curriculum learning

Architect

Mar 9, 2025 · Artificial Intelligence

Experiments with Reinforcement Learning Fine‑Tuning of a 0.5B Qwen Model on the KK Dataset

The author reports a series of reinforcement‑learning‑based fine‑tuning experiments on a 0.5‑billion‑parameter Qwen‑0.5VB instruct model using the KK dataset, detailing reward design adjustments, curriculum‑style data scaling, observed convergence issues, and hypotheses about why small models fail to develop long reasoning chains.

LLM fine-tuningcurriculum learningreinforcement learning

0 likes · 11 min read

Experiments with Reinforcement Learning Fine‑Tuning of a 0.5B Qwen Model on the KK Dataset

DataFunTalk

Aug 24, 2023 · Artificial Intelligence

Multi-Agent Decision Large Models: Challenges, Action Semantic Networks, Permutation Invariance/Equivariance, and Automated Curriculum Learning

This talk outlines the fundamental challenges of multi‑agent decision large models, introduces three core design priors—action semantic networks, permutation invariance/equivariance, and cross‑task automated curriculum learning— and demonstrates how these concepts improve performance across diverse environments such as StarCraft, Neural‑MMO, and SMAC.

AIMulti-Agent Reinforcement Learningaction semantics

0 likes · 12 min read

Multi-Agent Decision Large Models: Challenges, Action Semantic Networks, Permutation Invariance/Equivariance, and Automated Curriculum Learning

Alimama Tech

Sep 7, 2022 · Artificial Intelligence

Curriculum-Guided Bayesian Reinforcement Learning for ROI-Constrained Real-Time Bidding

The paper presents a Curriculum‑Guided Bayesian Reinforcement Learning (CBRL) framework that models ROI‑constrained real‑time bidding as a partially observable constrained MDP, using hard‑margin indicator rewards and a curriculum of relaxed proxy problems to achieve fast, constraint‑satisfying, Bayes‑optimal policies that outperform existing methods on large‑scale industrial data.

Bayesian RLMDPROI constraint

0 likes · 15 min read

Curriculum-Guided Bayesian Reinforcement Learning for ROI-Constrained Real-Time Bidding

Youku Technology

Dec 2, 2021 · Artificial Intelligence

Hybrid Curriculum Learning for Emotion Recognition in Conversation

The paper introduces a hybrid curriculum learning framework that tackles emotion shift and confusing labels in emotion recognition in conversation by applying nested curriculum stages at both conversation and utterance levels, enabling a progressive easy‑to‑hard training that markedly boosts classic ERC model performance across four public datasets and is already deployed in Alibaba’s entertainment AI brain script health‑check service.

AI applicationsEmotion RecognitionNatural Language Processing

0 likes · 2 min read

Hybrid Curriculum Learning for Emotion Recognition in Conversation

DataFunTalk

Mar 20, 2019 · Artificial Intelligence

Addressing Sparse Reward Problems in Model-Free Reinforcement Learning

This article reviews the challenges of model‑free reinforcement learning, especially sparse reward issues exemplified by Montezuma’s Revenge, and surveys recent approaches such as expert demonstrations, curriculum learning, self‑play, hierarchical reinforcement learning, and count‑based exploration to mitigate these problems.

curriculum learningexplorationhierarchical RL

0 likes · 12 min read

Addressing Sparse Reward Problems in Model-Free Reinforcement Learning