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2,407.04379 | A Mapping Strategy for Interacting with Latent Audio Synthesis Using
Artistic Materials | ['Shuoyang Zheng', 'Anna Xambó Sedó', 'Nick Bryan-Kinns'] | ['cs.SD', 'cs.HC', 'eess.AS'] | This paper presents a mapping strategy for interacting with the latent spaces
of generative AI models. Our approach involves using unsupervised feature
learning to encode a human control space and mapping it to an audio synthesis
model's latent space. To demonstrate how this mapping strategy can turn
high-dimensional s... | 2024-07-05T09:32:44Z | null | null | null | null | null | null | null | null | null | null |
2,407.044 | Hard-Attention Gates with Gradient Routing for Endoscopic Image
Computing | ['Giorgio Roffo', 'Carlo Biffi', 'Pietro Salvagnini', 'Andrea Cherubini'] | ['eess.IV', 'cs.CV', 'cs.LG'] | To address overfitting and enhance model generalization in
gastroenterological polyp size assessment, our study introduces
Feature-Selection Gates (FSG) or Hard-Attention Gates (HAG) alongside Gradient
Routing (GR) for dynamic feature selection. This technique aims to boost
Convolutional Neural Networks (CNNs) and Visi... | 2024-07-05T10:20:24Z | Attention Gates, Hard-Attention Gates, Gradient Routing, Feature
Selection Gates, Endoscopy, Medical Image Processing, Computer Vision | In Proceedings of the 27th International Conference on Medical
Image Computing and Computer-Assisted Intervention (MICCAI 2024), 2024 | null | null | null | null | null | null | null | null |
2,407.0442 | cosmosage: A Natural-Language Assistant for Cosmologists | ['Tijmen de Haan'] | ['astro-ph.IM', 'astro-ph.CO'] | cosmosage is a natural-language assistant intended for a wide audience, from
laypersons interested in cosmology to students, teachers, and professional
cosmologists. cosmosage provides a novel way to access knowledge and reason
about cosmology. Leveraging the power of advanced large language models (LLMs),
cosmosage ha... | 2024-07-05T11:10:53Z | null | Astronomy and Computing, Volume 51, 2025, 100934, ISSN 2213-1337 | 10.1016/j.ascom.2025.100934 | null | null | null | null | null | null | null |
2,407.04538 | PDiscoFormer: Relaxing Part Discovery Constraints with Vision
Transformers | ['Ananthu Aniraj', 'Cassio F. Dantas', 'Dino Ienco', 'Diego Marcos'] | ['cs.CV', 'cs.AI', 'cs.LG'] | Computer vision methods that explicitly detect object parts and reason on
them are a step towards inherently interpretable models. Existing approaches
that perform part discovery driven by a fine-grained classification task make
very restrictive assumptions on the geometric properties of the discovered
parts; they shou... | 2024-07-05T14:24:37Z | Accepted as a main conference paper at the European Conference of
Computer Vision (ECCV) 2024 | null | null | null | null | null | null | null | null | null |
2,407.04543 | Strengthening Structural Inductive Biases by Pre-training to Perform
Syntactic Transformations | ['Matthias Lindemann', 'Alexander Koller', 'Ivan Titov'] | ['cs.CL'] | Models need appropriate inductive biases to effectively learn from small
amounts of data and generalize systematically outside of the training
distribution. While Transformers are highly versatile and powerful, they can
still benefit from enhanced structural inductive biases for seq2seq tasks,
especially those involvin... | 2024-07-05T14:29:44Z | null | null | null | Strengthening Structural Inductive Biases by Pre-training to Perform Syntactic Transformations | ['Matthias Lindemann', 'Alexander Koller', 'Ivan Titov'] | 2,024 | Conference on Empirical Methods in Natural Language Processing | 4 | 55 | ['Computer Science'] |
2,407.04604 | PartCraft: Crafting Creative Objects by Parts | ['Kam Woh Ng', 'Xiatian Zhu', 'Yi-Zhe Song', 'Tao Xiang'] | ['cs.CV'] | This paper propels creative control in generative visual AI by allowing users
to "select". Departing from traditional text or sketch-based methods, we for
the first time allow users to choose visual concepts by parts for their
creative endeavors. The outcome is fine-grained generation that precisely
captures selected v... | 2024-07-05T15:53:04Z | ECCV 2024. arXiv admin note: substantial text overlap with
arXiv:2311.15477 | null | null | null | null | null | null | null | null | null |
2,407.04619 | CountGD: Multi-Modal Open-World Counting | ['Niki Amini-Naieni', 'Tengda Han', 'Andrew Zisserman'] | ['cs.CV'] | The goal of this paper is to improve the generality and accuracy of
open-vocabulary object counting in images. To improve the generality, we
repurpose an open-vocabulary detection foundation model (GroundingDINO) for the
counting task, and also extend its capabilities by introducing modules to
enable specifying the tar... | 2024-07-05T16:20:48Z | NeurIPS 2024 | null | null | null | null | null | null | null | null | null |
2,407.04621 | OneRestore: A Universal Restoration Framework for Composite Degradation | ['Yu Guo', 'Yuan Gao', 'Yuxu Lu', 'Huilin Zhu', 'Ryan Wen Liu', 'Shengfeng He'] | ['cs.CV'] | In real-world scenarios, image impairments often manifest as composite
degradations, presenting a complex interplay of elements such as low light,
haze, rain, and snow. Despite this reality, existing restoration methods
typically target isolated degradation types, thereby falling short in
environments where multiple de... | 2024-07-05T16:27:00Z | null | null | null | OneRestore: A Universal Restoration Framework for Composite Degradation | ['Yu Guo', 'Yuan Gao', 'Yuxu Lu', 'Huilin Zhu', 'Ryan Wen Liu', 'Shengfeng He'] | 2,024 | European Conference on Computer Vision | 33 | 100 | ['Computer Science'] |
2,407.04693 | ANAH-v2: Scaling Analytical Hallucination Annotation of Large Language
Models | ['Yuzhe Gu', 'Ziwei Ji', 'Wenwei Zhang', 'Chengqi Lyu', 'Dahua Lin', 'Kai Chen'] | ['cs.CL', 'cs.AI'] | Large language models (LLMs) exhibit hallucinations in long-form
question-answering tasks across various domains and wide applications. Current
hallucination detection and mitigation datasets are limited in domains and
sizes, which struggle to scale due to prohibitive labor costs and insufficient
reliability of existin... | 2024-07-05T17:56:38Z | Accepted by NeurIPS 2024. Dataset, code, and model are released at
https://github.com/open-compass/ANAH | null | null | ANAH-v2: Scaling Analytical Hallucination Annotation of Large Language Models | ['Yuzhe Gu', 'Ziwei Ji', 'Wenwei Zhang', 'Chengqi Lyu', 'Dahua Lin', 'Kai Chen'] | 2,024 | Neural Information Processing Systems | 5 | 71 | ['Computer Science'] |
2,407.04822 | YourMT3+: Multi-instrument Music Transcription with Enhanced Transformer
Architectures and Cross-dataset Stem Augmentation | ['Sungkyun Chang', 'Emmanouil Benetos', 'Holger Kirchhoff', 'Simon Dixon'] | ['eess.AS', 'cs.LG', 'cs.SD'] | Multi-instrument music transcription aims to convert polyphonic music
recordings into musical scores assigned to each instrument. This task is
challenging for modeling as it requires simultaneously identifying multiple
instruments and transcribing their pitch and precise timing, and the lack of
fully annotated data add... | 2024-07-05T19:18:33Z | Accepted at IEEE International Workshop on Machine Learning for
Signal Processing (MLSP) 2024, London | null | null | null | null | null | null | null | null | null |
2,407.04842 | MJ-Bench: Is Your Multimodal Reward Model Really a Good Judge for
Text-to-Image Generation? | ['Zhaorun Chen', 'Yichao Du', 'Zichen Wen', 'Yiyang Zhou', 'Chenhang Cui', 'Zhenzhen Weng', 'Haoqin Tu', 'Chaoqi Wang', 'Zhengwei Tong', 'Qinglan Huang', 'Canyu Chen', 'Qinghao Ye', 'Zhihong Zhu', 'Yuqing Zhang', 'Jiawei Zhou', 'Zhuokai Zhao', 'Rafael Rafailov', 'Chelsea Finn', 'Huaxiu Yao'] | ['cs.CV', 'cs.CL', 'cs.LG'] | While text-to-image models like DALLE-3 and Stable Diffusion are rapidly
proliferating, they often encounter challenges such as hallucination, bias, and
the production of unsafe, low-quality output. To effectively address these
issues, it is crucial to align these models with desired behaviors based on
feedback from a ... | 2024-07-05T20:03:16Z | 42 pages, 13 figures, 33 tables | null | null | MJ-Bench: Is Your Multimodal Reward Model Really a Good Judge for Text-to-Image Generation? | ['Zhaorun Chen', 'Yichao Du', 'Zichen Wen', 'Yiyang Zhou', 'Chenhang Cui', 'Zhenzhen Weng', 'Haoqin Tu', 'Chaoqi Wang', 'Zhengwei Tong', 'Qinglan Huang', 'Canyu Chen', 'Qinghao Ye', 'Zhihong Zhu', 'Yuqing Zhang', 'Jiawei Zhou', 'Zhuokai Zhao', 'Rafael Rafailov', 'Chelsea Finn', 'Huaxiu Yao'] | 2,024 | arXiv.org | 35 | 97 | ['Computer Science'] |
2,407.04923 | OmChat: A Recipe to Train Multimodal Language Models with Strong Long
Context and Video Understanding | ['Tiancheng Zhao', 'Qianqian Zhang', 'Kyusong Lee', 'Peng Liu', 'Lu Zhang', 'Chunxin Fang', 'Jiajia Liao', 'Kelei Jiang', 'Yibo Ma', 'Ruochen Xu'] | ['cs.CV', 'cs.CL'] | We introduce OmChat, a model designed to excel in handling long contexts and
video understanding tasks. OmChat's new architecture standardizes how different
visual inputs are processed, making it more efficient and adaptable. It uses a
dynamic vision encoding process to effectively handle images of various
resolutions,... | 2024-07-06T02:16:10Z | 14 pages | null | null | null | null | null | null | null | null | null |
2,407.04948 | Zero-shot Object Counting with Good Exemplars | ['Huilin Zhu', 'Jingling Yuan', 'Zhengwei Yang', 'Yu Guo', 'Zheng Wang', 'Xian Zhong', 'Shengfeng He'] | ['cs.CV'] | Zero-shot object counting (ZOC) aims to enumerate objects in images using
only the names of object classes during testing, without the need for manual
annotations. However, a critical challenge in current ZOC methods lies in their
inability to identify high-quality exemplars effectively. This deficiency
hampers scalabi... | 2024-07-06T03:37:22Z | null | null | null | Zero-shot Object Counting with Good Exemplars | ['Huilin Zhu', 'Jingling Yuan', 'Zhengwei Yang', 'Yu Guo', 'Zheng Wang', 'Xian Zhong', 'Shengfeng He'] | 2,024 | European Conference on Computer Vision | 10 | 48 | ['Computer Science'] |
2,407.05015 | How do you know that? Teaching Generative Language Models to Reference
Answers to Biomedical Questions | ['Bojana Bašaragin', 'Adela Ljajić', 'Darija Medvecki', 'Lorenzo Cassano', 'Miloš Košprdić', 'Nikola Milošević'] | ['cs.CL', 'cs.AI'] | Large language models (LLMs) have recently become the leading source of
answers for users' questions online. Despite their ability to offer eloquent
answers, their accuracy and reliability can pose a significant challenge. This
is especially true for sensitive domains such as biomedicine, where there is a
higher need f... | 2024-07-06T09:10:05Z | Accepted at BioNLP Workshop 2024, colocated with ACL 2024 | null | null | null | null | null | null | null | null | null |
2,407.05282 | UltraEdit: Instruction-based Fine-Grained Image Editing at Scale | ['Haozhe Zhao', 'Xiaojian Ma', 'Liang Chen', 'Shuzheng Si', 'Rujie Wu', 'Kaikai An', 'Peiyu Yu', 'Minjia Zhang', 'Qing Li', 'Baobao Chang'] | ['cs.CV'] | This paper presents UltraEdit, a large-scale (approximately 4 million editing
samples), automatically generated dataset for instruction-based image editing.
