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Yichun Shi, Peng Wang, Jianglong Ye +3 authors
MVDream generates geometrically consistent multi-view images from text prompts using pre-trained image diffusion models and Score Distillation Sampling, improving 3D generation stability and supporting personalized generation.
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Yuanzhi Li, Sébastien Bubeck, Ronen Eldan +3 authors
A new 1.3 billion parameter Transformer-based language model, phi-1.5, demonstrates comparable performance to much larger models on common sense reasoning and complex tasks despite the absence of web data.
Yukang Chen, Shengju Qian, Haotian Tang +4 authors
LongLoRA extends LLM context sizes efficiently using sparse local attention and parameter-efficient fine-tuning, demonstrating strong results with minimal computational cost.
Thuat Nguyen, Chien Van Nguyen, Viet Dac Lai +5 authors
CulturaX is a large multilingual dataset designed to improve the training and quality of large language models through rigorous data cleaning and deduplication.
Timothée Darcet, Maxime Oquab, Julien Mairal +1 authors
Additional input tokens in Vision Transformers mitigate artifacts in feature maps, enhancing performance and enabling smoother visual processing.
Bowen Peng, Jeffrey Quesnelle, Honglu Fan +1 authors
YaRN extends the context window of transformer-based language models like LLaMA with improved efficiency and performance.
Grégoire Delétang, Anian Ruoss, Paul-Ambroise Duquenne +9 authors
Large language models demonstrate strong compression capabilities, outperforming domain-specific compressors and offering new insights into scaling laws, tokenization, and in-context learning.
Daixuan Cheng, Shaohan Huang, Furu Wei
Transforming raw corpora into reading comprehension texts enhances large language models' question-answering abilities across various domains and improves performance on general benchmarks.
Ramakrishna Bairi, Atharv Sonwane, Aditya Kanade +6 authors
CodePlan automates repository-level coding tasks, such as package migration and temporal code edits, using a planning framework that leverages LLMs with context derived from code repositories and change analysis.
Shengqiong Wu, Hao Fei, Leigang Qu +2 authors
NExT-GPT, an any-to-any Multimodal Large Language Model, combines LLMs with multimodal adaptors and diffusion decoders to generate content across various modalities, enhanced by modality-switching instruction tuning and a curated dataset.
Chengrun Yang, Xuezhi Wang, Yifeng Lu +4 authors
OPRO, a method using large language models to optimize tasks described in natural language, outperforms human-designed prompts on various benchmark datasets.
Woosuk Kwon, Zhuohan Li, Siyuan Zhuang +6 authors
PagedAttention algorithm and vLLM system enhance the throughput of large language models by efficiently managing memory and reducing waste in the key-value cache.
Vincent Perot, Kai Kang, Florian Luisier +7 authors
LMDX adapts large language models for document information extraction with grounding guarantees, setting a new state-of-the-art on VRDU and CORD benchmarks.
Chenyang Si, Ziqi Huang, Yuming Jiang +1 authors
A method called FreeU improves diffusion U-Net models' generation quality by re-weighting skip connections and backbone features without additional training.
Runpei Dong, Chunrui Han, Yuang Peng +11 authors
DreamLLM, a framework for Multimodal Large Language Models, directly samples in the multimodal space to enhance comprehension and creation synergy, enabling free-form interleaved content generation.
Seungwhan Moon, Andrea Madotto, Zhaojiang Lin +10 authors
AnyMAL is a unified model that processes multiple modalities (text, image, video, audio, IMU) and generates text, achieving top performance in multimodal tasks through a pre-trained aligner and fine-tuning with diverse instructions.
Tengchao Lv, Yupan Huang, Jingye Chen +11 authors
Kosmos-2.5, a unified multimodal model, generates spatially-aware and structured text from text-intensive images using a Transformer architecture and task-specific prompts.
Jon Saad-Falcon, Joe Barrow, Alexa Siu +3 authors
PDFTriage enables LLMs to retrieve context effectively from structured documents like PDFs and web pages for better document QA performance.
Brendan Walsh, Mark Hamilton, Greg Newby +8 authors
A system leverages neural text-to-speech to automatically generate high-quality, customizable audiobooks from e-books, significantly expanding access to literature.
Zhengqi Li, Richard Tucker, Noah Snavely +1 authors
A frequency-coordinated diffusion sampling process is used to predict long-term motion representations for still images, enabling dynamic video creation and interactive scene manipulation.
Qingyan Guo, Rui Wang, Junliang Guo +6 authors
EvoPrompt, a framework using evolutionary algorithms, automates prompt optimization for large language models, achieving better performance than human-engineered prompts.
Harrison Lee, Samrat Phatale, Hassan Mansoor +5 authors
Reinforcement learning from AI feedback (RLAIF) achieves similar performance to reinforcement learning from human feedback (RLHF) in aligning large language models with human preferences, offering a scalable alternative.
Li Chen, Mengyi Zhao, Yiheng Liu +8 authors
PhotoVerse uses a dual-branch conditioning mechanism and facial identity loss to generate high-quality, identity-preserving images efficiently with minimal tuning.
Jiaxiang Tang, Jiawei Ren, Hang Zhou +2 authors
DreamGaussian is a 3D content generation framework that combines generative Gaussian splatting with mesh extraction and texture refinement for high efficiency and quality.
Yuhui Xu, Lingxi Xie, Xiaotao Gu +6 authors
QA-LoRA algorithm reduces computational requirements for large language models by quantizing weights during fine-tuning and integrating auxiliary weights post-training.
Xiang Li, Yiqun Yao, Xin Jiang +10 authors
A growth strategy reduces the cost of training large language models while achieving comparable performance, with a focus on evaluating IQ and minimizing memorization.
Yaohui Wang, Xinyuan Chen, Xin Ma +17 authors
LaVie, a text-to-video framework integrating cascaded video latent diffusion models, achieves state-of-the-art video generation by leveraging temporal self-attentions and joint image-video fine-tuning.
Wangchunshu Zhou, Yuchen Eleanor Jiang, Long Li +14 authors
Agents is an open-source library that facilitates the creation, customization, and deployment of autonomous language agents with features like planning, memory, and tool usage, aiming to make advances in large language models accessible to a broader audience.
Chunyuan Li, Zhe Gan, Zhengyuan Yang +4 authors
The survey covers the development and advancements in multimodal foundation models that integrate vision and language, transitioning from specialized models to versatile assistants through various training methods and unified architectures.
Shehzaad Dhuliawala, Mojtaba Komeili, Jing Xu +4 authors
The Chain-of-Verification method reduces hallucinations in language models by having them draft, plan verification questions, answer independently, and then generate a final verified response.
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