Benchmarking Graph Anomaly Detection for Real-World Use
Explore a new benchmark evaluating graph anomaly detection models on million-node graphs with scarce anomalies and missing data.
RRCM: Advanced Ranking for LLM-Based Recommendations
Discover RRCM, a ranking-driven retrieval framework enhancing LLM recommendations with collaborative and meta memories for precise, context-aware results.
Simple Graph Heuristic Uncovers Shortcut Benchmarks in Sequential Rec
Discover how a simple graph heuristic reveals shortcut-solvable benchmarks, challenging complex models in sequential recommendation systems.
Stabilized Neural HJB Solvers for Model-Based RL
Explore stabilized neural Hamilton-Jacobi-Bellman solvers with error analysis and applications in continuous-time model-based reinforcement learning.
MoLF: Hybrid LoRA & Full Fine-Tuning for LLMs
Discover MoLF, a hybrid framework combining LoRA and Full Fine-Tuning to boost Large Language Model adaptation and performance efficiently.