Up in the Air, Split on the Ground: STAR-RIS vs. RIS in 3D Networks
A mechanism-first reading of why aerial STAR-RIS does not simply dominate RIS: in 3D wireless networks, altitude, distance, and orientation decide the winner.
A mechanism-first reading of why aerial STAR-RIS does not simply dominate RIS: in 3D wireless networks, altitude, distance, and orientation decide the winner.
A mechanism-first reading of the Agent Capability Problem: how information, cost, and uncertainty can help decide whether an AI agent should proceed, approximate, redesign, or stop.
A mechanism-first reading of DEMOCRITUS, a system that turns LLM-generated causal fragments into navigable causal maps without pretending they are validated causal truth.
A comparison-based reading of PPO, GRPO, and DAPO that shows why RL fine-tuning for reasoning is less about algorithmic fashion and more about managing instability, shortcuts, and evaluation boundaries.
ReasonBENCH shows why LLM reasoning systems should be evaluated as cost-quality distributions, not single benchmark scores.
Shopee’s CompassMax-V3-Thinking paper shows that scaling RL for giant MoE models is less about buying more rollouts and more about making every rollout produce usable learning signal.
A mechanism-first reading of TROJail, showing why multi-turn jailbreak risk is less about one bad prompt than about trajectory-level strategy, sparse credit assignment, and semantic drift.
SymPyBench shows why scientific AI evaluation needs executable ground truth, controlled variants, and robustness metrics beyond headline accuracy.
A close reading of how a GPT-5-based correctness checker turns scientific paper auditing from artisanal peer-review labor into a scalable quality-control workflow.
A comparison-based reading of how a multimodal oncology agent turns generated clinical reports into measurable predictive signal for IDH1 mutation status in low-grade glioma.