Belief Memory: Enhancing AI Agent Memory in Partial Observability
Discover BeliefMem, a probabilistic memory system boosting AI agents' decision-making under uncertainty and partial observability for superior performance.
AlphaCrafter: Adaptive Multi-Agent Quantitative Trading Framework
Discover AlphaCrafter, a full-stack multi-agent framework that adapts quantitative trading strategies to dynamic market conditions for superior returns.
Locality-Aware Private Class ID for Domain Adaptation
Discover a new locality-aware method for private class identification in domain adaptation, improving accuracy under extreme label shifts with ReOT.
LoPE Boosts LLM Reasoning by Prompt Space Perturbation
Discover how LoPE uses prompt space perturbation to overcome zero-advantage issues, enhancing reasoning in large language models.
BitCal-TTS: Boost Quantized Reasoning Model Accuracy
Discover BitCal-TTS, a novel method improving confidence calibration and stability in quantized reasoning models for better AI inference.