Recall Initiator

Recall, in the context of machine learning and artificial intelligence, refers to a system's ability to retrieve relevant information from its memory, whether that memory is explicitly stored or implicitly encoded within model parameters. Current research focuses on improving recall in various applications, including trajectory prediction, multimodal embedding retrieval, and large language model (LLM) performance, often employing techniques like contrastive decoding, memory arrays, and hybrid loss functions to enhance accuracy and efficiency. These advancements are crucial for improving the performance and reliability of AI systems across diverse fields, from autonomous driving to e-commerce and medical device safety, by enabling more effective use of past experiences and knowledge.

Papers

September 4, 2023

Probabilistic Precision and Recall Towards Reliable Evaluation of Generative Models
Dogyun Park, Suhyun Kim
Generative Model Recall Initiator State of the Art Generative New Metric

July 20, 2023

Parse and Recall: Towards Accurate Lung Nodule Malignancy Prediction like Radiologists
Jianpeng Zhang, Xianghua Ye, Jianfeng Zhang, Yuxing Tang, Minfeng Xu, Jianfei Guo, Xin Chen, Zaiyi Liu, Jingren Zhou, Le Lu, Ling Zhang
Contextual Information Document Parsing Recall Initiator Radiologist Annotation Lung Nodule Malignancy Contextual Structure

July 11, 2023

Grid Cell-Inspired Fragmentation and Recall for Efficient Map Building
Jaedong Hwang, Zhang-Wei Hong, Eric Chen, Akhilan Boopathy, Pulkit Agrawal, Ila Fiete
Procedural Content Generation Long Term Memory Recall Initiator Inspired Fragmentation Large Scale Exploration Static Map

July 6, 2023

RecallM: An Adaptable Memory Mechanism with Temporal Understanding for Large Language Models
Brandon Kynoch, Hugo Latapie, Dwane van der Sluis
Question Answering Long Term Memory Recall Initiator Temporal Understanding

May 9, 2023

Completeness, Recall, and Negation in Open-World Knowledge Bases: A Survey
Simon Razniewski, Hiba Arnaout, Shrestha Ghosh, Fabian Suchanek
Timely Survey Knowledge Graph Open World Knowledge Base Knowledge Representation Recall Initiator Probabilistic Completeness

March 30, 2023

Recognition, recall, and retention of few-shot memories in large language models
A. Emin Orhan
Large Language Model Recognition Rate Memory Trace Episodic Memory Recall Initiator Customer Retention Visual Memory

March 19, 2023

Two Kinds of Recall
Yoav Goldberg
Different Type Recall Initiator Neural Method Pattern Based Method

December 18, 2022

Recall, Expand and Multi-Candidate Cross-Encode: Fast and Accurate Ultra-Fine Entity Typing
Chengyue Jiang, Wenyang Hui, Yong Jiang, Xiaobin Wang, Pengjun Xie, Kewei Tu
Entity Mention Prompt Expansion Recall Initiator Cross Encoder Ultra Fine Entity Typing Type Prediction Bounded Recall

September 29, 2022

RECALL: Rehearsal-free Continual Learning for Object Classification
Markus Knauer, Maximilian Denninger, Rudolph Triebel
Convolutional Neural Network Deep Neural Network Continual LEArning Object Recognition Object Classification Recall Initiator Unseen Category Rehearsal Free Continual Learning

September 22, 2022

CAMRI Loss: Improving Recall of a Specific Class without Sacrificing Accuracy
Daiki Nishiyama, Kazuto Fukuchi, Youhei Akimoto, Jun Sakuma
Loss Function Cross Entropy Loss Multi Class Classification Class Specific Recall Initiator Angular Margin Loss Penalty Based

June 21, 2022

Early Recall, Late Precision: Multi-Robot Semantic Object Mapping under Operational Constraints in Perceptually-Degraded Environments
Xianmei Lei, Taeyeon Kim, Nicolas Marchal, Daniel Pastor, Barry Ridge, Frederik Schöller, Edward Terry, Fernando Chavez, Thomas Touma, Kyohei Otsu, Ali Agha
Non Humanoid Robot Multi Robot Multidimensional Local Precision Rate Recall Initiator Semantic Object Operational Constraint Multi Robot Active Mapping

April 18, 2022

AB/BA analysis: A framework for estimating keyword spotting recall improvement while maintaining audio privacy
Raphael Petegrosso, Vasistakrishna Baderdinni, Thibaud Senechal, Benjamin L. Bullough
New Framework Semi Supervised Recall Initiator Multi Word Keywords Keyword Enrollment Complementary Information Speech Privacy

Recall Initiator

Papers

Probabilistic Precision and Recall Towards Reliable Evaluation of Generative Models

Parse and Recall: Towards Accurate Lung Nodule Malignancy Prediction like Radiologists

Grid Cell-Inspired Fragmentation and Recall for Efficient Map Building

RecallM: An Adaptable Memory Mechanism with Temporal Understanding for Large Language Models

Completeness, Recall, and Negation in Open-World Knowledge Bases: A Survey

Recognition, recall, and retention of few-shot memories in large language models

Two Kinds of Recall

Recall, Expand and Multi-Candidate Cross-Encode: Fast and Accurate Ultra-Fine Entity Typing

RECALL: Rehearsal-free Continual Learning for Object Classification

CAMRI Loss: Improving Recall of a Specific Class without Sacrificing Accuracy

Early Recall, Late Precision: Multi-Robot Semantic Object Mapping under Operational Constraints in Perceptually-Degraded Environments

AB/BA analysis: A framework for estimating keyword spotting recall improvement while maintaining audio privacy