) to understand audio -- including
non-speech sounds and non-verbal speech -- is critically important for diverse
real-world applications of LLMs. In this paper, we propose Audio Flamingo, a
novel audio language model with 1) strong audio understanding abilities, 2) the
ability to ... | 2024-02-02T18:58:34Z | ICML 2024 | null | null | Audio Flamingo: A Novel Audio Language Model with Few-Shot Learning and Dialogue Abilities | ['Zhifeng Kong', 'Arushi Goel', 'Rohan Badlani', 'Wei Ping', 'Rafael Valle', 'Bryan Catanzaro'] | 2,024 | International Conference on Machine Learning | 94 | 93 | ['Computer Science', 'Engineering'] |
2,402.01912 | Natural language guidance of high-fidelity text-to-speech with synthetic
annotations | ['Dan Lyth', 'Simon King'] | ['cs.SD', 'cs.CL', 'eess.AS'] | Text-to-speech models trained on large-scale datasets have demonstrated
impressive in-context learning capabilities and naturalness. However, control
of speaker identity and style in these models typically requires conditioning
on reference speech recordings, limiting creative applications. Alternatively,
natural langu... | 2024-02-02T21:29:34Z | null | null | null | null | null | null | null | null | null | null |
2,402.01935 | Code Representation Learning At Scale | ['Dejiao Zhang', 'Wasi Ahmad', 'Ming Tan', 'Hantian Ding', 'Ramesh Nallapati', 'Dan Roth', 'Xiaofei Ma', 'Bing Xiang'] | ['cs.CL'] | Recent studies have shown that code language models at scale demonstrate
significant performance gains on downstream tasks, i.e., code generation.
However, most of the existing works on code representation learning train
models at a hundred million parameter scale using very limited pretraining
corpora. In this work, w... | 2024-02-02T22:19:15Z | 10 pages | ICLR 2024 | null | null | null | null | null | null | null | null |
2,402.0198 | SOCIALITE-LLAMA: An Instruction-Tuned Model for Social Scientific Tasks | ['Gourab Dey', 'Adithya V Ganesan', 'Yash Kumar Lal', 'Manal Shah', 'Shreyashee Sinha', 'Matthew Matero', 'Salvatore Giorgi', 'Vivek Kulkarni', 'H. Andrew Schwartz'] | ['cs.CL'] | Social science NLP tasks, such as emotion or humor detection, are required to
capture the semantics along with the implicit pragmatics from text, often with
limited amounts of training data. Instruction tuning has been shown to improve
the many capabilities of large language models (LLMs) such as commonsense
reasoning,... | 2024-02-03T01:33:16Z | Short paper accepted to EACL 2024. 4 pgs, 2 tables | null | null | null | null | null | null | null | null | null |
2,402.01981 | Self-Debiasing Large Language Models: Zero-Shot Recognition and
Reduction of Stereotypes | ['Isabel O. Gallegos', 'Ryan A. Rossi', 'Joe Barrow', 'Md Mehrab Tanjim', 'Tong Yu', 'Hanieh Deilamsalehy', 'Ruiyi Zhang', 'Sungchul Kim', 'Franck Dernoncourt'] | ['cs.CL', 'cs.AI', 'cs.CY', 'cs.LG'] | Large language models (LLMs) have shown remarkable advances in language
generation and understanding but are also prone to exhibiting harmful social
biases. While recognition of these behaviors has generated an abundance of bias
mitigation techniques, most require modifications to the training data, model
parameters, o... | 2024-02-03T01:40:11Z | null | null | null | null | null | null | null | null | null | null |
2,402.02207 | Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large
Language Models | ['Yongshuo Zong', 'Ondrej Bohdal', 'Tingyang Yu', 'Yongxin Yang', 'Timothy Hospedales'] | ['cs.LG'] | Current vision large language models (VLLMs) exhibit remarkable capabilities
yet are prone to generate harmful content and are vulnerable to even the
simplest jailbreaking attacks. Our initial analysis finds that this is due to
the presence of harmful data during vision-language instruction fine-tuning,
and that VLLM f... | 2024-02-03T16:43:42Z | ICML 2024 | null | null | Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models | ['Yongshuo Zong', 'Ondrej Bohdal', 'Tingyang Yu', 'Yongxin Yang', 'Timothy M. Hospedales'] | 2,024 | International Conference on Machine Learning | 73 | 47 | ['Computer Science'] |
