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Hello, I am Peter 👋🏻

  • 🎓 Phd student at Chung Cheng University in Taiwan
  • 🔬 Focus on Computer Vision, Natural Language Processing, Speech Systhesis, Reinforcement Learning.
  • 💻 AI Researcher for 6 years
  • 💬 Speak Vietnamese, English
  • 💜 Like Python, C/C++

PeterPham's Projects

4dgaussians icon 4dgaussians

[CVPR 2024] 4D Gaussian Splatting for Real-Time Dynamic Scene Rendering

abigsurvey icon abigsurvey

A collection of 1000+ survey papers on Natural Language Processing (NLP) and Machine Learning (ML)

agentbench icon agentbench

A Comprehensive Benchmark to Evaluate LLMs as Agents

agents icon agents

An Open-source Framework for Autonomous Language Agents

ai-game-development-tools icon ai-game-development-tools

Here we will keep track of the AI Game Development Tools, including programming, animation, effects, modeling, audio, music and more.🔥

aios icon aios

AIOS: LLM Agent Operating System

altfreezing icon altfreezing

[CVPR 2023 Highlight] Official implementation of the paper: "AltFreezing for More General Video Face Forgery Detection"

amphion icon amphion

Amphion (/æmˈfaɪən/) is a toolkit for Audio, Music, and Speech Generation. Its purpose is to support reproducible research and help junior researchers and engineers get started in the field of audio, music, and speech generation research and development.

anima icon anima

33B Chinese LLM, DPO QLORA, 100K context, AirLLM 70B inference with single 4GB GPU - Test thu

animateddrawings icon animateddrawings

Code to accompany "A Method for Animating Children's Drawings of the Human Figure"

animatezero icon animatezero

Official PyTorch implementation for the paper "AnimateZero: Video Diffusion Models are Zero-Shot Image Animators"

anylabeling icon anylabeling

Effortless AI-assisted data labeling with AI support from Segment Anything and YOLO!

ao2-detr icon ao2-detr

AO2-DETR: Arbitrary-Oriented Object Detection Transformer

arc2face icon arc2face

Arc2Face: A Foundation Model of Human Faces

athina-evals icon athina-evals

Python SDK for running evaluations on LLM generated responses

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