Our key idea is to address the drawbacks in existing image editing datasets
like InstructPix2Pix and MagicBrush, and provide a systematic approach to
producing mas... | 2024-07-07T06:50:22Z | NeurIPS 2024 | null | null | null | null | null | null | null | null | null |
2,407.05361 | Emilia: An Extensive, Multilingual, and Diverse Speech Dataset for
Large-Scale Speech Generation | ['Haorui He', 'Zengqiang Shang', 'Chaoren Wang', 'Xuyuan Li', 'Yicheng Gu', 'Hua Hua', 'Liwei Liu', 'Chen Yang', 'Jiaqi Li', 'Peiyang Shi', 'Yuancheng Wang', 'Kai Chen', 'Pengyuan Zhang', 'Zhizheng Wu'] | ['eess.AS', 'cs.CL'] | Recent advancements in speech generation models have been significantly
driven by the use of large-scale training data. However, producing highly
spontaneous, human-like speech remains a challenge due to the scarcity of
large, diverse, and spontaneous speech datasets. In response, we introduce
Emilia, the first large-s... | 2024-07-07T13:24:54Z | Accepted in SLT 2024. Dataset available:
https://huggingface.co/datasets/amphion/Emilia-Dataset | null | null | null | null | null | null | null | null | null |
2,407.05407 | CosyVoice: A Scalable Multilingual Zero-shot Text-to-speech Synthesizer
based on Supervised Semantic Tokens | ['Zhihao Du', 'Qian Chen', 'Shiliang Zhang', 'Kai Hu', 'Heng Lu', 'Yexin Yang', 'Hangrui Hu', 'Siqi Zheng', 'Yue Gu', 'Ziyang Ma', 'Zhifu Gao', 'Zhijie Yan'] | ['cs.SD', 'cs.AI', 'eess.AS'] | Recent years have witnessed a trend that large language model (LLM) based
text-to-speech (TTS) emerges into the mainstream due to their high naturalness
and zero-shot capacity. In this paradigm, speech signals are discretized into
token sequences, which are modeled by an LLM with text as prompts and
reconstructed by a ... | 2024-07-07T15:16:19Z | work in progress. arXiv admin note: substantial text overlap with
arXiv:2407.04051 | null | null | null | null | null | null | null | null | null |
2,407.05449 | SmurfCat at PAN 2024 TextDetox: Alignment of Multilingual Transformers
for Text Detoxification | ['Elisei Rykov', 'Konstantin Zaytsev', 'Ivan Anisimov', 'Alexandr Voronin'] | ['cs.CL', 'cs.AI'] | This paper presents a solution for the Multilingual Text Detoxification task
in the PAN-2024 competition of the SmurfCat team. Using data augmentation
through machine translation and a special filtering procedure, we collected an
additional multilingual parallel dataset for text detoxification. Using the
obtained data,... | 2024-07-07T17:19:34Z | null | null | null | null | null | null | null | null | null | null |
2,407.0553 | This&That: Language-Gesture Controlled Video Generation for Robot
Planning | ['Boyang Wang', 'Nikhil Sridhar', 'Chao Feng', 'Mark Van der Merwe', 'Adam Fishman', 'Nima Fazeli', 'Jeong Joon Park'] | ['cs.RO', 'cs.AI', 'cs.CV'] | Clear, interpretable instructions are invaluable when attempting any complex
task. Good instructions help to clarify the task and even anticipate the steps
needed to solve it. In this work, we propose a robot learning framework for
communicating, planning, and executing a wide range of tasks, dubbed This&That.
This&Tha... | 2024-07-08T00:28:41Z | null | null | null | This&That: Language-Gesture Controlled Video Generation for Robot Planning | ['Boyang Wang', 'Nikhil Sridhar', 'Chao Feng', 'Mark Van der Merwe', 'Adam Fishman', 'Nima Fazeli', 'Jeong Joon Park'] | 2,024 | arXiv.org | 14 | 0 | ['Computer Science'] |
2,407.05562 | Focus on the Whole Character: Discriminative Character Modeling for
Scene Text Recognition | ['Bangbang Zhou', 'Yadong Qu', 'Zixiao Wang', 'Zicheng Li', 'Boqiang Zhang', 'Hongtao Xie'] | ['cs.CV'] | Recently, scene text recognition (STR) models have shown significant
performance improvements. However, existing models still encounter difficulties
in recognizing challenging texts that involve factors such as severely
distorted and perspective characters. These challenging texts mainly cause two
problems: (1) Large I... | 2024-07-08T02:33:29Z | Accepted to IJCAI2024 | null | null | null | null | null | null | null | null | null |
2,407.057 | InverseCoder: Self-improving Instruction-Tuned Code LLMs with
Inverse-Instruct | ['Yutong Wu', 'Di Huang', 'Wenxuan Shi', 'Wei Wang', 'Lingzhe Gao', 'Shihao Liu', 'Ziyuan Nan', 'Kaizhao Yuan', 'Rui Zhang', 'Xishan Zhang', 'Zidong Du', 'Qi Guo', 'Yewen Pu', 'Dawei Yin', 'Xing Hu', 'Yunji Chen'] | ['cs.CL', 'cs.AI', 'cs.SE'] | Recent advancements in open-source code large language models (LLMs) have
been driven by fine-tuning on the data generated from powerful closed-source
LLMs, which are expensive to obtain. This paper explores whether it is possible
to use a fine-tuned open-source model to generate additional data to augment
its instruct... | 2024-07-08T08:00:05Z | Accepted for publication at AAAI 2025. Extended version with full
appendix, 18 pages | null | null | null | null | null | null | null | null | null |
2,407.05878 | HiT-SR: Hierarchical Transformer for Efficient Image Super-Resolution | ['Xiang Zhang', 'Yulun Zhang', 'Fisher Yu'] | ['cs.CV'] | Transformers have exhibited promising performance in computer vision tasks
including image super-resolution (SR). However, popular transformer-based SR
methods often employ window self-attention with quadratic computational
complexity to window sizes, resulting in fixed small windows with limited
receptive fields. In t... | 2024-07-08T12:42:10Z | ECCV 2024 | null | null | HiT-SR: Hierarchical Transformer for Efficient Image Super-Resolution | ['Xiang Zhang', 'Yulun Zhang', 'Fisher Yu'] | 2,024 | European Conference on Computer Vision | 23 | 54 | ['Computer Science'] |
2,407.05965 | T2VSafetyBench: Evaluating the Safety of Text-to-Video Generative Models | ['Yibo Miao', 'Yifan Zhu', 'Yinpeng Dong', 'Lijia Yu', 'Jun Zhu', 'Xiao-Shan Gao'] | ['cs.CV', 'cs.AI', 'cs.CL', 'cs.CR', 'cs.LG'] | The recent development of Sora leads to a new era in text-to-video (T2V)
generation. Along with this comes the rising concern about its security risks.