2,402.02263 | MixedNUTS: Training-Free Accuracy-Robustness Balance via Nonlinearly
Mixed Classifiers | ['Yatong Bai', 'Mo Zhou', 'Vishal M. Patel', 'Somayeh Sojoudi'] | ['cs.LG', 'cs.AI', 'cs.CV', '68T07'] | Adversarial robustness often comes at the cost of degraded accuracy, impeding
real-life applications of robust classification models. Training-based
solutions for better trade-offs are limited by incompatibilities with
already-trained high-performance large models, necessitating the exploration of
training-free ensembl... | 2024-02-03T21:12:36Z | null | null | null | MixedNUTS: Training-Free Accuracy-Robustness Balance via Nonlinearly Mixed Classifiers | ['Yatong Bai', 'Mo Zhou', 'Vishal M. Patel', 'S. Sojoudi'] | 2,024 | Trans. Mach. Learn. Res. | 8 | 63 | ['Computer Science'] |
2,402.02368 | Timer: Generative Pre-trained Transformers Are Large Time Series Models | ['Yong Liu', 'Haoran Zhang', 'Chenyu Li', 'Xiangdong Huang', 'Jianmin Wang', 'Mingsheng Long'] | ['cs.LG', 'stat.ML'] | Deep learning has contributed remarkably to the advancement of time series
analysis. Still, deep models can encounter performance bottlenecks in
real-world data-scarce scenarios, which can be concealed due to the performance
saturation with small models on current benchmarks. Meanwhile, large models
have demonstrated g... | 2024-02-04T06:55:55Z | null | null | null | null | null | null | null | null | null | null |
2,402.02416 | Aligner: Efficient Alignment by Learning to Correct | ['Jiaming Ji', 'Boyuan Chen', 'Hantao Lou', 'Donghai Hong', 'Borong Zhang', 'Xuehai Pan', 'Juntao Dai', 'Tianyi Qiu', 'Yaodong Yang'] | ['cs.CL', 'cs.AI', 'cs.LG'] | With the rapid development of large language models (LLMs) and ever-evolving
practical requirements, finding an efficient and effective alignment method has
never been more critical. However, the tension between the complexity of
current alignment methods and the need for rapid iteration in deployment
scenarios necessi... | 2024-02-04T09:24:51Z | Accepted by NeurIPS 2024 Oral Presentation | null | null | null | null | null | null | null | null | null |
2,402.02464 | A Graph is Worth $K$ Words: Euclideanizing Graph using Pure Transformer | ['Zhangyang Gao', 'Daize Dong', 'Cheng Tan', 'Jun Xia', 'Bozhen Hu', 'Stan Z. Li'] | ['cs.LG', 'cs.AI', 'cs.SI'] | Can we model Non-Euclidean graphs as pure language or even Euclidean vectors
while retaining their inherent information? The Non-Euclidean property have
posed a long term challenge in graph modeling. Despite recent graph neural
networks and graph transformers efforts encoding graphs as Euclidean vectors,
recovering the... | 2024-02-04T12:29:40Z | null | null | null | null | null | null | null | null | null | null |
2,402.02574 | Spatio-temporal Prompting Network for Robust Video Feature Extraction | ['Guanxiong Sun', 'Chi Wang', 'Zhaoyu Zhang', 'Jiankang Deng', 'Stefanos Zafeiriou', 'Yang Hua'] | ['cs.CV', 'cs.LG'] | Frame quality deterioration is one of the main challenges in the field of
video understanding. To compensate for the information loss caused by
deteriorated frames, recent approaches exploit transformer-based integration
modules to obtain spatio-temporal information. However, these integration
modules are heavy and com... | 2024-02-04T17:52:04Z | null | 2023 International Conference on Computer Vision (ICCV)
13541-13551 | 10.1109/ICCV51070.2023.01250 | Spatio-temporal Prompting Network for Robust Video Feature Extraction | ['Guanxiong Sun', 'Chi Wang', 'Zhaoyu Zhang', 'Jiankang Deng', 'S. Zafeiriou', 'Yang Hua'] | 2,023 | IEEE International Conference on Computer Vision | 4 | 70 | ['Computer Science'] |
2,402.02583 | DiffEditor: Boosting Accuracy and Flexibility on Diffusion-based Image
Editing | ['Chong Mou', 'Xintao Wang', 'Jiechong Song', 'Ying Shan', 'Jian Zhang'] | ['cs.CV', 'cs.LG'] | Large-scale Text-to-Image (T2I) diffusion models have revolutionized image
generation over the last few years. Although owning diverse and high-quality
generation capabilities, translating these abilities to fine-grained image
