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Weimin Wang, Jiawei Liu, Zhijie Lin +9 authors
MagicVideo-V2 generates high-fidelity and smooth videos from text using an integrated pipeline that includes text-to-image, video motion generation, and frame interpolation modules, outperforming existing systems in user evaluations.
Tiannan Wang, Jiamin Chen, Qingrui Jia +43 authors
Weaver, a family of specialized large language models, achieves superior writing capabilities through pre-training and fine-tuning methods, surpasses GPT-4 in various writing tasks, and supports retrieval-augmented generation and tool usage.
Abhimanyu Hans, Avi Schwarzschild, Valeriia Cherepanova +5 authors
A novel LLM detector using contrasting scores from two pre-trained models achieves high accuracy in identifying machine-generated text without any training data.
Tianheng Cheng, Lin Song, Yixiao Ge +3 authors
YOLO-World enhances YOLO with open-vocabulary detection using vision-language modeling and a re-parameterizable network, achieving high accuracy and speed.
Alon Ziv, Itai Gat, Gael Le Lan +6 authors
MAGNeT is a single-stage, non-autoregressive transformer for audio generation that uses masked spans during training, a rescoring method, and a hybrid approach to achieve fast generation.
Yue Liu, Yunjie Tian, Yuzhong Zhao +5 authors
VMamba, a novel state space model architecture, combines global receptive fields and dynamic weights from ViTs with linear complexity, outperforming established models as image resolution increases.
Xiaoyu Shi, Zhaoyang Huang, Fu-Yun Wang +9 authors
Motion-I2V, a diffusion-based framework for image-to-video generation, achieves consistency and controllability through explicit motion modeling and trajectory prediction.
Matanel Oren, Michael Hassid, Yossi Adi +1 authors
Decoder-only transformers can be conceptualized as finite multi-state RNNs, and a new cache compression technique, TOVA, significantly reduces their computational cost while maintaining high performance.
Alaaeldin El-Nouby, Michal Klein, Shuangfei Zhai +5 authors
Autoregressive pre-training for vision models (AIM) scales similarly to LLMs, showing improved performance with more data and parameters, and does not exhibit performance saturation.
Rachit Bansal, Bidisha Samanta, Siddharth Dalmia +6 authors
CALM, a composition method for large language models, enhances capabilities by integrating cross-attention with specialized models, demonstrating improvements on translation and coding tasks.
Chaochao Lu, Chen Qian, Guodong Zheng +33 authors
A qualitative study evaluates the generalizability, trustworthiness, and causal reasoning capabilities of MLLMs across text, code, image, and video modalities to understand their reliability for downstream applications.
Haoran Xu, Amr Sharaf, Yunmo Chen +5 authors
Contrastive Preference Optimization (CPO) enhances moderate-sized LLMs in machine translation, enabling them to match or exceed state-of-the-art model performance.
Keming Lu, Bowen Yu, Chang Zhou +1 authors
Ditto, a self-alignment method, enhances the role-playing capabilities of open-source large language models by fine-tuning them on a large generated dataset, achieving performance comparable to proprietary chatbots.
Zihan Liu, Wei Ping, Rajarshi Roy +3 authors
ChatQA uses a two-stage instruction tuning method with a dense retriever to improve zero-shot conversational QA performance, outperforming GPT-4 on multiple datasets.
Dongsheng Wang, Zhiqiang Ma, Armineh Nourbakhsh +2 authors
A new framework, DocGraphLM, combines pre-trained language models with graph semantics to improve information extraction and question answering on documents with complex layouts.
Ming Yan, Ruihao Li, Hao Zhang +3 authors
LARP is a language agent framework for open-world games, incorporating memory and decision-making capabilities to enhance interaction and coherence in a diverse range of applications.
Zhennan Wu, Yang Li, Han Yan +8 authors
BlockFusion, a diffusion-based model, generates and expands 3D scenes using latent tri-plane representations and a 2D layout conditioning mechanism.
Hongliang He, Wenlin Yao, Kaixin Ma +5 authors
WebVoyager, a Large Multimodal Model, enhances web agent performance by handling multiple modalities and real-world web interactions, achieving high success rates in practical tasks.
Mirac Suzgun, Adam Tauman Kalai
Meta-prompting enhances language model performance by organizing and integrating multiple expert instances to handle complex tasks, demonstrating superiority over traditional methods in zero-shot settings.
Zipeng Fu, Tony Z. Zhao, Chelsea Finn
Co-training of supervised behavior cloning with static and mobile manipulation datasets improves the success rates of mobile manipulation tasks using a whole-body teleoperation system.
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