The generated videos may contain illegal or unethical content, and there is a
lack of comprehensive quantitative understanding of their safety, posing a
challenge to th... | 2024-07-08T14:04:58Z | null | null | null | T2VSafetyBench: Evaluating the Safety of Text-to-Video Generative Models | ['Yibo Miao', 'Yifan Zhu', 'Yinpeng Dong', 'Lijia Yu', 'Jun Zhu', 'Xiao-Shan Gao'] | 2,024 | Neural Information Processing Systems | 20 | 68 | ['Computer Science'] |
2,407.05975 | LLaMAX: Scaling Linguistic Horizons of LLM by Enhancing Translation
Capabilities Beyond 100 Languages | ['Yinquan Lu', 'Wenhao Zhu', 'Lei Li', 'Yu Qiao', 'Fei Yuan'] | ['cs.CL', 'cs.AI'] | Large Language Models (LLMs) demonstrate remarkable translation capabilities
in high-resource language tasks, yet their performance in low-resource
languages is hindered by insufficient multilingual data during pre-training. To
address this, we conduct extensive multilingual continual pre-training on the
LLaMA series m... | 2024-07-08T14:18:28Z | EMNLP 2024 findings | null | null | LLaMAX: Scaling Linguistic Horizons of LLM by Enhancing Translation Capabilities Beyond 100 Languages | ['Yinquan Lu', 'Wenhao Zhu', 'Lei Li', 'Yu Qiao', 'Fei Yuan'] | 2,024 | Conference on Empirical Methods in Natural Language Processing | 32 | 70 | ['Computer Science'] |
2,407.06011 | Igea: a Decoder-Only Language Model for Biomedical Text Generation in
Italian | ['Tommaso Mario Buonocore', 'Simone Rancati', 'Enea Parimbelli'] | ['cs.CL', 'cs.AI', 'I.2.7; J.3'] | The development of domain-specific language models has significantly advanced
natural language processing applications in various specialized fields,
particularly in biomedicine. However, the focus has largely been on
English-language models, leaving a gap for less-resourced languages such as
Italian. This paper introd... | 2024-07-08T15:04:21Z | 6 pages, 1 figure, 3 tables | null | null | Igea: a Decoder-Only Language Model for Biomedical Text Generation in Italian | ['T. M. Buonocore', 'Simone Rancati', 'Enea Parimbelli'] | 2,024 | arXiv.org | 0 | 8 | ['Computer Science'] |
2,407.06048 | Vision-Braille: An End-to-End Tool for Chinese Braille Image-to-Text
Translation | ['Alan Wu', 'Ye Yuan', 'Ming Zhang'] | ['cs.CL', 'cs.CV'] | Visually impaired people are a large group who can only use braille for
reading and writing. However, the lack of special educational resources is the
bottleneck for educating them. Educational equity is a reflection of the level
of social civilization, cultural equality, and individual dignity. Facilitating
and improv... | 2024-07-08T15:51:37Z | This paper is submitted to NeurIPS 2024 High School Project Track | null | null | null | null | null | null | null | null | null |
2,407.06129 | Evaluating the Semantic Profiling Abilities of LLMs for Natural Language
Utterances in Data Visualization | ['Hannah K. Bako', 'Arshnoor Bhutani', 'Xinyi Liu', 'Kwesi A. Cobbina', 'Zhicheng Liu'] | ['cs.AI', 'cs.HC'] | Automatically generating data visualizations in response to human utterances
on datasets necessitates a deep semantic understanding of the data utterance,
including implicit and explicit references to data attributes, visualization
tasks, and necessary data preparation steps. Natural Language Interfaces (NLIs)
for data... | 2024-07-08T17:04:31Z | 5 pages, 4 figures, IEEE VIS short papers | null | null | Evaluating the Semantic Profiling Abilities of LLMs for Natural Language Utterances in Data Visualization | ['Hannah K. Bako', 'Arshnoor Bhutani', 'Xinyi Liu', 'K.A. Cobbina', 'Zhicheng Liu'] | 2,024 | Visual .. | 0 | 34 | ['Computer Science'] |
2,407.06135 | ANOLE: An Open, Autoregressive, Native Large Multimodal Models for
Interleaved Image-Text Generation | ['Ethan Chern', 'Jiadi Su', 'Yan Ma', 'Pengfei Liu'] | ['cs.CL', 'cs.AI', 'cs.CV'] | Previous open-source large multimodal models (LMMs) have faced several
limitations: (1) they often lack native integration, requiring adapters to
align visual representations with pre-trained large language models (LLMs); (2)
many are restricted to single-modal generation; (3) while some support
multimodal generation, ... | 2024-07-08T17:08:02Z | null | null | null | null | null | null | null | null | null | null |
2,407.06191 | Tailor3D: Customized 3D Assets Editing and Generation with Dual-Side
Images | ['Zhangyang Qi', 'Yunhan Yang', 'Mengchen Zhang', 'Long Xing', 'Xiaoyang Wu', 'Tong Wu', 'Dahua Lin', 'Xihui Liu', 'Jiaqi Wang', 'Hengshuang Zhao'] | ['cs.CV'] | Recent advances in 3D AIGC have shown promise in directly creating 3D objects
from text and images, offering significant cost savings in animation and
product design. However, detailed edit and customization of 3D assets remains a
long-standing challenge. Specifically, 3D Generation methods lack the ability
to follow f... | 2024-07-08T17:59:55Z | Project Page: https://tailor3d-2024.github.io/ | null | null | Tailor3D: Customized 3D Assets Editing and Generation with Dual-Side Images | ['Zhangyang Qi', 'Yu-nuo Yang', 'Mengchen Zhang', 'Long Xing', 'Xiaoyang Wu', 'Tong Wu', 'Dahua Lin', 'Xihui Liu', 'Jiaqi Wang', 'Hengshuang Zhao'] | 2,024 | arXiv.org | 10 | 66 | ['Computer Science'] |
2,407.06245 | ORAN-Bench-13K: An Open Source Benchmark for Assessing LLMs in Open
Radio Access Networks | ['Pranshav Gajjar', 'Vijay K. Shah'] | ['cs.NI', 'cs.AI', 'cs.CL', 'cs.LG'] | Large Language Models (LLMs) can revolutionize how we deploy and operate Open
Radio Access Networks (O-RAN) by enhancing network analytics, anomaly
detection, and code generation and significantly increasing the efficiency and
reliability of a plethora of O-RAN tasks. In this paper, we present
ORAN-Bench-13K, the first... | 2024-07-08T13:07:50Z | null | null | null | null | null | null | null | null | null | null |
2,407.06358 | MiraData: A Large-Scale Video Dataset with Long Durations and Structured
Captions | ['Xuan Ju', 'Yiming Gao', 'Zhaoyang Zhang', 'Ziyang Yuan', 'Xintao Wang', 'Ailing Zeng', 'Yu Xiong', 'Qiang Xu', 'Ying Shan'] | ['cs.CV'] | Sora's high-motion intensity and long consistent videos have significantly
impacted the field of video generation, attracting unprecedented attention.
However, existing publicly available datasets are inadequate for generating
Sora-like videos, as they mainly contain short videos with low motion intensity
and brief cap... | 2024-07-08T19:58:59Z | null | null | null | null | null | null | null | null | null | null |
2,407.06438 | SOLO: A Single Transformer for Scalable Vision-Language Modeling | ['Yangyi Chen', 'Xingyao Wang', 'Hao Peng', 'Heng Ji'] | ['cs.CV', 'cs.CL', 'cs.LG'] | We present SOLO, a single transformer for Scalable visiOn-Language mOdeling.
Current large vision-language models (LVLMs) such as LLaVA mostly employ
heterogeneous architectures that connect pre-trained visual encoders with large
language models (LLMs) to facilitate visual recognition and complex reasoning.
Although ac... | 2024-07-08T22:40:15Z | Accepted to TMLR | null | null | null | null | null | null | null | null | null |
2,407.06542 | LIONs: An Empirically Optimized Approach to Align Language Models | ['Xiao Yu', 'Qingyang Wu', 'Yu Li', 'Zhou Yu'] | ['cs.CL'] | Alignment is a crucial step to enhance the instruction-following and
conversational abilities of language models. Despite many recent work proposing
new algorithms, datasets, and training pipelines, there is a lack of
comprehensive studies measuring the impact of various design choices throughout
the whole training pro... | 2024-07-09T04:34:39Z | null | null | null | LIONs: An Empirically Optimized Approach to Align Language Models | ['Xiao Yu', 'Qingyang Wu', 'Yu Li', 'Zhou Yu'] | 2,024 | Conference on Empirical Methods in Natural Language Processing | 6 | 61 | ['Computer Science'] |
2,407.06551 | OffsetBias: Leveraging Debiased Data for Tuning Evaluators | ['Junsoo Park', 'Seungyeon Jwa', 'Meiying Ren', 'Daeyoung Kim', 'Sanghyuk Choi'] | ['cs.CL'] | Employing Large Language Models (LLMs) to assess the quality of generated
responses, such as prompting instruct-tuned models or fine-tuning judge models,
has become a widely adopted evaluation method. It is also known that such
evaluators are vulnerable to biases, such as favoring longer responses. While
it is importan... | 2024-07-09T05:16:22Z | EMNLP2024 Findings | null | null | OffsetBias: Leveraging Debiased Data for Tuning Evaluators | ['Junsoo Park', 'Seungyeon Jwa', 'Meiying Ren', 'Daeyoung Kim', 'Sanghyuk Choi'] | 2,024 | Conference on Empirical Methods in Natural Language Processing | 43 | 35 | ['Computer Science'] |
2,407.06597 | TVR-Ranking: A Dataset for Ranked Video Moment Retrieval with Imprecise
Queries | ['Renjie Liang', 'Li Li', 'Chongzhi Zhang', 'Jing Wang', 'Xizhou Zhu', 'Aixin Sun'] | ['cs.AI'] | In this paper, we propose the task of \textit{Ranked Video Moment Retrieval}
(RVMR) to locate a ranked list of matching moments from a collection of videos,
through queries in natural language. Although a few related tasks have been
proposed and studied by CV, NLP, and IR communities, RVMR is the task that best
reflect... | 2024-07-09T06:57:30Z | null | null | null | TVR-Ranking: A Dataset for Ranked Video Moment Retrieval with Imprecise Queries | ['Renjie Liang', 'Li Li', 'Chongzhi Zhang', 'Jing Wang', 'Xizhou Zhu', 'Aixin Sun'] | 2,024 | arXiv.org | 1 | 0 | ['Computer Science'] |
2,407.06723 | Graph-Based Captioning: Enhancing Visual Descriptions by Interconnecting
Region Captions | ['Yu-Guan Hsieh', 'Cheng-Yu Hsieh', 'Shih-Ying Yeh', 'Louis Béthune', 'Hadi Pour Ansari', 'Pavan Kumar Anasosalu Vasu', 'Chun-Liang Li', 'Ranjay Krishna', 'Oncel Tuzel', 'Marco Cuturi'] | ['cs.CV', 'cs.AI', 'cs.LG'] | Humans describe complex scenes with compositionality, using simple text
descriptions enriched with links and relationships. While vision-language
research has aimed to develop models with compositional understanding
capabilities, this is not reflected yet in existing datasets which, for the
most part, still use plain t... | 2024-07-09T09:55:04Z | 59 pages, 42 figures | null | null | Graph-Based Captioning: Enhancing Visual Descriptions by Interconnecting Region Captions | ['Yu-Guan Hsieh', 'Cheng-Yu Hsieh', 'Shih-Ying Yeh', "Louis B'ethune", 'Hadi Pour Ansari', 'Pavan Kumar Anasosalu Vasu', 'Chun-Liang Li', 'Ranjay Krishna', 'Oncel Tuzel', 'Marco Cuturi'] | 2,024 | arXiv.org | 5 | 76 | ['Computer Science'] |
2,407.0695 | Spanish TrOCR: Leveraging Transfer Learning for Language Adaptation | ['Filipe Lauar', 'Valentin Laurent'] | ['cs.AI', 'cs.CL'] | This study explores the transfer learning capabilities of the TrOCR
architecture to Spanish. TrOCR is a transformer-based Optical Character
Recognition (OCR) model renowned for its state-of-the-art performance in
English benchmarks. Inspired by Li et al. assertion regarding its adaptability
to multilingual text recogni... | 2024-07-09T15:31:41Z | 10 pages, 5 figures | null | null | null | null | null | null | null | null | null |
2,407.0708 | Adapting LLMs to Hebrew: Unveiling DictaLM 2.0 with Enhanced Vocabulary
and Instruction Capabilities | ['Shaltiel Shmidman', 'Avi Shmidman', 'Amir DN Cohen', 'Moshe Koppel'] | ['cs.CL'] | Training large language models (LLMs) in low-resource languages such as
Hebrew poses unique challenges. In this paper, we introduce DictaLM2.0 and
DictaLM2.0-Instruct, two LLMs derived from the Mistral model, trained on a
substantial corpus of approximately 200 billion tokens in both Hebrew and
English. Adapting a pre-... | 2024-07-09T17:51:37Z | null | null | null | Adapting LLMs to Hebrew: Unveiling DictaLM 2.0 with Enhanced Vocabulary and Instruction Capabilities | ['Shaltiel Shmidman', 'Avi Shmidman', 'Amir DN Cohen', 'Moshe Koppel'] | 2,024 | arXiv.org | 3 | 32 | ['Computer Science'] |
2,407.07093 | FBI-LLM: Scaling Up Fully Binarized LLMs from Scratch via Autoregressive
Distillation | ['Liqun Ma', 'Mingjie Sun', 'Zhiqiang Shen'] | ['cs.CL', 'cs.AI', 'cs.LG'] | This work presents a Fully BInarized Large Language Model (FBI-LLM),
demonstrating for the first time how to train a large-scale binary language
model from scratch (not the partial binary or ternary LLM like BitNet b1.58) to
match the performance of its full-precision counterparts (e.g., FP16 or BF16)
in transformer-ba... | 2024-07-09T17:59:48Z | Github at https://github.com/LiqunMa/FBI-LLM | null | null | null | null | null | null | null | null | null |
2,407.0758 | InstructLayout: Instruction-Driven 2D and 3D Layout Synthesis with
Semantic Graph Prior | ['Chenguo Lin', 'Yuchen Lin', 'Panwang Pan', 'Xuanyang Zhang', 'Yadong Mu'] | ['cs.CV'] | Comprehending natural language instructions is a charming property for both
2D and 3D layout synthesis systems. Existing methods implicitly model object
joint distributions and express object relations, hindering generation's
controllability. We introduce InstructLayout, a novel generative framework that
integrates a s... | 2024-07-10T12:13:39Z | This paper is an extension of ICLR 2024 "InstructScene:
Instruction-Driven 3D Indoor Scene Synthesis with Semantic Graph Prior".
