Wednesday, June 3: 5 frontier papers out of 298 read.
Papers rated as moving the field
How we choose“On Lean-IMO-Bench, LEAP boosts the one-shot formal solve rate of general-purpose LLMs from below 10% to 70%, notably surpassing the 48% benchmark set by a specialized, gold-medal-caliber IMO system.”
The authors, in the abstract
Supercharging LLMs for Formal Mathematics with Agentic Frameworks
“Across 61 checkpoint rows and 1920 row-level transitions, aggressive PPO has the highest localized reward-hacking rate (14.45%; bootstrap 95% CI: 10.16-18.75), while UP-PPO yields lower rates in the same aggressive regime (11.33-10.94%).”
“To evaluate reward-model robustness, we introduce RewardHackBench containing 13 reward-hacking patterns covering real life high-stakes domains and general settings, and we find severe failures on specific subcategories across eight reward models.”
“Our results demonstrate that self-sustaining AI-driven cyber-threats are no longer theoretical.”
May 28 – Jun 3: 185 cleared, 11 frontier
The week’s papers have not been sorted into fields yet.
Papers this week that name the model
Papers this week with an author at the lab
26 papers