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Bernhard Kerbl, Georgios Kopanas, Thomas Leimkühler +1 authors
A method using 3D Gaussians for scene representation and optimized rendering allows high-quality, real-time novel-view synthesis at 1080p resolution.
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Zhewei Yao, Reza Yazdani Aminabadi, Olatunji Ruwase +16 authors
DeepSpeed-Chat introduces an efficient and accessible RLHF training pipeline for large-scale ChatGPT-like models, enabling rapid and cost-effective training.
Xian Li, Ping Yu, Chunting Zhou +5 authors
A scalable instruction-following language model is built using auto-labelling and iterative self-augmentation and self-curation, outperforming other LLaMa-based models on Alpaca.
Lukas Blecher, Guillem Cucurull, Thomas Scialom +1 authors
Nougat, a Visual Transformer model, performs OCR on scientific documents converting them to markup language, enhancing digital accessibility.
Chi Han, Qifan Wang, Wenhan Xiong +3 authors
LM-Infinite addresses length generalization in Transformer-based LLMs using a simple $\Lambda$-shaped attention mask, achieving fluency and quality up to 32k tokens without retraining.
SeungHeon Doh, Keunwoo Choi, Jongpil Lee +1 authors
A large-scale pseudo music caption dataset generated using LLMs improves music captioning performance over supervised models in zero-shot and transfer-learning settings.
Hu Ye, Jun Zhang, Sibo Liu +2 authors
IP-Adapter introduces a lightweight decoupled cross-attention mechanism to enhance pretrained text-to-image diffusion models with image prompt capabilities, enabling multimodal image generation and compatibility with existing tools.
Haohe Liu, Qiao Tian, Yi Yuan +7 authors
A unified audio generation framework using a language of audio representation, AudioMAE, and latent diffusion model achieves state-of-the-art performance across different audio types.
Cheng-Yu Hsieh, Si-An Chen, Chun-Liang Li +5 authors
LLMs can effectively use tool documentation instead of demonstrations to perform complex tasks, achieving performance comparable or superior to few-shot learning on both vision and language benchmarks.
Jessy Lin, Yuqing Du, Olivia Watkins +4 authors
Dynalang, a multimodal agent, learns to predict future text and image representations using language hints to improve task performance and enrich its understanding.
Yangyi Huang, Hongwei Yi, Yuliang Xiu +4 authors
TeCH reconstructs high-fidelity 3D human models from single images using descriptive text prompts, a personalized Text-to-Image diffusion model, and a hybrid DMTet representation, outperforming existing methods.
Yu Shu, Siwei Dong, Guangyao Chen +5 authors
LLaSM, an end-to-end trained large multi-modal speech-language model, enhances human interaction with AI by following speech-and-language instructions using cross-modal conversational abilities.
Tear Gosling, Alpin Dale, Yinhe Zheng
PIPPA, a community-driven partially-synthetic dataset, provides over a million utterances across numerous conversation sessions to enhance role-play and conversational AI research and development.
Anas Awadalla, Irena Gao, Josh Gardner +13 authors
OpenFlamingo, an open-source family of autoregressive vision-language models, replicates DeepMind's Flamingo performance across multiple datasets.
Niklas Muennighoff, Qian Liu, Armel Zebaze +7 authors
Instruction tuning using Git commits improves performance on natural language and coding tasks compared to other benchmarks, with models achieving state-of-the-art results on expanded HumanEvalPack.
Peike Li, Boyu Chen, Yao Yao +3 authors
JEN-1, a diffusion model combining autoregressive and non-autoregressive training, achieves superior performance in text-to-music generation, music inpainting, and continuation, while maintaining computational efficiency.
Tianlu Wang, Ping Yu, Xiaoqing Ellen Tan +7 authors
Shepherd, a small language model tuned for critique, outperforms or ties with larger models like ChatGPT in refining language model outputs using a high-quality feedback dataset.
Anthony Brohan, Noah Brown, Justice Carbajal +51 authors
Vision-language-action models, trained on large-scale vision and language data, are integrated into robotic control to enhance generalization and semantic reasoning.
Scott L. Fleming, Alejandro Lozano, William J. Haberkorn +27 authors
MedAlign, a curated dataset of natural language instructions for EHR data, evaluates the accuracy and quality of general domain LLMs in healthcare, revealing high error rates and context length dependencies.
Yang Liu, Yuanshun Yao, Jean-Francois Ton +5 authors
This survey examines key dimensions of trustworthiness for large language models, including reliability, safety, fairness, misuse resistance, explainability, social norms adherence, and robustness, providing guidelines for evaluating and improving model alignment.
Neha Sengupta, Sunil Kumar Sahu, Bokang Jia +19 authors
Jais and Jais-chat, Arabic-centric LLMs based on the GPT-3 architecture, outperform existing models in Arabic and are competitive in English with fewer resources.
Hao Ouyang, Qiuyu Wang, Yuxi Xiao +6 authors
CoDeF represents videos using a canonical content field and a temporal deformation field, enabling the lifting of image processing algorithms to video processing with superior cross-frame consistency.
Michaël Mathieu, Sherjil Ozair, Srivatsan Srinivasan +21 authors
A benchmark called AlphaStar Unplugged is established for offline reinforcement learning using a dataset from StarCraft II, featuring unprecedented challenges and achieving high win rates with offline data.
Hanjia Lyu, Song Jiang, Hanqing Zeng +2 authors
Combining diverse prompts and input augmentation techniques improves personalized content recommendation performance using large language models.
Xiaofei Wang, Manthan Thakker, Zhuo Chen +7 authors
SpeechX integrates neural codec language modeling and multi-task learning to enable versatile speech generation, transformation, and enhancement tasks in both clean and noisy conditions.
Cheng Li, Mingyang Zhang, Qiaozhu Mei +4 authors
A multistage and multitask framework using large language models enhances personalized text generation by improving retrieval, ranking, summarization, synthesis, and generation skills.
Benjamin Spector, Chris Re
A staged speculative decoding algorithm enhances LLM inference efficiency in small-batch, on-device settings by restructuring speculative batches and adding a second decoding stage.
Xiao Liu, Hao Yu, Hanchen Zhang +19 authors
AgentBench is a multi-dimensional benchmark for evaluating LLMs as autonomous agents across various interactive environments, highlighting performance differences between commercial and open-source models.
Binhui Liu, Xin Liu, Anbo Dai +3 authors
The dual-stream diffusion net (DSDN) enhances video consistency and smoothness in text-to-video generation by using separate content and motion diffusion streams with a cross-transformer interaction module and motion decomposer/combiner.
Aojun Zhou, Ke Wang, Zimu Lu +8 authors
A novel code-based self-verification method significantly improves math reasoning in GPT-4 Code Interpreter, enhancing accuracy on the MATH dataset.
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