arXiv admin note: substantial text overlap with arXiv:2402.04717 | null | null | null | null | null | null | null | null | null |
2,407.07726 | PaliGemma: A versatile 3B VLM for transfer | ['Lucas Beyer', 'Andreas Steiner', 'André Susano Pinto', 'Alexander Kolesnikov', 'Xiao Wang', 'Daniel Salz', 'Maxim Neumann', 'Ibrahim Alabdulmohsin', 'Michael Tschannen', 'Emanuele Bugliarello', 'Thomas Unterthiner', 'Daniel Keysers', 'Skanda Koppula', 'Fangyu Liu', 'Adam Grycner', 'Alexey Gritsenko', 'Neil Houlsby', ... | ['cs.CV', 'cs.AI', 'cs.CL', 'cs.LG'] | PaliGemma is an open Vision-Language Model (VLM) that is based on the
SigLIP-So400m vision encoder and the Gemma-2B language model. It is trained to
be a versatile and broadly knowledgeable base model that is effective to
transfer. It achieves strong performance on a wide variety of open-world tasks.
We evaluate PaliGe... | 2024-07-10T14:57:46Z | v2 adds Appendix H and I and a few citations | null | null | PaliGemma: A versatile 3B VLM for transfer | ['Lucas Beyer', 'A. Steiner', 'André Susano Pinto', 'Alexander Kolesnikov', 'Xiao Wang', 'Daniel M. Salz', 'Maxim Neumann', 'Ibrahim M. Alabdulmohsin', 'Michael Tschannen', 'Emanuele Bugliarello', 'Thomas Unterthiner', 'Daniel Keysers', 'Skanda Koppula', 'Fangyu Liu', 'Adam Grycner', 'A. Gritsenko', 'N. Houlsby', 'Mano... | 2,024 | arXiv.org | 212 | 0 | ['Computer Science'] |
2,407.07844 | OV-DINO: Unified Open-Vocabulary Detection with Language-Aware Selective
Fusion | ['Hao Wang', 'Pengzhen Ren', 'Zequn Jie', 'Xiao Dong', 'Chengjian Feng', 'Yinlong Qian', 'Lin Ma', 'Dongmei Jiang', 'Yaowei Wang', 'Xiangyuan Lan', 'Xiaodan Liang'] | ['cs.CV'] | Open-vocabulary detection is a challenging task due to the requirement of
detecting objects based on class names, including those not encountered during
training. Existing methods have shown strong zero-shot detection capabilities
through pre-training and pseudo-labeling on diverse large-scale datasets.
However, these ... | 2024-07-10T17:05:49Z | Technical Report | null | null | OV-DINO: Unified Open-Vocabulary Detection with Language-Aware Selective Fusion | ['Hao Wang', 'Pengzhen Ren', 'Zequn Jie', 'Xiao Dong', 'Chengjian Feng', 'Yinlong Qian', 'Lin Ma', 'Dongmei Jiang', 'Yaowei Wang', 'Xiangyuan Lan', 'Xiaodan Liang'] | 2,024 | arXiv.org | 6 | 64 | ['Computer Science'] |
2,407.07895 | LLaVA-NeXT-Interleave: Tackling Multi-image, Video, and 3D in Large
Multimodal Models | ['Feng Li', 'Renrui Zhang', 'Hao Zhang', 'Yuanhan Zhang', 'Bo Li', 'Wei Li', 'Zejun Ma', 'Chunyuan Li'] | ['cs.CV', 'cs.CL', 'cs.LG'] | Visual instruction tuning has made considerable strides in enhancing the
capabilities of Large Multimodal Models (LMMs). However, existing open LMMs
largely focus on single-image tasks, their applications to multi-image
scenarios remains less explored. Additionally, prior LMM research separately
tackles different scena... | 2024-07-10T17:59:43Z | Project Page:
https://llava-vl.github.io/blog/2024-06-16-llava-next-interleave/ | null | null | null | null | null | null | null | null | null |
2,407.08044 | RoLoRA: Fine-tuning Rotated Outlier-free LLMs for Effective
Weight-Activation Quantization | ['Xijie Huang', 'Zechun Liu', 'Shih-Yang Liu', 'Kwang-Ting Cheng'] | ['cs.CL', 'cs.AI', 'cs.LG'] | Low-Rank Adaptation (LoRA), as a representative Parameter-Efficient
Fine-Tuning (PEFT)method, significantly enhances the training efficiency by
updating only a small portion of the weights in Large Language Models (LLMs).
Recently, weight-only quantization techniques have also been applied to LoRA
methods to reduce the... | 2024-07-10T20:52:18Z | EMNLP 2024 Findings, Codes: https://github.com/HuangOwen/RoLoRA,
Models:
https://huggingface.co/collections/ScarletAce/rolora-66f5f228a90681c7c4512b28 | null | null | RoLoRA: Fine-tuning Rotated Outlier-free LLMs for Effective Weight-Activation Quantization | ['Xijie Huang', 'Zechun Liu', 'Shih-Yang Liu', 'Kwang-Ting Cheng'] | 2,024 | Conference on Empirical Methods in Natural Language Processing | 9 | 42 | ['Computer Science'] |
2,407.08083 | MambaVision: A Hybrid Mamba-Transformer Vision Backbone | ['Ali Hatamizadeh', 'Jan Kautz'] | ['cs.CV'] | We propose a novel hybrid Mamba-Transformer backbone, MambaVision,
specifically tailored for vision applications. Our core contribution includes
redesigning the Mamba formulation to enhance its capability for efficient
modeling of visual features. Through a comprehensive ablation study, we
demonstrate the feasibility o... | 2024-07-10T23:02:45Z | Accepted to CVPR'25 | null | null | null | null | null | null | null | null | null |
2,407.08136 | EchoMimic: Lifelike Audio-Driven Portrait Animations through Editable
Landmark Conditions | ['Zhiyuan Chen', 'Jiajiong Cao', 'Zhiquan Chen', 'Yuming Li', 'Chenguang Ma'] | ['cs.CV'] | The area of portrait image animation, propelled by audio input, has witnessed
notable progress in the generation of lifelike and dynamic portraits.
Conventional methods are limited to utilizing either audios or facial key
points to drive images into videos, while they can yield satisfactory results,
certain issues exis... | 2024-07-11T02:26:51Z | null | null | null | EchoMimic: Lifelike Audio-Driven Portrait Animations through Editable Landmark Conditions | ['Zhiyuan Chen', 'Jiajiong Cao', 'Zhiquan Chen', 'Yuming Li', 'Chenguang Ma'] | 2,024 | AAAI Conference on Artificial Intelligence | 69 | 27 | ['Computer Science'] |
2,407.08199 | SRPose: Two-view Relative Pose Estimation with Sparse Keypoints | ['Rui Yin', 'Yulun Zhang', 'Zherong Pan', 'Jianjun Zhu', 'Cheng Wang', 'Biao Jia'] | ['cs.CV'] | Two-view pose estimation is essential for map-free visual relocalization and
object pose tracking tasks. However, traditional matching methods suffer from
time-consuming robust estimators, while deep learning-based pose regressors
only cater to camera-to-world pose estimation, lacking generalizability to
different imag... | 2024-07-11T05:46:35Z | 30 pages, 11 figures, to be published in ECCV 2024 | null | null | null | null | null | null | null | null | null |
2,407.08275 | Beyond Benchmarks: Evaluating Embedding Model Similarity for Retrieval
Augmented Generation Systems | ['Laura Caspari', 'Kanishka Ghosh Dastidar', 'Saber Zerhoudi', 'Jelena Mitrovic', 'Michael Granitzer'] | ['cs.IR'] | The choice of embedding model is a crucial step in the design of Retrieval
Augmented Generation (RAG) systems. Given the sheer volume of available
options, identifying clusters of similar models streamlines this model
selection process. Relying solely on benchmark performance scores only allows
for a weak assessment of... | 2024-07-11T08:24:16Z | null | null | null | null | null | null | null | null | null | null |
2,407.0833 | HDT: Hierarchical Document Transformer | ['Haoyu He', 'Markus Flicke', 'Jan Buchmann', 'Iryna Gurevych', 'Andreas Geiger'] | ['cs.LG'] | In this paper, we propose the Hierarchical Document Transformer (HDT), a
novel sparse Transformer architecture tailored for structured hierarchical
documents. Such documents are extremely important in numerous domains,
including science, law or medicine. However, most existing solutions are
inefficient and fail to make... | 2024-07-11T09:28:04Z | null | null | null | HDT: Hierarchical Document Transformer | ['Haoyu He', 'Markus Flicke', 'Jan Buchmann', 'Iryna Gurevych', 'Andreas Geiger'] | 2,024 | arXiv.org | 0 | 68 | ['Computer Science'] |
2,407.0841 | Specialized curricula for training vision-language models in retinal
image analysis | ['Robbie Holland', 'Thomas R. P. Taylor', 'Christopher Holmes', 'Sophie Riedl', 'Julia Mai', 'Maria Patsiamanidi', 'Dimitra Mitsopoulou', 'Paul Hager', 'Philip Müller', 'Hendrik P. N. Scholl', 'Hrvoje Bogunović', 'Ursula Schmidt-Erfurth', 'Daniel Rueckert', 'Sobha Sivaprasad', 'Andrew J. Lotery', 'Martin J. Menten'] | ['cs.AI'] | Clinicians spend a significant amount of time reviewing medical images and
transcribing their findings regarding patient diagnosis, referral and treatment
in text form. Vision-language models (VLMs), which automatically interpret
images and summarize their findings as text, have enormous potential to
alleviate clinical... | 2024-07-11T11:31:48Z | Under review at npj Digital Medicine | null | null | null | null | null | null | null | null | null |
2,407.08447 | WildGaussians: 3D Gaussian Splatting in the Wild | ['Jonas Kulhanek', 'Songyou Peng', 'Zuzana Kukelova', 'Marc Pollefeys', 'Torsten Sattler'] | ['cs.CV'] | While the field of 3D scene reconstruction is dominated by NeRFs due to their
