Popular GitHub Repositories for Claim Ambiguity

Links to conference/journal publications in automated fact-checking (resources for the TACL22/EMNLP23 paper).

Lightweight and Interpretable ML Model for Speech Emotion Recognition and Ambiguity Resolution (trained on IEMOCAP dataset)

LiteFlowNet3: Resolving Correspondence Ambiguity for More Accurate Optical Flow Estimation, ECCV 2020

NotPixel automatic claim and paint bot? easy to use without extras.

Auto chat, leave, join discord server, delete, reaction messages with AI. [100 STARS TO ENABLE AUTO CHAT WITH AI]

This project aims to emulate some of the advanced reasoning capabilities seen in models like OpenAI's o1. It does not claim to replicate the exact functionality or performance of o1.

[CVPR 2024] Confronting Ambiguity in 6D Object Pose Estimation via Score-Based Diffusion on SE(3)

Auto connect wallet, referrals, chat with AI.

This is the code repo of our CVPR2021 on protecting the IPR of Generative Adversarial Networks (GANs) from Ambiguity Attack

Fact-checking system for textual and visual inputs.

Automation for Pixai.art auto claim credits

Auto do tasks, play games, referrals, checkin.

Insurance claim fraud detection using machine learning algorithms.

Official Implementation of Our Paper "X as Supervision: Contending with Depth Ambiguity in Unsupervised Monocular 3D Pose Estimation"

GLM, Neural Network and Gradient Boosting for Insurance Pricing, Part 1: Claim Frequency

Towards Ambiguity-Free Spatial Foundation Model: Rethinking and Decoupling Depth Ambiguity

Code for the paper "On the Ambiguity of Rank-Based Evaluation of Entity Alignment or Link Prediction Methods" (https://arxiv.org/abs/2002.06914)

The most popular databases used in multimodal emotion recognition with a focus on the representation of emotion ambiguity.

Successfully established a machine learning model which can estimate the net health insurance claim of an individual based on a set of characteristics of that individual to an appreciable level of accuracy.

A retrieval-augmented generation-based framework for automatically constructing a hierarchy of aspects typically considered when addressing a nuanced claim and enriching them with corpus-specific perspectives.