3 papers
cs.LG2026
Meta-Learning Reinforcement Learning for Crypto-Return Prediction
Junqiao Wang, Zhaoyang Guan, Guanyu Liu +7
Predicting cryptocurrency returns is notoriously difficult: price movements are driven by a fast-shifting blend of on-chain activity, news flow, and social sentiment, while labeled…
cs.CL2026
Entropy-Gated Branching for Efficient Test-Time Reasoning
Xianzhi Li, Ethan Callanan, Abdellah Ghassel +1
Test-time compute methods can significantly improve the reasoning capabilities and problem-solving accuracy of large language models (LLMs). However, these approaches require subst…
cs.CL2026
Detect, Explain, Escalate: Sustainable Dialogue Breakdown Management for LLM Agents
Abdellah Ghassel, Xianzhi Li, Xiaodan Zhu
Large Language Models (LLMs) have demonstrated substantial capabilities in conversational AI applications, yet their susceptibility to dialogue breakdowns poses significant challen…