photorealistic quality, 3D Gaussian Splatting (3DGS) has recently emerged,
offering similar quality with real-time rendering speeds. However, both methods
primarily excel with well-controlled 3D scenes, while in-the-wild data -
characterized ... | 2024-07-11T12:41:32Z | NeurIPS 2024; Project page: https://wild-gaussians.github.io/ | null | null | null | null | null | null | null | null | null |
2,407.08488 | Lynx: An Open Source Hallucination Evaluation Model | ['Selvan Sunitha Ravi', 'Bartosz Mielczarek', 'Anand Kannappan', 'Douwe Kiela', 'Rebecca Qian'] | ['cs.AI', 'cs.CL'] | Retrieval Augmented Generation (RAG) techniques aim to mitigate
hallucinations in Large Language Models (LLMs). However, LLMs can still produce
information that is unsupported or contradictory to the retrieved contexts. We
introduce LYNX, a SOTA hallucination detection LLM that is capable of advanced
reasoning on chall... | 2024-07-11T13:22:17Z | null | null | null | Lynx: An Open Source Hallucination Evaluation Model | ['Selvan Sunitha Ravi', 'B. Mielczarek', 'Anand Kannappan', 'Douwe Kiela', 'Rebecca Qian'] | 2,024 | arXiv.org | 20 | 40 | ['Computer Science'] |
2,407.08515 | 15M Multimodal Facial Image-Text Dataset | ['Dawei Dai', 'YuTang Li', 'YingGe Liu', 'Mingming Jia', 'Zhang YuanHui', 'Guoyin Wang'] | ['cs.CV', 'cs.AI'] | Currently, image-text-driven multi-modal deep learning models have
demonstrated their outstanding potential in many fields. In practice, tasks
centered around facial images have broad application prospects. This paper
presents \textbf{FaceCaption-15M}, a large-scale, diverse, and high-quality
dataset of facial images a... | 2024-07-11T14:00:14Z | 15 pages, 8 figures | null | null | null | null | null | null | null | null | null |
2,407.08655 | SPOCKMIP: Segmentation of Vessels in MRAs with Enhanced Continuity using
Maximum Intensity Projection as Loss | ['Chethan Radhakrishna', 'Karthikesh Varma Chintalapati', 'Sri Chandana Hudukula Ram Kumar', 'Raviteja Sutrave', 'Hendrik Mattern', 'Oliver Speck', 'Andreas Nürnberger', 'Soumick Chatterjee'] | ['eess.IV', 'cs.AI', 'cs.LG', 'physics.med-ph'] | Identification of vessel structures of different sizes in biomedical images
is crucial in the diagnosis of many neurodegenerative diseases. However, the
sparsity of good-quality annotations of such images makes the task of vessel
segmentation challenging. Deep learning offers an efficient way to segment
vessels of diff... | 2024-07-11T16:39:24Z | null | null | null | null | null | null | null | null | null | null |
2,407.08683 | SEED-Story: Multimodal Long Story Generation with Large Language Model | ['Shuai Yang', 'Yuying Ge', 'Yang Li', 'Yukang Chen', 'Yixiao Ge', 'Ying Shan', 'Yingcong Chen'] | ['cs.CV'] | With the remarkable advancements in image generation and open-form text
generation, the creation of interleaved image-text content has become an
increasingly intriguing field. Multimodal story generation, characterized by
producing narrative texts and vivid images in an interleaved manner, has
emerged as a valuable and... | 2024-07-11T17:21:03Z | Our models, codes and datasets are released in
https://github.com/TencentARC/SEED-Story | null | null | SEED-Story: Multimodal Long Story Generation with Large Language Model | ['Shuai Yang', 'Yuying Ge', 'Yang Li', 'Yukang Chen', 'Yixiao Ge', 'Ying Shan', 'Yingcong Chen'] | 2,024 | arXiv.org | 32 | 53 | ['Computer Science'] |
2,407.08701 | Live2Diff: Live Stream Translation via Uni-directional Attention in
Video Diffusion Models | ['Zhening Xing', 'Gereon Fox', 'Yanhong Zeng', 'Xingang Pan', 'Mohamed Elgharib', 'Christian Theobalt', 'Kai Chen'] | ['cs.CV'] | Large Language Models have shown remarkable efficacy in generating streaming
data such as text and audio, thanks to their temporally uni-directional
attention mechanism, which models correlations between the current token and
previous tokens. However, video streaming remains much less explored, despite a
growing need f... | 2024-07-11T17:34:51Z | https://live2diff.github.io/ | null | null | null | null | null | null | null | null | null |
2,407.08737 | Video Diffusion Alignment via Reward Gradients | ['Mihir Prabhudesai', 'Russell Mendonca', 'Zheyang Qin', 'Katerina Fragkiadaki', 'Deepak Pathak'] | ['cs.CV', 'cs.AI', 'cs.LG', 'cs.RO'] | We have made significant progress towards building foundational video
diffusion models. As these models are trained using large-scale unsupervised
data, it has become crucial to adapt these models to specific downstream tasks.
Adapting these models via supervised fine-tuning requires collecting target
datasets of video... | 2024-07-11T17:59:45Z | Project Webpage: https://vader-vid.github.io; Code available at:
https://github.com/mihirp1998/VADER | null | null | null | null | null | null | null | null | null |
2,407.08819 | Rule-Based, Neural and LLM Back-Translation: Comparative Insights from a
Variant of Ladin | ['Samuel Frontull', 'Georg Moser'] | ['cs.CL'] | This paper explores the impact of different back-translation approaches on
machine translation for Ladin, specifically the Val Badia variant. Given the
limited amount of parallel data available for this language (only 18k
Ladin-Italian sentence pairs), we investigate the performance of a multilingual
neural machine tra... | 2024-07-11T19:05:43Z | Accepted to LoResMT 2024 (ACL workshop) | null | null | null | null | null | null | null | null | null |
2,407.09121 | Refuse Whenever You Feel Unsafe: Improving Safety in LLMs via Decoupled
Refusal Training | ['Youliang Yuan', 'Wenxiang Jiao', 'Wenxuan Wang', 'Jen-tse Huang', 'Jiahao Xu', 'Tian Liang', 'Pinjia He', 'Zhaopeng Tu'] | ['cs.CL', 'cs.AI'] | This study addresses a critical gap in safety tuning practices for Large
Language Models (LLMs) by identifying and tackling a refusal position bias
within safety tuning data, which compromises the models' ability to
appropriately refuse generating unsafe content. We introduce a novel approach,
Decoupled Refusal Trainin... | 2024-07-12T09:36:33Z | Accepted by ACL 2025 main | null | null | null | null | null | null | null | null | null |
2,407.09252 | Context Embeddings for Efficient Answer Generation in RAG | ['David Rau', 'Shuai Wang', 'Hervé Déjean', 'Stéphane Clinchant'] | ['cs.CL', 'cs.IR'] | Retrieval-Augmented Generation (RAG) allows overcoming the limited knowledge
of LLMs by extending the input with external information. As a consequence, the
contextual inputs to the model become much longer which slows down decoding
time directly translating to the time a user has to wait for an answer. We
address this... | 2024-07-12T13:30:44Z | 10 pages | WSDM 2025 | null | Context Embeddings for Efficient Answer Generation in RAG | ['David Rau', 'Shuai Wang', "Herv'e D'ejean", 'S. Clinchant'] | 2,024 | arXiv.org | 10 | 0 | ['Computer Science'] |
2,407.09276 | H2O-Danube3 Technical Report | ['Pascal Pfeiffer', 'Philipp Singer', 'Yauhen Babakhin', 'Gabor Fodor', 'Nischay Dhankhar', 'Sri Satish Ambati'] | ['cs.CL', 'cs.LG'] | We present H2O-Danube3, a series of small language models consisting of
H2O-Danube3-4B, trained on 6T tokens and H2O-Danube3-500M, trained on 4T
tokens. Our models are pre-trained on high quality Web data consisting of
primarily English tokens in three stages with different data mixes before final
supervised tuning for... | 2024-07-12T14:09:40Z | null | null | null | null | null | null | null | null | null | null |
2,407.09379 | FANet: Feature Amplification Network for Semantic Segmentation in
Cluttered Background | ['Muhammad Ali', 'Mamoona Javaid', 'Mubashir Noman', 'Mustansar Fiaz', 'Salman Khan'] | ['cs.CV'] | Existing deep learning approaches leave out the semantic cues that are
crucial in semantic segmentation present in complex scenarios including
cluttered backgrounds and translucent objects, etc. To handle these challenges,
we propose a feature amplification network (FANet) as a backbone network that
incorporates semant... | 2024-07-12T15:57:52Z | Accepted at ICIP 2024 | null | null | FANet: Feature Amplification Network for Semantic Segmentation in Cluttered Background | ['Muhammad Ali', 'Mamoona Javaid', 'Mubashir Noman', 'M. Fiaz', 'Salman H. Khan'] | 2,024 | International Conference on Information Photonics | 1 | 29 | ['Computer Science'] |
2,407.09533 | Video Occupancy Models | ['Manan Tomar', 'Philippe Hansen-Estruch', 'Philip Bachman', 'Alex Lamb', 'John Langford', 'Matthew E. Taylor', 'Sergey Levine'] | ['cs.CV', 'cs.AI'] | We introduce a new family of video prediction models designed to support
downstream control tasks. We call these models Video Occupancy models (VOCs).