editing remains challenging. In this paper, we propose DiffEditor to rectify
two weaknesses i... | 2024-02-04T18:50:29Z | null | null | null | DiffEditor: Boosting Accuracy and Flexibility on Diffusion-Based Image Editing | ['Chong Mou', 'Xintao Wang', 'Jie Song', 'Ying Shan', 'Jian Zhang'] | 2,024 | Computer Vision and Pattern Recognition | 55 | 0 | ['Computer Science'] |
2,402.02592 | Unified Training of Universal Time Series Forecasting Transformers | ['Gerald Woo', 'Chenghao Liu', 'Akshat Kumar', 'Caiming Xiong', 'Silvio Savarese', 'Doyen Sahoo'] | ['cs.LG', 'cs.AI'] | Deep learning for time series forecasting has traditionally operated within a
one-model-per-dataset framework, limiting its potential to leverage the
game-changing impact of large pre-trained models. The concept of universal
forecasting, emerging from pre-training on a vast collection of time series
datasets, envisions... | 2024-02-04T20:00:45Z | null | null | null | null | null | null | null | null | null | null |
2,402.02622 | DenseFormer: Enhancing Information Flow in Transformers via Depth
Weighted Averaging | ['Matteo Pagliardini', 'Amirkeivan Mohtashami', 'Francois Fleuret', 'Martin Jaggi'] | ['cs.CL', 'cs.LG'] | The transformer architecture by Vaswani et al. (2017) is now ubiquitous
across application domains, from natural language processing to speech
processing and image understanding. We propose DenseFormer, a simple
modification to the standard architecture that improves the perplexity of the
model without increasing its s... | 2024-02-04T21:44:09Z | null | null | null | null | null | null | null | null | null | null |
2,402.02632 | GIRT-Model: Automated Generation of Issue Report Templates | ['Nafiseh Nikeghbal', 'Amir Hossein Kargaran', 'Abbas Heydarnoori'] | ['cs.SE', 'cs.CL'] | Platforms such as GitHub and GitLab introduce Issue Report Templates (IRTs)
to enable more effective issue management and better alignment with developer
expectations. However, these templates are not widely adopted in most
repositories, and there is currently no tool available to aid developers in
generating them. In ... | 2024-02-04T22:53:38Z | Accepted to be published at the 21st IEEE/ACM International
Conference on Mining Software Repositories (MSR 2024) | null | 10.1145/3643991.3644906 | null | null | null | null | null | null | null |
2,402.02754 | Focal Modulation Networks for Interpretable Sound Classification | ['Luca Della Libera', 'Cem Subakan', 'Mirco Ravanelli'] | ['cs.SD', 'cs.LG', 'eess.AS'] | The increasing success of deep neural networks has raised concerns about
their inherent black-box nature, posing challenges related to interpretability
and trust. While there has been extensive exploration of interpretation
techniques in vision and language, interpretability in the audio domain has
received limited att... | 2024-02-05T06:20:52Z | Accepted to ICASSP 2024 XAI-SA Workshop | null | null | Focal Modulation Networks for Interpretable Sound Classification | ['Luca Della Libera', 'Cem Subakan', 'M. Ravanelli'] | 2,024 | 2024 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW) | 2 | 52 | ['Computer Science', 'Engineering'] |
2,402.02834 | Shortened LLaMA: Depth Pruning for Large Language Models with Comparison
of Retraining Methods | ['Bo-Kyeong Kim', 'Geonmin Kim', 'Tae-Ho Kim', 'Thibault Castells', 'Shinkook Choi', 'Junho Shin', 'Hyoung-Kyu Song'] | ['cs.LG', 'cs.CL'] | Structured pruning of modern large language models (LLMs) has emerged as a
way of decreasing their high computational needs. Width pruning reduces the
size of projection weight matrices (e.g., by removing attention heads) while
maintaining the number of layers. Depth pruning, in contrast, removes entire
layers or block... | 2024-02-05T09:44:49Z | Update (arXiv-v2): continued pretraining for severe pruning ratios,
compatibility with quantization, and enhanced baselines. Preliminary work
(arXiv-v1) accepted at ICLR 2024 Workshop on ME-FoMo:
