LeArning Abstract

Learning, in the context of these papers, encompasses a broad range of research focused on improving the efficiency, robustness, and adaptability of machine learning models across diverse applications. Current efforts concentrate on developing novel self-supervised learning techniques, particularly for structured data like tabular formats, and on leveraging low-rank adaptations for efficient fine-tuning of large language and other foundation models. These advancements are significant because they address key challenges in data efficiency, computational cost, and the generalization capabilities of machine learning systems, impacting fields ranging from personalized medicine to autonomous robotics.

2549papers

Papers - Page 13

February 18, 2025

Learning To Explore With Predictive World Model Via Self-Supervised Learning
LeArning Abstract World Model Autonomous Software Agent Reward Function Complex Behavior
Fake It Till You Make It: Using Synthetic Data and Domain Knowledge for Improved Text-Based Learning for LGE Detection
Domain Knowledge LeArning Abstract Image Text Pair Cardiac Magnetic Resonance Synthetic Data
Tuning Algorithmic and Architectural Hyperparameters in Graph-Based Semi-Supervised Learning with Provable Guarantees
LeArning Abstract Semi Supervised Learning New Hyperparameter Hyper Parameter Provable Guarantee Automatic Tuning Graph Convolution
A Smooth Transition Between Induction and Deduction: Fast Abductive Learning Based on Probabilistic Symbol Perception
Successful Deduction Symbolic Reasoning Contrastive Meta Abduction Method LeArning Abstract Abductive Learning Abductive Reasoning Automatic Induction Strong Generalization
S²R: Teaching LLMs to Self-verify and Self-correct via Reinforcement Learning
Self Verification Positive Reinforcement LeArning Abstract Self Correction Medical LLM LLM Reasoning Complex Cognitive
Enhancing Semi-supervised Learning with Noisy Zero-shot Pseudolabels
LeArning Abstract Pseudo Label Zero Shot
Learning Transformation-Isomorphic Latent Space for Accurate Hand Pose Estimation
Estimation Task Hand Pose LeArning Abstract Latent Space Pose Estimation W Net Representation Learning Vision Backbone
Savaal: Scalable Concept-Driven Question Generation to Enhance Human Learning
Question Generation LLM Prompt LeArning Abstract Large Language Model High Quality Question

February 17, 2025

Towards Fusing Point Cloud and Visual Representations for Imitation Learning
Point Cloud Robotics Benchmark LeArning Abstract Imitation Learning Feature Imitation Visual Representation
Learning to Reason at the Frontier of Learnability
New Frontier Reason Giving LeArning Abstract Complex Reasoning Task Reinforcement Learning Language Model
Learning in a Multifield Coherent Ising Machine
Learning Rule LeArning Abstract Ising Machine Physical Computing Long Term Memory
Learning to Keep a Promise: Scaling Language Model Decoding Parallelism with Learned Asynchronous Decoding
LeArning Abstract Asynchronous Learning Autoregressive Large Language Model Promise
Medical Image Registration Meets Vision Foundation Model: Prototype Learning and Contour Awareness
LeArning Abstract Vision Foundation Model Anatomical Shape Visual Prototype Contour Initialization Anatomy Aware Medical Image Registration
\textsc{FLAG-Trader}: Fusion LLM-Agent with Gradient-based Reinforcement Learning for Financial Trading
LeArning Abstract FINancial Task Reinforcement Learning Multimodal Data Financial Trading Language Processing Large Language Model

February 16, 2025

Learning to Reason from Feedback at Test-Time
User Feedback Human Feedback LeArning Abstract Length Generalization Reasoning Datasets Reason Giving

February 15, 2025

SEM-CLIP: Precise Few-Shot Learning for Nanoscale Defect Detection in Scanning Electron Microscope Image
Segmentation Result LeArning Abstract SEM Image Segmentation Accuracy Wafer Defect
Breast Lump Detection and Localization with a Tactile Glove Using Deep Learning
Breast Tissue Breast Cancer Detection Localization Focus Dielectric Elastomer LeArning Abstract