VOCs operate in a compact latent space, thus avoiding the need to make
predictions about individual pixels. Unlike prior latent-space world models,
VOCs directly predict... | 2024-06-25T17:57:38Z | null | null | null | null | null | null | null | null | null | null |
2,407.09577 | FlashNorm: fast normalization for LLMs | ['Nils Graef', 'Andrew Wasielewski', 'Matthew Clapp'] | ['cs.LG'] | This paper presents FlashNorm, which is an exact but faster implementation of
RMSNorm followed by linear layers. RMSNorm is used by many LLMs such as Llama,
Mistral, and OpenELM. FlashNorm also speeds up Layer Normalization and its
recently proposed replacement Dynamic Tanh (DyT) arXiv:2503.10622. FlashNorm
also reduce... | 2024-07-12T00:37:55Z | 16 pages, 10 figures | null | null | null | null | null | null | null | null | null |
2,407.09756 | LLM-Collaboration on Automatic Science Journalism for the General
Audience | ['Gongyao Jiang', 'Xinran Shi', 'Qiong Luo'] | ['cs.CL'] | Science journalism reports current scientific discoveries to non-specialists,
aiming to enable public comprehension of the state of the art. However, this
task can be challenging as the audience often lacks specific knowledge about
the presented research. To address this challenge, we propose a framework that
integrate... | 2024-07-13T03:31:35Z | Under review | null | null | LLM-Collaboration on Automatic Science Journalism for the General Audience | ['Gongyao Jiang', 'Xinran Shi', 'Qiong Luo'] | 2,024 | arXiv.org | 3 | 37 | ['Computer Science'] |
2,407.09861 | A Systematic Survey of Natural Language Processing for the Greek
Language | ['Juli Bakagianni', 'Kanella Pouli', 'Maria Gavriilidou', 'John Pavlopoulos'] | ['cs.CL', 'cs.AI'] | Comprehensive monolingual Natural Language Processing (NLP) surveys are
essential for assessing language-specific challenges, resource availability,
and research gaps. However, existing surveys often lack standardized
methodologies, leading to selection bias and fragmented coverage of NLP tasks
and resources. This stud... | 2024-07-13T12:01:52Z | This version matches the paper published in Patterns (Cell Press).
The title has been updated to reflect the published version | null | null | A Systematic Survey of Natural Language Processing for the Greek Language | ['Juli Bakagianni', 'K. Pouli', 'M. Gavriilidou', 'John Pavlopoulos'] | 2,024 | null | 1 | 0 | ['Computer Science'] |
2,407.09887 | OptiBench Meets ReSocratic: Measure and Improve LLMs for Optimization
Modeling | ['Zhicheng Yang', 'Yiwei Wang', 'Yinya Huang', 'Zhijiang Guo', 'Wei Shi', 'Xiongwei Han', 'Liang Feng', 'Linqi Song', 'Xiaodan Liang', 'Jing Tang'] | ['cs.LG', 'math.OC'] | Large language models (LLMs) have exhibited their problem-solving abilities
in mathematical reasoning. Solving realistic optimization (OPT) problems in
application scenarios requires advanced and applied mathematics ability.
However, current OPT benchmarks that merely solve linear programming are far
from complex reali... | 2024-07-13T13:27:57Z | null | The Thirteenth International Conference on Learning
Representations, 2025 | null | OptiBench Meets ReSocratic: Measure and Improve LLMs for Optimization Modeling | ['Zhicheng YANG', 'Yinya Huang', 'Zhijiang Guo', 'Wei Shi', 'Liang Feng', 'Linqi Song', 'Yiwei Wang', 'Xiaodan Liang', 'Jing Tang'] | 2,024 | International Conference on Learning Representations | 5 | 51 | ['Computer Science', 'Mathematics'] |
2,407.09941 | Hydra: Bidirectional State Space Models Through Generalized Matrix
Mixers | ['Sukjun Hwang', 'Aakash Lahoti', 'Tri Dao', 'Albert Gu'] | ['cs.LG', 'cs.AI'] | A wide array of sequence models are built on a framework modeled after
Transformers, comprising alternating sequence mixer and channel mixer layers.
This paper studies a unifying matrix mixer view of sequence mixers that can be
conceptualized as a linear map on the input sequence. This framework
encompasses a broad ran... | 2024-07-13T16:34:18Z | null | null | null | null | null | null | null | null | null | null |
2,407.10032 | LeanQuant: Accurate and Scalable Large Language Model Quantization with
Loss-error-aware Grid | ['Tianyi Zhang', 'Anshumali Shrivastava'] | ['cs.LG'] | Large language models (LLMs) have shown immense potential across various
domains, but their high memory requirements and inference costs remain critical
challenges for deployment. Post-training quantization (PTQ) has emerged as a
promising technique to reduce memory requirements and decoding latency.
However, recent ac... | 2024-07-14T00:23:51Z | null | null | null | LeanQuant: Accurate and Scalable Large Language Model Quantization with Loss-error-aware Grid | ['Tianyi Zhang', 'Anshumali Shrivastava'] | 2,024 | International Conference on Learning Representations | 6 | 57 | ['Computer Science'] |
2,407.10086 | Rapid Biomedical Research Classification: The Pandemic PACT Advanced
Categorisation Engine | ['Omid Rohanian', 'Mohammadmahdi Nouriborji', 'Olena Seminog', 'Rodrigo Furst', 'Thomas Mendy', 'Shanthi Levanita', 'Zaharat Kadri-Alabi', 'Nusrat Jabin', 'Daniela Toale', 'Georgina Humphreys', 'Emilia Antonio', 'Adrian Bucher', 'Alice Norton', 'David A. Clifton'] | ['cs.CL', 'cs.AI', '68T50', 'I.2.7'] | This paper introduces the Pandemic PACT Advanced Categorisation Engine
(PPACE) along with its associated dataset. PPACE is a fine-tuned model
developed to automatically classify research abstracts from funded biomedical
projects according to WHO-aligned research priorities. This task is crucial for
monitoring research ... | 2024-07-14T05:22:53Z | null | null | null | Rapid Biomedical Research Classification: The Pandemic PACT Advanced Categorisation Engine | ['Omid Rohanian', 'Mohammadmahdi Nouriborji', 'Olena Seminog', 'Rodrigo Furst', 'Thomas Mendy', 'Shanthi Levanita', 'Zaharat Kadri-Alabi', 'Nusrat Jabin', 'Daniela Toale', 'Georgina Humphreys', 'E. Antonio', 'Adrian Bucher', 'Alice Norton', 'David A. Clifton'] | 2,024 | arXiv.org | 1 | 32 | ['Computer Science'] |
2,407.10172 | Restoring Images in Adverse Weather Conditions via Histogram Transformer | ['Shangquan Sun', 'Wenqi Ren', 'Xinwei Gao', 'Rui Wang', 'Xiaochun Cao'] | ['cs.CV'] | Transformer-based image restoration methods in adverse weather have achieved
significant progress. Most of them use self-attention along the channel
dimension or within spatially fixed-range blocks to reduce computational load.
However, such a compromise results in limitations in capturing long-range
spatial features. ... | 2024-07-14T11:59:22Z | 19 pages, 7 figures, 10MB | null | null | Restoring Images in Adverse Weather Conditions via Histogram Transformer | ['Shangquan Sun', 'Wenqi Ren', 'Xinwei Gao', 'Rui Wang', 'Xiaochun Cao'] | 2,024 | European Conference on Computer Vision | 39 | 98 | ['Computer Science'] |
2,407.10424 | CodeV: Empowering LLMs with HDL Generation through Multi-Level
Summarization | ['Yang Zhao', 'Di Huang', 'Chongxiao Li', 'Pengwei Jin', 'Muxin Song', 'Yinan Xu', 'Ziyuan Nan', 'Mingju Gao', 'Tianyun Ma', 'Lei Qi', 'Yansong Pan', 'Zhenxing Zhang', 'Rui Zhang', 'Xishan Zhang', 'Zidong Du', 'Qi Guo', 'Xing Hu'] | ['cs.PL', 'cs.AI'] | The design flow of processors, particularly in hardware description languages
(HDL) like Verilog and Chisel, is complex and costly. While recent advances in
large language models (LLMs) have significantly improved coding tasks in
software languages such as Python, their application in HDL generation remains
limited due... | 2024-07-15T03:57:20Z | 13 pages, 10 figures, journal | null | null | CodeV: Empowering LLMs with HDL Generation through Multi-Level Summarization | ['Yang Zhao', 'Di Huang', 'Chongxiao Li', 'Pengwei Jin', 'Ziyuan Nan', 'Tianyun Ma', 'Lei Qi', 'Yansong Pan', 'Zhenxing Zhang', 'Rui Zhang', 'Xishan Zhang', 'Zidong Du', 'Qi Guo', 'Xingui Hu', 'Yunji Chen'] | 2,024 | null | 20 | 49 | ['Computer Science'] |
2,407.10603 | Leave No Knowledge Behind During Knowledge Distillation: Towards
Practical and Effective Knowledge Distillation for Code-Switching ASR Using
Realistic Data | ['Liang-Hsuan Tseng', 'Zih-Ching Chen', 'Wei-Shun Chang', 'Cheng-Kuang Lee', 'Tsung-Ren Huang', 'Hung-yi Lee'] | ['eess.AS', 'cs.CL', 'cs.SD'] | Recent advances in automatic speech recognition (ASR) often rely on large
speech foundation models for generating high-quality transcriptions. However,
these models can be impractical due to limited computing resources. The
situation is even more severe in terms of more realistic or difficult
scenarios, such as code-sw... | 2024-07-15T10:25:14Z | null | null | null | null | null | null | null | null | null | null |
2,407.10666 | Flow Perturbation to Accelerate Unbiased Sampling of Boltzmann
distribution | ['Xin Peng', 'Ang Gao'] | ['stat.ML', 'cs.LG', 'physics.chem-ph'] | Flow-based generative models have been employed for sampling the Boltzmann
distribution, but their application to high-dimensional systems is hindered by
the significant computational cost of obtaining the Jacobian of the flow. To
overcome this challenge, we introduce the flow perturbation method, which
incorporates op... | 2024-07-15T12:29:17Z | null | null | null | null | null | null | null | null | null | null |
2,407.10671 | Qwen2 Technical Report | ['An Yang', 'Baosong Yang', 'Binyuan Hui', 'Bo Zheng', 'Bowen Yu', 'Chang Zhou', 'Chengpeng Li', 'Chengyuan Li', 'Dayiheng Liu', 'Fei Huang', 'Guanting Dong', 'Haoran Wei', 'Huan Lin', 'Jialong Tang', 'Jialin Wang', 'Jian Yang', 'Jianhong Tu', 'Jianwei Zhang', 'Jianxin Ma', 'Jianxin Yang', 'Jin Xu', 'Jingren Zhou', 'Ji... | ['cs.CL', 'cs.AI'] | This report introduces the Qwen2 series, the latest addition to our large
language models and large multimodal models. We release a comprehensive suite
of foundational and instruction-tuned language models, encompassing a parameter
range from 0.5 to 72 billion, featuring dense models and a Mixture-of-Experts
model. Qwe... | 2024-07-15T12:35:42Z | 26 pages, 1 figure | null | null | null | null | null | null | null | null | null |
2,407.10759 | Qwen2-Audio Technical Report | ['Yunfei Chu', 'Jin Xu', 'Qian Yang', 'Haojie Wei', 'Xipin Wei', 'Zhifang Guo', 'Yichong Leng', 'Yuanjun Lv', 'Jinzheng He', 'Junyang Lin', 'Chang Zhou', 'Jingren Zhou'] | ['eess.AS', 'cs.CL', 'cs.LG'] | We introduce the latest progress of Qwen-Audio, a large-scale audio-language