https://openreview.net/forum?id=18VGxuOdpu | null | null | Shortened LLaMA: A Simple Depth Pruning for Large Language Models | ['Bo-Kyeong Kim', 'Geonmin Kim', 'Tae-Ho Kim', 'Thibault Castells', 'Shinkook Choi', 'Junho Shin', 'Hyoung-Kyu Song'] | 2,024 | arXiv.org | 40 | 69 | ['Computer Science'] |
2,402.03166 | RRWNet: Recursive Refinement Network for effective retinal artery/vein
segmentation and classification | ['José Morano', 'Guilherme Aresta', 'Hrvoje Bogunović'] | ['eess.IV', 'cs.CV'] | The caliber and configuration of retinal blood vessels serve as important
biomarkers for various diseases and medical conditions. A thorough analysis of
the retinal vasculature requires the segmentation of the blood vessels and
their classification into arteries and veins, typically performed on color
fundus images obt... | 2024-02-05T16:35:29Z | null | Expert Systems with Applications, 2024 | 10.1016/j.eswa.2024.124970 | RRWNet: Recursive Refinement Network for Effective Retinal Artery/Vein Segmentation and Classification | ['José Morano', 'Guilherme Aresta', "Hrvoje Bogunovi'c"] | 2,024 | Expert systems with applications | 2 | 81 | ['Computer Science', 'Engineering'] |
2,402.03216 | BGE M3-Embedding: Multi-Lingual, Multi-Functionality, Multi-Granularity
Text Embeddings Through Self-Knowledge Distillation | ['Jianlv Chen', 'Shitao Xiao', 'Peitian Zhang', 'Kun Luo', 'Defu Lian', 'Zheng Liu'] | ['cs.CL', 'cs.AI', 'cs.LG'] | In this paper, we present a new embedding model, called M3-Embedding, which
is distinguished for its versatility in Multi-Linguality, Multi-Functionality,
and Multi-Granularity. It can support more than 100 working languages, leading
to new state-of-the-art performances on multi-lingual and cross-lingual
retrieval task... | 2024-02-05T17:26:49Z | null | null | null | BGE M3-Embedding: Multi-Lingual, Multi-Functionality, Multi-Granularity Text Embeddings Through Self-Knowledge Distillation | ['Jianlv Chen', 'Shitao Xiao', 'Peitian Zhang', 'Kun Luo', 'Defu Lian', 'Zheng Liu'] | 2,024 | Annual Meeting of the Association for Computational Linguistics | 449 | 60 | ['Computer Science'] |
2,402.03284 | Deal, or no deal (or who knows)? Forecasting Uncertainty in
Conversations using Large Language Models | ['Anthony Sicilia', 'Hyunwoo Kim', 'Khyathi Raghavi Chandu', 'Malihe Alikhani', 'Jack Hessel'] | ['cs.CL', 'cs.AI', 'cs.LG'] | Effective interlocutors account for the uncertain goals, beliefs, and
emotions of others. But even the best human conversationalist cannot perfectly
anticipate the trajectory of a dialogue. How well can language models represent
inherent uncertainty in conversations? We propose FortUne Dial, an expansion of
the long-st... | 2024-02-05T18:39:47Z | 2 Figures; 7 Tables; 27 pages | null | null | null | null | null | null | null | null | null |
2,402.0329 | InstanceDiffusion: Instance-level Control for Image Generation | ['Xudong Wang', 'Trevor Darrell', 'Sai Saketh Rambhatla', 'Rohit Girdhar', 'Ishan Misra'] | ['cs.CV', 'cs.AI', 'cs.LG'] | Text-to-image diffusion models produce high quality images but do not offer
control over individual instances in the image. We introduce InstanceDiffusion
that adds precise instance-level control to text-to-image diffusion models.
InstanceDiffusion supports free-form language conditions per instance and
allows flexible... | 2024-02-05T18:49:17Z | Preprint; Project page:
https://people.eecs.berkeley.edu/~xdwang/projects/InstDiff/ | null | null | null | null | null | null | null | null | null |
2,402.033 | DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open
Language Models | ['Zhihong Shao', 'Peiyi Wang', 'Qihao Zhu', 'Runxin Xu', 'Junxiao Song', 'Xiao Bi', 'Haowei Zhang', 'Mingchuan Zhang', 'Y. K. Li', 'Y. Wu', 'Daya Guo'] | ['cs.CL', 'cs.AI', 'cs.LG'] | Mathematical reasoning poses a significant challenge for language models due
to its complex and structured nature. In this paper, we introduce DeepSeekMath
7B, which continues pre-training DeepSeek-Coder-Base-v1.5 7B with 120B
math-related tokens sourced from Common Crawl, together with natural language
and code data. ... | 2024-02-05T18:55:32Z | null | null | null | null | null | null | null | null | null | null |
