bowen-upenn

AnyText

Official implementation code of the paper <AnyText: Multilingual Visual Text Generation And Editing>

Awesome-LLM-Reasoning

Reasoning in Large Language Models: Papers and Resources, including Chain-of-Thought, Instruction-Tuning and Multimodality.

CCD

[ICCV2023] Self-supervised Character-to-Character Distillation for Text Recognition

CFR_VQA

Coarse-to-Fine Reasoning for Visual Question Answering (CVPRW'22)

llm_token_bias

This is the official implementation of the paper "A Peek into Token Bias: Large Language Models Are Not Yet Genuine Reasoners" in PyTorch.

MMMA_Rationality

This is the official repository of the paper "Multi-Modal and Multi-Agent Systems Meet Rationality: A Survey"

Multi-Agent-VQA

Multi-Agent VQA: Exploring Multi-Agent Foundation Models on Zero-Shot Visual Question Answering

Rethinking-Text-Segmentation

[CVPR 2021] Rethinking Text Segmentation: A Novel Dataset and A Text-Specific Refinement Approach

scene_graph_commonsense

This is the official implementation of the paper "Enhancing Scene Graph Generation with Hierarchical Relationships and Commonsense Knowledge" in PyTorch.

BundleTrack2.0

bowen-upenn/scene_graph_commonsense

This is the official implementation of the paper "Enhancing Scene Graph Generation with Hierarchical Relationships and Commonsense Knowledge" in PyTorch.

bowen-upenn/MMMA_Rationality

This is the official repository of the paper "Multi-Modal and Multi-Agent Systems Meet Rationality: A Survey"

bowen-upenn/Multi-Agent-VQA

Multi-Agent VQA: Exploring Multi-Agent Foundation Models on Zero-Shot Visual Question Answering

bowen-upenn/llm_token_bias

This is the official implementation of the paper "A Peek into Token Bias: Large Language Models Are Not Yet Genuine Reasoners" in PyTorch.

bowen-upenn/AnyText

Official implementation code of the paper <AnyText: Multilingual Visual Text Generation And Editing>

bowen-upenn/Awesome-LLM-Reasoning

Reasoning in Large Language Models: Papers and Resources, including Chain-of-Thought, Instruction-Tuning and Multimodality.

bowen-upenn/CCD

[ICCV2023] Self-supervised Character-to-Character Distillation for Text Recognition

bowen-upenn/CFR_VQA

Coarse-to-Fine Reasoning for Visual Question Answering (CVPRW'22)

bowen-upenn/Rethinking-Text-Segmentation

[CVPR 2021] Rethinking Text Segmentation: A Novel Dataset and A Text-Specific Refinement Approach

bowen-upenn/SeeAct

[ICML'24] SeeAct is a system for generalist web agents that autonomously carry out tasks on any given website, with a focus on large multimodal models (LMMs) such as GPT-4V(ision).

bowen-upenn/unilm

Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities

bowen-upenn/VLSAT

CVPR2023 : VL-SAT: Visual-Linguistic Semantics Assisted Training for 3D Semantic Scene Graph Prediction in Point Cloud