Trending Research
Agents: An Open-source Framework for Autonomous Language Agents
Recent advances on large language models (LLMs) enable researchers and developers to build autonomous language agents that can automatically solve various tasks and interact with environments, humans, and other agents using natural language interfaces.
The Rise and Potential of Large Language Model Based Agents: A Survey
Many efforts have been made to develop intelligent agents, but they mainly focus on advancement in algorithms or training strategies to enhance specific capabilities or performance on particular tasks.
NExT-GPT: Any-to-Any Multimodal LLM
While recently Multimodal Large Language Models (MM-LLMs) have made exciting strides, they mostly fall prey to the limitation of only input-side multimodal understanding, without the ability to produce content in multiple modalities.
ProPainter: Improving Propagation and Transformer for Video Inpainting
We also propose a mask-guided sparse video Transformer, which achieves high efficiency by discarding unnecessary and redundant tokens.
Ranked #1 on
Video Inpainting
on DAVIS
OverFlow: Putting flows on top of neural transducers for better TTS
coqui-ai/TTS
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Neural HMMs are a type of neural transducer recently proposed for sequence-to-sequence modelling in text-to-speech.
Ranked #11 on
Text-To-Speech Synthesis
on LJSpeech
(using extra training data)
AgentVerse: Facilitating Multi-Agent Collaboration and Exploring Emergent Behaviors in Agents
Autonomous agents empowered by Large Language Models (LLMs) have undergone significant improvements, enabling them to generalize across a broad spectrum of tasks.
Communicative Agents for Software Development
At the core of this paradigm lies ChatDev, a virtual chat-powered software development company that mirrors the established waterfall model, meticulously dividing the development process into four distinct chronological stages: designing, coding, testing, and documenting.
Baichuan 2: Open Large-scale Language Models
Large language models (LLMs) have demonstrated remarkable performance on a variety of natural language tasks based on just a few examples of natural language instructions, reducing the need for extensive feature engineering.
Nougat: Neural Optical Understanding for Academic Documents
Scientific knowledge is predominantly stored in books and scientific journals, often in the form of PDFs.
GPTFUZZER : Red Teaming Large Language Models with Auto-Generated Jailbreak Prompts
Notably, even starting with suboptimal seed templates, \fuzzer maintains over 90\% attack success rate against ChatGPT and Llama-2 models.