2,402.03477 | Arabic Synonym BERT-based Adversarial Examples for Text Classification | ['Norah Alshahrani', 'Saied Alshahrani', 'Esma Wali', 'Jeanna Matthews'] | ['cs.CL'] | Text classification systems have been proven vulnerable to adversarial text
examples, modified versions of the original text examples that are often
unnoticed by human eyes, yet can force text classification models to alter
their classification. Often, research works quantifying the impact of
adversarial text attacks h... | 2024-02-05T19:39:07Z | This paper is accepted at The 18th Conference of the European Chapter
of the Association for Computational Linguistics (Student Research Workshop),
March 17-22, 2024 | null | null | Arabic Synonym BERT-based Adversarial Examples for Text Classification | ['Norah M. Alshahrani', 'Saied Alshahrani', 'Esma Wali', 'J. Matthews'] | 2,024 | Conference of the European Chapter of the Association for Computational Linguistics | 6 | 53 | ['Computer Science'] |
2,402.03686 | Are Machines Better at Complex Reasoning? Unveiling Human-Machine
Inference Gaps in Entailment Verification | ['Soumya Sanyal', 'Tianyi Xiao', 'Jiacheng Liu', 'Wenya Wang', 'Xiang Ren'] | ['cs.CL', 'cs.AI'] | Making inferences in text comprehension to understand the meaning is
essential in language processing. This work studies the entailment verification
(EV) problem of multi-sentence premises that requires a system to make multiple
inferences implicitly. Studying EV for such complex premises is important
because modern NL... | 2024-02-06T04:14:09Z | null | null | null | null | null | null | null | null | null | null |
2,402.03766 | MobileVLM V2: Faster and Stronger Baseline for Vision Language Model | ['Xiangxiang Chu', 'Limeng Qiao', 'Xinyu Zhang', 'Shuang Xu', 'Fei Wei', 'Yang Yang', 'Xiaofei Sun', 'Yiming Hu', 'Xinyang Lin', 'Bo Zhang', 'Chunhua Shen'] | ['cs.CV', 'cs.AI'] | We introduce MobileVLM V2, a family of significantly improved vision language
models upon MobileVLM, which proves that a delicate orchestration of novel
architectural design, an improved training scheme tailored for mobile VLMs, and
rich high-quality dataset curation can substantially benefit VLMs' performance.
Specifi... | 2024-02-06T07:16:36Z | null | null | null | MobileVLM V2: Faster and Stronger Baseline for Vision Language Model | ['Xiangxiang Chu', 'Limeng Qiao', 'Xinyu Zhang', 'Shuang Xu', 'Fei Wei', 'Yang Yang', 'Xiaofei Sun', 'Yiming Hu', 'Xinyang Lin', 'Bo Zhang', 'Chunhua Shen'] | 2,024 | arXiv.org | 109 | 68 | ['Computer Science'] |
2,402.03774 | Learning a Decision Tree Algorithm with Transformers | ['Yufan Zhuang', 'Liyuan Liu', 'Chandan Singh', 'Jingbo Shang', 'Jianfeng Gao'] | ['cs.LG', 'cs.AI', 'cs.CL'] | Decision trees are renowned for their ability to achieve high predictive
performance while remaining interpretable, especially on tabular data.
Traditionally, they are constructed through recursive algorithms, where they
partition the data at every node in a tree. However, identifying a good
partition is challenging, a... | 2024-02-06T07:40:53Z | null | null | null | null | null | null | null | null | null | null |
2,402.03804 | ReLU$^2$ Wins: Discovering Efficient Activation Functions for Sparse
LLMs | ['Zhengyan Zhang', 'Yixin Song', 'Guanghui Yu', 'Xu Han', 'Yankai Lin', 'Chaojun Xiao', 'Chenyang Song', 'Zhiyuan Liu', 'Zeyu Mi', 'Maosong Sun'] | ['cs.LG', 'cs.AI'] | Sparse computation offers a compelling solution for the inference of Large
Language Models (LLMs) in low-resource scenarios by dynamically skipping the
computation of inactive neurons. While traditional approaches focus on
ReLU-based LLMs, leveraging zeros in activation values, we broaden the scope of
sparse LLMs beyon... | 2024-02-06T08:45:51Z | null | null | null | null | null | null | null | null | null | null |
2,402.03885 | MOMENT: A Family of Open Time-series Foundation Models | ['Mononito Goswami', 'Konrad Szafer', 'Arjun Choudhry', 'Yifu Cai', 'Shuo Li', 'Artur Dubrawski'] | ['cs.LG', 'cs.AI'] | We introduce MOMENT, a family of open-source foundation models for