LeArning Abstract

Papers - Page 13

Learning To Explore With Predictive World Model Via Self-Supervised Learning

Fake It Till You Make It: Using Synthetic Data and Domain Knowledge for Improved Text-Based Learning for LGE Detection

Tuning Algorithmic and Architectural Hyperparameters in Graph-Based Semi-Supervised Learning with Provable Guarantees

A Smooth Transition Between Induction and Deduction: Fast Abductive Learning Based on Probabilistic Symbol Perception

S²R: Teaching LLMs to Self-verify and Self-correct via Reinforcement Learning

Enhancing Semi-supervised Learning with Noisy Zero-shot Pseudolabels

Learning Transformation-Isomorphic Latent Space for Accurate Hand Pose Estimation

Savaal: Scalable Concept-Driven Question Generation to Enhance Human Learning

Towards Fusing Point Cloud and Visual Representations for Imitation Learning

Learning to Reason at the Frontier of Learnability

Learning in a Multifield Coherent Ising Machine

Learning to Keep a Promise: Scaling Language Model Decoding Parallelism with Learned Asynchronous Decoding

Medical Image Registration Meets Vision Foundation Model: Prototype Learning and Contour Awareness

\textsc{FLAG-Trader}: Fusion LLM-Agent with Gradient-based Reinforcement Learning for Financial Trading

Learning to Reason from Feedback at Test-Time

SEM-CLIP: Precise Few-Shot Learning for Nanoscale Defect Detection in Scanning Electron Microscope Image

Breast Lump Detection and Localization with a Tactile Glove Using Deep Learning

Balancing the Scales: A Theoretical and Algorithmic Framework for Learning from Imbalanced Data

Unknown Word Detection for English as a Second Language (ESL) Learners Using Gaze and Pre-trained Language Models

SPIRIT: Short-term Prediction of solar IRradIance for zero-shot Transfer learning using Foundation Models

LeArning Abstract

Papers - Page 13

Learning To Explore With Predictive World Model Via Self-Supervised Learning

Fake It Till You Make It: Using Synthetic Data and Domain Knowledge for Improved Text-Based Learning for LGE Detection

Tuning Algorithmic and Architectural Hyperparameters in Graph-Based Semi-Supervised Learning with Provable Guarantees

A Smooth Transition Between Induction and Deduction: Fast Abductive Learning Based on Probabilistic Symbol Perception

S2R: Teaching LLMs to Self-verify and Self-correct via Reinforcement Learning

Enhancing Semi-supervised Learning with Noisy Zero-shot Pseudolabels

Learning Transformation-Isomorphic Latent Space for Accurate Hand Pose Estimation

Savaal: Scalable Concept-Driven Question Generation to Enhance Human Learning

Towards Fusing Point Cloud and Visual Representations for Imitation Learning

Learning to Reason at the Frontier of Learnability

Learning in a Multifield Coherent Ising Machine

Learning to Keep a Promise: Scaling Language Model Decoding Parallelism with Learned Asynchronous Decoding

Medical Image Registration Meets Vision Foundation Model: Prototype Learning and Contour Awareness

\textsc{FLAG-Trader}: Fusion LLM-Agent with Gradient-based Reinforcement Learning for Financial Trading

Learning to Reason from Feedback at Test-Time

SEM-CLIP: Precise Few-Shot Learning for Nanoscale Defect Detection in Scanning Electron Microscope Image

Breast Lump Detection and Localization with a Tactile Glove Using Deep Learning

Balancing the Scales: A Theoretical and Algorithmic Framework for Learning from Imbalanced Data

Unknown Word Detection for English as a Second Language (ESL) Learners Using Gaze and Pre-trained Language Models

SPIRIT: Short-term Prediction of solar IRradIance for zero-shot Transfer learning using Foundation Models

S²R: Teaching LLMs to Self-verify and Self-correct via Reinforcement Learning