model called Qwen2-Audio, which is capable of accepting various audio signal
inputs and performing audio analysis or direct textual responses with regard to
speech instructions. In contrast to complex hierarchical tags, we have
simplified the ... | 2024-07-15T14:38:09Z | https://github.com/QwenLM/Qwen2-Audio. Checkpoints, codes and scripts
will be opensoursed soon | null | null | Qwen2-Audio Technical Report | ['Yunfei Chu', 'Jin Xu', 'Qian Yang', 'Haojie Wei', 'Xipin Wei', 'Zhifang Guo', 'Yichong Leng', 'Yuanjun Lv', 'Jinzheng He', 'Junyang Lin', 'Chang Zhou', 'Jingren Zhou'] | 2,024 | arXiv.org | 161 | 37 | ['Engineering', 'Computer Science'] |
2,407.10909 | FinDKG: Dynamic Knowledge Graphs with Large Language Models for
Detecting Global Trends in Financial Markets | ['Xiaohui Victor Li', 'Francesco Sanna Passino'] | ['q-fin.CP'] | Dynamic knowledge graphs (DKGs) are popular structures to express different
types of connections between objects over time. They can also serve as an
efficient mathematical tool to represent information extracted from complex
unstructured data sources, such as text or images. Within financial
applications, DKGs could b... | 2024-07-15T17:09:44Z | 9 pages | ICAIF '24: Proceedings of the 5th ACM International Conference on
AI in Finance, 573-581 (2024) | 10.1145/3677052.3698603 | FinDKG: Dynamic Knowledge Graphs with Large Language Models for Detecting Global Trends in Financial Markets | ['Xiaohui Victor Li', 'Francesco Sanna Passino'] | 2,024 | International Conference on AI in Finance | 7 | 46 | ['Economics', 'Computer Science'] |
2,407.10953 | MMM: Multilingual Mutual Reinforcement Effect Mix Datasets & Test with
Open-domain Information Extraction Large Language Models | ['Chengguang Gan', 'Sunbowen Lee', 'Qingyu Yin', 'Xinyang He', 'Hanjun Wei', 'Yunhao Liang', 'Younghun Lim', 'Shijian Wang', 'Hexiang Huang', 'Qinghao Zhang', 'Shiwen Ni', 'Tatsunori Mori'] | ['cs.CL'] | The Mutual Reinforcement Effect (MRE) represents a promising avenue in
information extraction and multitasking research. Nevertheless, its
applicability has been constrained due to the exclusive availability of MRE mix
datasets in Japanese, thereby limiting comprehensive exploration by the global
research community. To... | 2024-07-15T17:50:43Z | Under Review. 11 pages, 5 Figure | null | null | null | null | null | null | null | null | null |
2,407.10973 | Make-An-Agent: A Generalizable Policy Network Generator with
Behavior-Prompted Diffusion | ['Yongyuan Liang', 'Tingqiang Xu', 'Kaizhe Hu', 'Guangqi Jiang', 'Furong Huang', 'Huazhe Xu'] | ['cs.AI'] | Can we generate a control policy for an agent using just one demonstration of
desired behaviors as a prompt, as effortlessly as creating an image from a
textual description? In this paper, we present Make-An-Agent, a novel policy
parameter generator that leverages the power of conditional diffusion models
for behavior-... | 2024-07-15T17:59:57Z | Annual Conference on Neural Information Processing Systems 38 | null | null | null | null | null | null | null | null | null |
2,407.10995 | LionGuard: Building a Contextualized Moderation Classifier to Tackle
Localized Unsafe Content | ['Jessica Foo', 'Shaun Khoo'] | ['cs.CL', 'cs.AI'] | As large language models (LLMs) become increasingly prevalent in a wide
variety of applications, concerns about the safety of their outputs have become
more significant. Most efforts at safety-tuning or moderation today take on a
predominantly Western-centric view of safety, especially for toxic, hateful, or
violent sp... | 2024-06-24T14:05:56Z | Preprint | null | null | null | null | null | null | null | null | null |
2,407.11005 | RAGBench: Explainable Benchmark for Retrieval-Augmented Generation
Systems | ['Robert Friel', 'Masha Belyi', 'Atindriyo Sanyal'] | ['cs.CL', 'cs.AI'] | Retrieval-Augmented Generation (RAG) has become a standard architectural
pattern for incorporating domain-specific knowledge into user-facing chat
applications powered by Large Language Models (LLMs). RAG systems are
characterized by (1) a document retriever that queries a domain-specific corpus
for context information... | 2024-06-25T20:23:15Z | null | null | null | null | null | null | null | null | null | null |
2,407.11007 | Panacea: A foundation model for clinical trial search, summarization,
design, and recruitment | ['Jiacheng Lin', 'Hanwen Xu', 'Zifeng Wang', 'Sheng Wang', 'Jimeng Sun'] | ['cs.CL', 'cs.AI'] | Clinical trials are fundamental in developing new drugs, medical devices, and
treatments. However, they are often time-consuming and have low success rates.
Although there have been initial attempts to create large language models
(LLMs) for clinical trial design and patient-trial matching, these models
remain task-spe... | 2024-06-25T21:29:25Z | null | null | null | null | null | null | null | null | null | null |
2,407.11062 | EfficientQAT: Efficient Quantization-Aware Training for Large Language
Models | ['Mengzhao Chen', 'Wenqi Shao', 'Peng Xu', 'Jiahao Wang', 'Peng Gao', 'Kaipeng Zhang', 'Ping Luo'] | ['cs.LG', 'cs.AI', 'cs.CL'] | Large language models (LLMs) are crucial in modern natural language
processing and artificial intelligence. However, they face challenges in
managing their significant memory requirements. Although quantization-aware
training (QAT) offers a solution by reducing memory consumption through low-bit
representations with mi... | 2024-07-10T17:53:30Z | ACL 2025 Main, camera ready version | null | null | EfficientQAT: Efficient Quantization-Aware Training for Large Language Models | ['Mengzhao Chen', 'Wenqi Shao', 'Peng Xu', 'Jiahao Wang', 'Peng Gao', 'Kai-Chuang Zhang', 'Yu Qiao', 'Ping Luo'] | 2,024 | arXiv.org | 35 | 79 | ['Computer Science'] |
2,407.11093 | A neural network for forward and inverse nonlinear Fourier transforms
for fiber optic communication | ['Wen Qi Zhang', 'Terence H. Chan', 'Shahraam Afshar V.'] | ['eess.SP', 'physics.optics'] | We propose a neural network for both forward and inverse continuous nonlinear
Fourier transforms, NFT and INFT respectively. We demonstrate the network's
capability to perform NFT and INFT for a random mix of NFDM-QAM signals. The
network transformations (NFT and INFT) exhibit true characteristics of these
transformati... | 2024-07-15T01:43:12Z | null | Optics & Laser Technology, vol. 176, p. 110971, Sep. 2024 | 10.1016/j.optlastec.2024.110971. | null | null | null | null | null | null | null |
2,407.11194 | AstroMLab 1: Who Wins Astronomy Jeopardy!? | ['Yuan-Sen Ting', 'Tuan Dung Nguyen', 'Tirthankar Ghosal', 'Rui Pan', 'Hardik Arora', 'Zechang Sun', 'Tijmen de Haan', 'Nesar Ramachandra', 'Azton Wells', 'Sandeep Madireddy', 'Alberto Accomazzi'] | ['astro-ph.IM', 'astro-ph.EP', 'astro-ph.GA', 'astro-ph.SR', 'cs.AI', 'cs.CL'] | We present a comprehensive evaluation of proprietary and open-weights large
language models using the first astronomy-specific benchmarking dataset. This
dataset comprises 4,425 multiple-choice questions curated from the Annual
Review of Astronomy and Astrophysics, covering a broad range of astrophysical
topics. Our an... | 2024-07-15T19:28:14Z | 45 pages, 12 figures, 7 tables. Published in Astronomy & Computing.
AstroMLab homepage: https://astromlab.org/ | null | null | AstroMLab 1: Who Wins Astronomy Jeopardy!? | ['Yuan-Sen Ting', 'Tuan Dung Nguyen', 'Tirthankar Ghosal', 'Rui Pan', 'Hardik Arora', 'Ze-Chang Sun', 'Tijmen de Haan', 'Nesar Ramachandra', 'Azton Wells', 'Sandeep Madireddy', 'Alberto Accomazzi'] | 2,024 | Astronomy and Computing | 4 | 31 | ['Computer Science', 'Physics'] |
2,407.11398 | Animate3D: Animating Any 3D Model with Multi-view Video Diffusion | ['Yanqin Jiang', 'Chaohui Yu', 'Chenjie Cao', 'Fan Wang', 'Weiming Hu', 'Jin Gao'] | ['cs.CV'] | Recent advances in 4D generation mainly focus on generating 4D content by
distilling pre-trained text or single-view image-conditioned models. It is
inconvenient for them to take advantage of various off-the-shelf 3D assets with
multi-view attributes, and their results suffer from spatiotemporal
inconsistency owing to ... | 2024-07-16T05:35:57Z | Project Page: https://animate3d.github.io/ | null | null | Animate3D: Animating Any 3D Model with Multi-view Video Diffusion | ['Yanqin Jiang', 'Chaohui Yu', 'Chenjie Cao', 'Fan Wang', 'Weiming Hu', 'Jin Gao'] | 2,024 | Neural Information Processing Systems | 19 | 77 | ['Computer Science'] |
2,407.11449 | Controllable Contextualized Image Captioning: Directing the Visual
Narrative through User-Defined Highlights | ['Shunqi Mao', 'Chaoyi Zhang', 'Hang Su', 'Hwanjun Song', 'Igor Shalyminov', 'Weidong Cai'] | ['cs.CV', 'cs.AI'] | Contextualized Image Captioning (CIC) evolves traditional image captioning
into a more complex domain, necessitating the ability for multimodal reasoning.
It aims to generate image captions given specific contextual information. This
paper further introduces a novel domain of Controllable Contextualized Image
Captionin... | 2024-07-16T07:32:48Z | ECCV 2024 | null | null | Controllable Contextualized Image Captioning: Directing the Visual Narrative through User-Defined Highlights | ['Shunqi Mao', 'Chaoyi Zhang', 'Hang Su', 'Hwanjun Song', 'Igor Shalyminov', 'Weidong Cai'] | 2,024 | European Conference on Computer Vision | 1 | 69 | ['Computer Science'] |
2,407.11496 | ReLaX-VQA: Residual Fragment and Layer Stack Extraction for Enhancing
Video Quality Assessment | ['Xinyi Wang', 'Angeliki Katsenou', 'David Bull'] | ['eess.IV', 'cs.CV', 'cs.MM'] | With the rapid growth of User-Generated Content (UGC) exchanged between users
and sharing platforms, the need for video quality assessment in the wild is
increasingly evident. UGC is typically acquired using consumer devices and
undergoes multiple rounds of compression (transcoding) before reaching the end
user. Theref... | 2024-07-16T08:33:55Z | 10 pages, 3 figures | null | null | null | null | null | null | null | null | null |
2,407.1166 | ECoh: Turn-level Coherence Evaluation for Multilingual Dialogues | ['John Mendonça', 'Isabel Trancoso', 'Alon Lavie'] | ['cs.CL'] | Despite being heralded as the new standard for dialogue evaluation, the
closed-source nature of GPT-4 poses challenges for the community. Motivated by
the need for lightweight, open source, and multilingual dialogue evaluators,
this paper introduces GenResCoh (Generated Responses targeting Coherence).
