[2026/06/01 ~ 07] AI/ML Papers Worth Reading This Week

To improve LLM agent efficiency, research is underway to externalize state management (Harness-1, AdaCoM) or compile complex workflows directly into model weights (Latent Agents), reducing inference cost and token usage.

There are also notable attempts to overcome the limitations of Transformer architecture. SISA injects SSM importance signals into attention to improve retrieval performance, while research on QKV variants presents optimization approaches that significantly reduce the KV cache while maintaining performance.

Research on system robustness and adaptability is also worth noting. MOSS addresses self-evolution through source code rewriting, and FuzzingBrain V2 covers vulnerability detection using multi-agents. Additionally, AdvGame approaches safety alignment through game theory, and Plan, Watch, Recover proposes a proactive assistant that intervenes in real time when a user deviates from a procedure.