Thought space explorer: Navigating and expanding thought space for large language model reasoning
Recent advances in large language models (LLMs) have demonstrated their potential in
handling complex reasoning tasks, which are usually achieved by constructing a thought …
handling complex reasoning tasks, which are usually achieved by constructing a thought …
DFlow: Diverse Dialogue Flow Simulation with Large Language Models
[PDF][PDF] Towards Robust Multi-Modal Federated Learning with Hierarchical Representation Fusion
J Anderson - 2025 - researchgate.net
Federated Learning (FL) has emerged as a promising decentralized machine learning
paradigm, allowing multiple clients to collaboratively train a shared model while preserving …
paradigm, allowing multiple clients to collaboratively train a shared model while preserving …
[PDF][PDF] Enhancing Federated Learning on Non-IID Data with Cross-Modal Gradient Synchronization
H Peter - 2025 - researchgate.net
Federated Learning (FL) has emerged as a promising solution for decentralized model
training, but its effectiveness is significantly hindered by Non-Independent and Identically …
training, but its effectiveness is significantly hindered by Non-Independent and Identically …
Improving Language Model Self-Correction Capability with Meta-Feedback
X Li, Y Zhang, L Wang - openreview.net
Large language models (LLMs) are capable of self-correcting their responses by generating
feedback and refining the initial output. However, their performance may sometimes decline …
feedback and refining the initial output. However, their performance may sometimes decline …