SUI

https://huggingface.co/papers/2305.13048 Paper page - RWKV: Reinventing RNNs for the Transformer Era huggingface.co https://twitter.com/_akhaliq/status/1660816265454419969?s=20 트위터에서 즐기는 AK “RWKV: Reinventing RNNs for the Transformer Era propose a novel model architecture, Receptance Weighted Key Value (RWKV), that combines the efficient parallelizable training of Transformers with the efficient..

https://arxiv.org/abs/2305.17066 Mindstorms in Natural Language-Based Societies of Mind Both Minsky's "society of mind" and Schmidhuber's "learning to think" inspire diverse societies of large multimodal neural networks (NNs) that solve problems by interviewing each other in a "mindstorm." Recent implementations of NN-based societies of minds arxiv.org 1. Minsky의 "마음의 사회"와 Schmidhuber의 "사고를 배우다"..

https://arxiv.org/abs/2305.16867 Playing repeated games with Large Language Models Large Language Models (LLMs) are transforming society and permeating into diverse applications. As a result, LLMs will frequently interact with us and other agents. It is, therefore, of great societal value to understand how LLMs behave in interactive soci arxiv.org 1. 대규모 언어 모델(LLMs)이 사회를 변화시키고 다양한 응용 분야에 퍼지고 있습니..

설명 -> https://twitter.com/DrJimFan/status/1662115266933972993?s=20 트위터에서 즐기는 Jim Fan “What if we set GPT-4 free in Minecraft? ⛏️ I’m excited to announce Voyager, the first lifelong learning agent that plays Minecraft purely in-context. Voyager continuously improves itself by writing, refining, committing, and retrieving *code* from twitter.com 1. 'Voyager'는 Minecraft에서 인간의 개입 없이 지속적으로 세계를 탐색하고, ..

https://arxiv.org/abs/2305.16960 Training Socially Aligned Language Models in Simulated Human Society Social alignment in AI systems aims to ensure that these models behave according to established societal values. However, unlike humans, who derive consensus on value judgments through social interaction, current language models (LMs) are trained to rigidl arxiv.org 1. 인공지능 시스템에서의 사회적 조정은 이러한 모델..

https://arxiv.org/abs/2305.17100 BiomedGPT: A Unified and Generalist Biomedical Generative Pre-trained Transformer for Vision, Language, and Multimodal Tasks In this paper, we introduce a unified and generalist Biomedical Generative Pre-trained Transformer (BiomedGPT) model, which leverages self-supervision on large and diverse datasets to accept multi-modal inputs and perform a range of downstr..

설명 https://twitter.com/tianle_cai/status/1662988435114852352?s=20 트위터에서 즐기는 Tianle Cai “LLMs can make their own tools just like humans🤖! Thrilled to share my intern work @Google. We introduced a closed-loop framework to let LLMs make and utilize reusable new tools🛠️ (implemented as programs). Paper: https://t.co/cOk3VZ47ka More det twitter.com https://arxiv.org/abs/2305.17126 Large Language Mode..

https://arxiv.org/abs/2305.16367 Role-Play with Large Language Models As dialogue agents become increasingly human-like in their performance, it is imperative that we develop effective ways to describe their behaviour in high-level terms without falling into the trap of anthropomorphism. In this paper, we foreground the conc arxiv.org 대화형 에이전트가 인간과 같은 행동을 점점 더 보여주면서, 인간의 특성을 과잉적으로 부여하는 인간화(anthr..

https://panda-gpt.github.io/ PandaGPT PandaGPT is a general-purpose instruction-following model that can both see and hear. Our pilot experiments show that PandaGPT can perform complex tasks such as detailed image description generation, writing stories inspired by videos, and answering questi panda-gpt.github.io https://arxiv.org/abs/2305.16355 PandaGPT: One Model To Instruction-Follow Them All..

https://arxiv.org/abs/2305.16338 Think Before You Act: Decision Transformers with Internal Working Memory Large language model (LLM)-based decision-making agents have shown the ability to generalize across multiple tasks. However, their performance relies on massive data and compute. We argue that this inefficiency stems from the forgetting phenomenon, in whic arxiv.org 1. 대형 언어 모델(LLM) 기반의 결정 생..