Papers

AI papers from arXiv and journals, each with a summary and why it matters · 7704 papers
Nov 5
PapersBuildersSelected11:08
Priors Beat Policies in LLM Test-Time Compute Allocation

The practical shift is that budget allocation is an information problem: gains come from knowing which inputs are solvable, not from a smarter scheduling rule. Teams running batched evaluation or inference can redirect effort from fancy policies toward building verifier plus prior pipelines. The stated requirement — prior rank correlation above roughly 0.3 to 0.55 and rare false acceptances — gives a concrete feasibility check before deploying such methods.

Event
arXiv cs.LG@Jinhyung Bae2 sourcesSource
Nov 4
PapersBuildersSelected14:04
Adversarial Speculative Reasoning Boosts Long-Horizon Agent Accuracy

Speculative decoding is usually tuned for speed, so the finding that acceptance choices can silently shift reasoning accuracy across long agent runs is a practical surprise. Developers building multi-step agents can adopt this training trick to improve reliability without touching the target model's weights or outputs. The parameter cost — under 0.3% — makes it feasible even for teams serving open-weight models.

arXiv cs.AI@Hongyin Luo et al. (8)Source