Tasks
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Multi AI Agent Systems 101. Automating Routine Tasks in Data Source… | by Mariya Mansurova | Jun, 2024
Initially, when ChatGPT just appeared, we used simple prompts to get answers to our questions. Then, we encountered issues with…
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Pokémon Go ‘Spelunker’s Cove’ event and Timed Research tasks
Pokémon Go is hosting a water- and rock-type Pokémon event called “Spelunker’s Cove” to coincide with Pokémon Go Fest: Madrid.…
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Evaluating the IWSLT2023 Speech Translation Tasks: Human Annotations, Automatic Metrics, and Segmentation
Human evaluation is a critical component in machine translation system development and has received much attention in text translation research.…
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From Low-Level to High-Level Tasks: Scaling Fine-Tuning with the ANDROIDCONTROL Dataset
Large language models (LLMs) have shown promise in powering autonomous agents that control computer interfaces to accomplish human tasks. However,…
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Pokémon Go ‘Stadium Sights’ event and Timed Research tasks
Pokémon Go is hosting the “Stadium Sights” event from June 1-4 to coincide with the in-person Pokémon Go Fest: Sendai…
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This AI Paper Introduces LCM-LoRA: Revolutionizing Text-to-Image Generative Tasks with Advanced Latent Consistency Models and LoRA Distillation
Latent Diffusion Models are generative models used in machine learning, particularly in probabilistic modeling. These models aim to capture a…
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Pokémon Go ‘Festival of Lights’ event guide, research tasks and rewards
Pokémon Go’s Festival of Lights is an event focused on electric- and fire-type Pokémon running between Nov. 7 and Nov.…
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Imperial College London Team Develops an Artificial Intelligence Method for Few-Shot Imitation Learning: Mastering Novel Real-World Tasks with Minimal Demonstrations
In the ever-evolving landscape of robotics and Artificial Intelligence, an interesting and challenging problem is how to educate robots to…
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HuggingFace Introduces TextEnvironments: An Orchestrator between a Machine Learning Model and A Set of Tools (Python Functions) that the Model can Call to Solve Specific Tasks
Supervised Fine-tuning (SFT), Reward Modeling (RM), and Proximal Policy Optimization (PPO) are all part of TRL. In this full-stack library,…
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Researchers from Stanford Propose ‘EquivAct’: A Breakthrough in Robot Learning for Generalizing Tasks Across Different Scales and Orientations
Humans can extrapolate and learn to solve variations of a manipulation task if the objects involved have varied visual or…
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