general-purpose time series analysis. Pre-training large models on time series
data is challenging due to (1) the absence of a large and cohesive public time
series repository, and (2) diverse time series characteristics which make
multi-dataset trainin... | 2024-02-06T10:48:46Z | Accepted at ICML'24. This is a revision. See changelog in the
Appendix | null | null | null | null | null | null | null | null | null |
2,402.04249 | HarmBench: A Standardized Evaluation Framework for Automated Red Teaming
and Robust Refusal | ['Mantas Mazeika', 'Long Phan', 'Xuwang Yin', 'Andy Zou', 'Zifan Wang', 'Norman Mu', 'Elham Sakhaee', 'Nathaniel Li', 'Steven Basart', 'Bo Li', 'David Forsyth', 'Dan Hendrycks'] | ['cs.LG', 'cs.AI', 'cs.CL', 'cs.CV'] | Automated red teaming holds substantial promise for uncovering and mitigating
the risks associated with the malicious use of large language models (LLMs),
yet the field lacks a standardized evaluation framework to rigorously assess
new methods. To address this issue, we introduce HarmBench, a standardized
evaluation fr... | 2024-02-06T18:59:08Z | Website: https://www.harmbench.org | null | null | HarmBench: A Standardized Evaluation Framework for Automated Red Teaming and Robust Refusal | ['Mantas Mazeika', 'Long Phan', 'Xuwang Yin', 'Andy Zou', 'Zifan Wang', 'Norman Mu', 'Elham Sakhaee', 'Nathaniel Li', 'Steven Basart', 'Bo Li', 'David Forsyth', 'Dan Hendrycks'] | 2,024 | International Conference on Machine Learning | 419 | 107 | ['Computer Science'] |
2,402.04252 | EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters | ['Quan Sun', 'Jinsheng Wang', 'Qiying Yu', 'Yufeng Cui', 'Fan Zhang', 'Xiaosong Zhang', 'Xinlong Wang'] | ['cs.CV'] | Scaling up contrastive language-image pretraining (CLIP) is critical for
empowering both vision and multimodal models. We present EVA-CLIP-18B, the
largest and most powerful open-source CLIP model to date, with 18-billion
parameters. With only 6-billion training samples seen, EVA-CLIP-18B achieves an
exceptional 80.7% ... | 2024-02-06T18:59:48Z | null | null | null | null | null | null | null | null | null | null |
2,402.04324 | ConsistI2V: Enhancing Visual Consistency for Image-to-Video Generation | ['Weiming Ren', 'Huan Yang', 'Ge Zhang', 'Cong Wei', 'Xinrun Du', 'Wenhao Huang', 'Wenhu Chen'] | ['cs.CV'] | Image-to-video (I2V) generation aims to use the initial frame (alongside a
text prompt) to create a video sequence. A grand challenge in I2V generation is
to maintain visual consistency throughout the video: existing methods often
struggle to preserve the integrity of the subject, background, and style from
the first f... | 2024-02-06T19:08:18Z | Project Page: https://tiger-ai-lab.github.io/ConsistI2V/ | null | null | ConsistI2V: Enhancing Visual Consistency for Image-to-Video Generation | ['Weiming Ren', 'Harry Yang', 'Ge Zhang', 'Cong Wei', 'Xinrun Du', 'Stephen W. Huang', 'Wenhu Chen'] | 2,024 | Trans. Mach. Learn. Res. | 66 | 73 | ['Computer Science'] |
2,402.04379 | Fine-Tuned Language Models Generate Stable Inorganic Materials as Text | ['Nate Gruver', 'Anuroop Sriram', 'Andrea Madotto', 'Andrew Gordon Wilson', 'C. Lawrence Zitnick', 'Zachary Ulissi'] | ['cs.LG', 'cond-mat.mtrl-sci'] | We propose fine-tuning large language models for generation of stable
materials. While unorthodox, fine-tuning large language models on text-encoded
atomistic data is simple to implement yet reliable, with around 90% of sampled
structures obeying physical constraints on atom positions and charges. Using
energy above hu... | 2024-02-06T20:35:28Z | ICLR 2024. Code available at:
https://github.com/facebookresearch/crystal-llm | null | null | Fine-Tuned Language Models Generate Stable Inorganic Materials as Text | ['Nate Gruver', 'Anuroop Sriram', 'Andrea Madotto', 'A. Wilson', 'C. L. Zitnick', 'Zachary W. Ulissi', 'Meta Fair'] | 2,024 | International Conference on Learning Representations | 67 | 41 | ['Computer Science', 'Physics'] |
2,402.04588 | UltraLink: An Open-Source Knowledge-Enhanced Multilingual Supervised