GenResCoh is a no... | 2024-07-16T12:28:30Z | Accepted to SIGDIAL 2024 | null | null | ECoh: Turn-level Coherence Evaluation for Multilingual Dialogues | ['John Mendonça', 'Isabel Trancoso', 'A. Lavie'] | 2,024 | SIGDIAL Conferences | 3 | 45 | ['Computer Science'] |
2,407.11691 | VLMEvalKit: An Open-Source Toolkit for Evaluating Large Multi-Modality
Models | ['Haodong Duan', 'Xinyu Fang', 'Junming Yang', 'Xiangyu Zhao', 'Yuxuan Qiao', 'Mo Li', 'Amit Agarwal', 'Zhe Chen', 'Lin Chen', 'Yuan Liu', 'Yubo Ma', 'Hailong Sun', 'Yifan Zhang', 'Shiyin Lu', 'Tack Hwa Wong', 'Weiyun Wang', 'Peiheng Zhou', 'Xiaozhe Li', 'Chaoyou Fu', 'Junbo Cui', 'Xiaoyi Dong', 'Yuhang Zang', 'Pan Zha... | ['cs.CV'] | We present VLMEvalKit: an open-source toolkit for evaluating large
multi-modality models based on PyTorch. The toolkit aims to provide a
user-friendly and comprehensive framework for researchers and developers to
evaluate existing multi-modality models and publish reproducible evaluation
results. In VLMEvalKit, we impl... | 2024-07-16T13:06:15Z | Updated on 2025.03.04 | null | null | null | null | null | null | null | null | null |
2,407.11699 | Relation DETR: Exploring Explicit Position Relation Prior for Object
Detection | ['Xiuquan Hou', 'Meiqin Liu', 'Senlin Zhang', 'Ping Wei', 'Badong Chen', 'Xuguang Lan'] | ['cs.CV'] | This paper presents a general scheme for enhancing the convergence and
performance of DETR (DEtection TRansformer). We investigate the slow
convergence problem in transformers from a new perspective, suggesting that it
arises from the self-attention that introduces no structural bias over inputs.
To address this issue,... | 2024-07-16T13:17:07Z | Accepted to ECCV 2024 | null | null | Relation DETR: Exploring Explicit Position Relation Prior for Object Detection | ['Xiuquan Hou', 'Mei-qin Liu', 'Senlin Zhang', 'Ping Wei', 'Badong Chen', 'Xuguang Lan'] | 2,024 | European Conference on Computer Vision | 17 | 52 | ['Computer Science'] |
2,407.11828 | Vibravox: A Dataset of French Speech Captured with Body-conduction Audio
Sensors | ['Julien Hauret', 'Malo Olivier', 'Thomas Joubaud', 'Christophe Langrenne', 'Sarah Poirée', 'Véronique Zimpfer', 'Éric Bavu'] | ['eess.AS', 'cs.LG'] | Vibravox is a dataset compliant with the General Data Protection Regulation
(GDPR) containing audio recordings using five different body-conduction audio
sensors: two in-ear microphones, two bone conduction vibration pickups, and a
laryngophone. The dataset also includes audio data from an airborne microphone
used as a... | 2024-07-16T15:16:10Z | 23 pages, 42 figures | null | null | Vibravox: A Dataset of French Speech Captured with Body-conduction Audio Sensors | ['J. Hauret', 'Malo Olivier', 'Thomas Joubaud', 'C. Langrenne', "Sarah Poir'ee", 'V. Zimpfer', 'É. Bavu'] | 2,024 | Speech Communication | 5 | 104 | ['Computer Science', 'Engineering'] |
2,407.12077 | GoldFinch: High Performance RWKV/Transformer Hybrid with Linear Pre-Fill
and Extreme KV-Cache Compression | ['Daniel Goldstein', 'Fares Obeid', 'Eric Alcaide', 'Guangyu Song', 'Eugene Cheah'] | ['cs.CL', 'cs.AI'] | We introduce GoldFinch, a hybrid Linear Attention/Transformer sequence model
that uses a new technique to efficiently generate a highly compressed and
reusable KV-Cache in linear time and space with respect to sequence length.
GoldFinch stacks our new GOLD transformer on top of an enhanced version of the
Finch (RWKV-6)... | 2024-07-16T18:00:00Z | null | null | null | GoldFinch: High Performance RWKV/Transformer Hybrid with Linear Pre-Fill and Extreme KV-Cache Compression | ['Daniel Goldstein', 'Fares Obeid', 'Eric Alcaide', 'Guangyu Song', 'Eugene Cheah'] | 2,024 | arXiv.org | 8 | 20 | ['Computer Science'] |
2,407.12126 | LLMs-in-the-loop Part-1: Expert Small AI Models for Bio-Medical Text
Translation | ['Bunyamin Keles', 'Murat Gunay', 'Serdar I. Caglar'] | ['cs.CL', 'cs.AI', '68T35'] | Machine translation is indispensable in healthcare for enabling the global
dissemination of medical knowledge across languages. However, complex medical
terminology poses unique challenges to achieving adequate translation quality
and accuracy. This study introduces a novel "LLMs-in-the-loop" approach to
develop superv... | 2024-07-16T19:32:23Z | 14 pages, 2 figures, 9 tables | null | null | LLMs-in-the-loop Part-1: Expert Small AI Models for Bio-Medical Text Translation | ['Bunyamin Keles', 'Murat Gunay', 'Serdar I. Caglar'] | 2,024 | arXiv.org | 2 | 54 | ['Computer Science'] |
2,407.1217 | Neural Passage Quality Estimation for Static Pruning | ['Xuejun Chang', 'Debabrata Mishra', 'Craig Macdonald', 'Sean MacAvaney'] | ['cs.IR'] | Neural networks -- especially those that use large, pre-trained language
models -- have improved search engines in various ways. Most prominently, they
can estimate the relevance of a passage or document to a user's query. In this
work, we depart from this direction by exploring whether neural networks can
effectively ... | 2024-07-16T20:47:54Z | SIGIR 2024 | null | 10.1145/3626772.3657765 | Neural Passage Quality Estimation for Static Pruning | ['Xuejun Chang', 'Debabrata Mishra', 'Craig Macdonald', 'Sean MacAvaney'] | 2,024 | Annual International ACM SIGIR Conference on Research and Development in Information Retrieval | 3 | 73 | ['Computer Science'] |
2,407.12317 | Out of Length Text Recognition with Sub-String Matching | ['Yongkun Du', 'Zhineng Chen', 'Caiyan Jia', 'Xieping Gao', 'Yu-Gang Jiang'] | ['cs.CV'] | Scene Text Recognition (STR) methods have demonstrated robust performance in
word-level text recognition. However, in real applications the text image is
sometimes long due to detected with multiple horizontal words. It triggers the
requirement to build long text recognition models from readily available short
(i.e., w... | 2024-07-17T05:02:17Z | Accepted by AAAI2025 | null | null | null | null | null | null | null | null | null |
2,407.12383 | Reliable and Efficient Concept Erasure of Text-to-Image Diffusion Models | ['Chao Gong', 'Kai Chen', 'Zhipeng Wei', 'Jingjing Chen', 'Yu-Gang Jiang'] | ['cs.CV'] | Text-to-image models encounter safety issues, including concerns related to
copyright and Not-Safe-For-Work (NSFW) content. Despite several methods have
been proposed for erasing inappropriate concepts from diffusion models, they
often exhibit incomplete erasure, consume a lot of computing resources, and
inadvertently ... | 2024-07-17T08:04:28Z | ECCV 2024 accepted | null | null | null | null | null | null | null | null | null |
2,407.12563 | Audio Conditioning for Music Generation via Discrete Bottleneck Features | ['Simon Rouard', 'Yossi Adi', 'Jade Copet', 'Axel Roebel', 'Alexandre Défossez'] | ['cs.SD', 'eess.AS'] | While most music generation models use textual or parametric conditioning
(e.g. tempo, harmony, musical genre), we propose to condition a language model
based music generation system with audio input. Our exploration involves two
distinct strategies. The first strategy, termed textual inversion, leverages a
pre-trained... | 2024-07-17T13:47:17Z | 6 pages, 2 figures, accepted at ISMIR 2024 | null | null | Audio Conditioning for Music Generation via Discrete Bottleneck Features | ['Simon Rouard', 'Yossi Adi', 'Jade Copet', 'Axel Roebel', "Alexandre D'efossez"] | 2,024 | International Society for Music Information Retrieval Conference | 1 | 39 | ['Computer Science', 'Engineering'] |
2,407.1258 | E5-V: Universal Embeddings with Multimodal Large Language Models | ['Ting Jiang', 'Minghui Song', 'Zihan Zhang', 'Haizhen Huang', 'Weiwei Deng', 'Feng Sun', 'Qi Zhang', 'Deqing Wang', 'Fuzhen Zhuang'] | ['cs.CL', 'cs.CV', 'cs.IR'] | Multimodal large language models (MLLMs) have shown promising advancements in
general visual and language understanding. However, the representation of
multimodal information using MLLMs remains largely unexplored. In this work, we
introduce a new framework, E5-V, designed to adapt MLLMs for achieving
universal multimo... | 2024-07-17T14:04:12Z | Code and models are available at https://github.com/kongds/E5-V | null | null | E5-V: Universal Embeddings with Multimodal Large Language Models | ['Ting Jiang', 'Minghui Song', 'Zihan Zhang', 'Haizhen Huang', 'Weiwei Deng', 'Feng Sun', 'Qi Zhang', 'Deqing Wang', 'Fuzhen Zhuang'] | 2,024 | arXiv.org | 34 | 30 | ['Computer Science'] |
2,407.12665 | Beyond Next Token Prediction: Patch-Level Training for Large Language
Models | ['Chenze Shao', 'Fandong Meng', 'Jie Zhou'] | ['cs.CL', 'cs.AI', 'cs.LG'] | The prohibitive training costs of Large Language Models (LLMs) have emerged
as a significant bottleneck in the development of next-generation LLMs. In this
paper, we show that it is possible to significantly reduce the training costs
of LLMs without sacrificing their performance. Specifically, we introduce
patch-level ... | 2024-07-17T15:48:39Z | ICLR 2025 Spotlight | null | null | null | null | null | null | null | null | null |
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