Fine-tuning Dataset | ['Haoyu Wang', 'Shuo Wang', 'Yukun Yan', 'Xujia Wang', 'Zhiyu Yang', 'Yuzhuang Xu', 'Zhenghao Liu', 'Liner Yang', 'Ning Ding', 'Xu Han', 'Zhiyuan Liu', 'Maosong Sun'] | ['cs.CL'] | Open-source large language models (LLMs) have gained significant strength
across diverse fields. Nevertheless, the majority of studies primarily
concentrate on English, with only limited exploration into the realm of
multilingual abilities. In this work, we therefore construct an open-source
multilingual supervised fin... | 2024-02-07T05:05:53Z | Work in Progress | null | null | UltraLink: An Open-Source Knowledge-Enhanced Multilingual Supervised Fine-tuning Dataset | ['Haoyu Wang', 'Shuo Wang', 'Yukun Yan', 'Xujia Wang', 'Zhiyu Yang', 'Yuzhuang Xu', 'Zhenghao Liu', 'Ning Ding', 'Xu Han', 'Zhiyuan Liu', 'Maosong Sun'] | 2,024 | Annual Meeting of the Association for Computational Linguistics | 0 | 21 | ['Computer Science'] |
2,402.04624 | MEMORYLLM: Towards Self-Updatable Large Language Models | ['Yu Wang', 'Yifan Gao', 'Xiusi Chen', 'Haoming Jiang', 'Shiyang Li', 'Jingfeng Yang', 'Qingyu Yin', 'Zheng Li', 'Xian Li', 'Bing Yin', 'Jingbo Shang', 'Julian McAuley'] | ['cs.CL'] | Existing Large Language Models (LLMs) usually remain static after deployment,
which might make it hard to inject new knowledge into the model. We aim to
build models containing a considerable portion of self-updatable parameters,
enabling the model to integrate new knowledge effectively and efficiently. To
this end, we... | 2024-02-07T07:14:11Z | 13 pages, 9 figures | null | null | null | null | null | null | null | null | null |
2,402.04717 | InstructScene: Instruction-Driven 3D Indoor Scene Synthesis with
Semantic Graph Prior | ['Chenguo Lin', 'Yadong Mu'] | ['cs.CV'] | Comprehending natural language instructions is a charming property for 3D
indoor scene synthesis systems. Existing methods directly model object joint
distributions and express object relations implicitly within a scene, thereby
hindering the controllability of generation. We introduce InstructScene, a
novel generative... | 2024-02-07T10:09:00Z | Accepted by ICLR 2024 for spotlight presentation; Project page:
https://chenguolin.github.io/projects/InstructScene | null | null | InstructScene: Instruction-Driven 3D Indoor Scene Synthesis with Semantic Graph Prior | ['Chenguo Lin', 'Yadong Mu'] | 2,024 | International Conference on Learning Representations | 40 | 83 | ['Computer Science'] |
2,402.04792 | Direct Language Model Alignment from Online AI Feedback | ['Shangmin Guo', 'Biao Zhang', 'Tianlin Liu', 'Tianqi Liu', 'Misha Khalman', 'Felipe Llinares', 'Alexandre Rame', 'Thomas Mesnard', 'Yao Zhao', 'Bilal Piot', 'Johan Ferret', 'Mathieu Blondel'] | ['cs.AI', 'cs.CL', 'cs.HC'] | Direct alignment from preferences (DAP) methods, such as DPO, have recently
emerged as efficient alternatives to reinforcement learning from human feedback
(RLHF), that do not require a separate reward model. However, the preference
datasets used in DAP methods are usually collected ahead of training and never
updated,... | 2024-02-07T12:31:13Z | 18 pages, 9 figures, 4 tables | null | null | null | null | null | null | null | null | null |
2,402.04841 | Data-efficient Large Vision Models through Sequential Autoregression | ['Jianyuan Guo', 'Zhiwei Hao', 'Chengcheng Wang', 'Yehui Tang', 'Han Wu', 'Han Hu', 'Kai Han', 'Chang Xu'] | ['cs.CV'] | Training general-purpose vision models on purely sequential visual data,
eschewing linguistic inputs, has heralded a new frontier in visual
understanding. These models are intended to not only comprehend but also
seamlessly transit to out-of-domain tasks. However, current endeavors are
hamstrung by an over-reliance on ... | 2024-02-07T13:41:53Z | 15 pages | ICML 2024 | null | null | null | null | null | null | null | null |
2,402.04914 | Personalized Text Generation with Fine-Grained Linguistic Control | ['Bashar Alhafni', 'Vivek Kulkarni', 'Dhruv Kumar', 'Vipul Raheja'] | ['cs.CL'] | As the text generation capabilities of large language models become
increasingly prominent, recent studies have focused on controlling particular
aspects of the generated text to make it more personalized. However, most
research on controllable text generation focuses on controlling the content or
modeling specific hig... | 2024-02-07T14:41:08Z | null | null | null | null | null | null | null | null | null | null |
2,402.05 | Pedagogical Alignment of Large Language Models | ['Shashank Sonkar', 'Kangqi Ni', 'Sapana Chaudhary', 'Richard G. Baraniuk'] | ['cs.CL'] | Large Language Models (LLMs), when used in educational settings without
pedagogical fine-tuning, often provide immediate answers rather than guiding
students through the problem-solving process. This approach falls short of
pedagogically best practices and limits their effectiveness as educational
tools. We term the ob... | 2024-02-07T16:15:59Z | Accepted at EMNLP 2024 Findings Track | null | null | null | null | null | null | null | null | null |
2,402.05008 | EfficientViT-SAM: Accelerated Segment Anything Model Without Accuracy
Loss | ['Zhuoyang Zhang', 'Han Cai', 'Song Han'] | ['cs.CV', 'cs.AI', 'cs.LG'] | We present EfficientViT-SAM, a new family of accelerated segment anything
models. We retain SAM's lightweight prompt encoder and mask decoder while
replacing the heavy image encoder with EfficientViT. For the training, we begin
with the knowledge distillation from the SAM-ViT-H image encoder to
EfficientViT. Subsequent... | 2024-02-07T16:28:36Z | CVPR 2024 Workshop (Efficient Large Vision Models) | null | null | EfficientViT-SAM: Accelerated Segment Anything Model Without Accuracy Loss | ['Zhuoyang Zhang', 'Han Cai', 'Song Han'] | 2,024 | null | 3 | 24 | ['Computer Science'] |
2,402.05044 | SALAD-Bench: A Hierarchical and Comprehensive Safety Benchmark for Large
Language Models | ['Lijun Li', 'Bowen Dong', 'Ruohui Wang', 'Xuhao Hu', 'Wangmeng Zuo', 'Dahua Lin', 'Yu Qiao', 'Jing Shao'] | ['cs.CL', 'cs.AI', 'cs.CR', 'cs.LG'] | In the rapidly evolving landscape of Large Language Models (LLMs), ensuring
robust safety measures is paramount. To meet this crucial need, we propose
\emph{SALAD-Bench}, a safety benchmark specifically designed for evaluating
LLMs, attack, and defense methods. Distinguished by its breadth, SALAD-Bench
transcends conve... | 2024-02-07T17:33:54Z | Accepted at ACL 2024 Findings | null | null | SALAD-Bench: A Hierarchical and Comprehensive Safety Benchmark for Large Language Models | ['Lijun Li', 'Bowen Dong', 'Ruohui Wang', 'Xuhao Hu', 'Wangmeng Zuo', 'Dahua Lin', 'Yu Qiao', 'Jing Shao'] | 2,024 | Annual Meeting of the Association for Computational Linguistics | 106 | 59 | ['Computer Science'] |
2,402.05054 | LGM: Large Multi-View Gaussian Model for High-Resolution 3D Content
Creation | ['Jiaxiang Tang', 'Zhaoxi Chen', 'Xiaokang Chen', 'Tengfei Wang', 'Gang Zeng', 'Ziwei Liu'] | ['cs.CV'] | 3D content creation has achieved significant progress in terms of both
quality and speed. Although current feed-forward models can produce 3D objects
in seconds, their resolution is constrained by the intensive computation
required during training. In this paper, we introduce Large Multi-View Gaussian
Model (LGM), a no... | 2024-02-07T17:57:03Z | Project page: https://me.kiui.moe/lgm/ | null | null | null | null | null | null | null | null | null |
2,402.0512 | More Agents Is All You Need | ['Junyou Li', 'Qin Zhang', 'Yangbin Yu', 'Qiang Fu', 'Deheng Ye'] | ['cs.CL', 'cs.AI', 'cs.LG'] | We find that, simply via a sampling-and-voting method, the performance of
large language models (LLMs) scales with the number of agents instantiated.
Also, this method, termed as Agent Forest, is orthogonal to existing
complicated methods to further enhance LLMs, while the degree of enhancement is
correlated to the tas... | 2024-02-03T05:55:24Z | Published at Transactions on Machine Learning Research (TMLR) | null | null | More Agents Is All You Need | ['Junyou Li', 'Qin Zhang', 'Yangbin Yu', 'Qiang Fu', 'Deheng Ye'] | 2,024 | Trans. Mach. Learn. Res. | 73 | 40 | ['Computer Science'] |
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