最新模型

新模型、開放權重、多模態、語音、影像與模型架構。

AI 研究

CritICL Turns Small-Model Failure Modes Into a Prompt Library, Bringing Single-Generation Performance Close to Multi-Sample Test-Time Compute

CritICL first catalogs small-model errors, failure types, and critiques offline, then adds relevant examples to a large model’s prompt instead of repeatedly sampling for every question. The authors report slightly higher accuracy than self-consistency on Qwen2.5 math benchmarks, but the cost of building the library offline and the unreleased code limit reproducibility.

代理工具

PILOT Lets Supervisory Agents Reroute Mid-Task and Write Execution Experience Back into Persistent Skills in Real Time

PILOT connects a supervisor and a worker agent through a bidirectional channel, allowing the former to provide guidance or terminate an erroneous path before a long-running task is complete. The authors report improved accuracy and token efficiency across three agent benchmarks, but its “self-improvement” updates only the harness, skills, and memory—not the model parameters.

代理工具

PRAXIST Preserves Experimental Causality Across Generations With Evidence Graphs, Cuts MLE-bench Model Costs to About One-Twelfth of Baseline

PRAXIST has multiple research agents propose changes over successive generations, then records evaluation results, mechanisms, and lineage in an auditable evidence graph to avoid restarting exploration in every round. Its authors report 60 medals across 75 MLE-bench tasks at a model cost of $3,054, but the newly released system’s performance and costs have so far been measured primarily by its development team.

最新模型

TTPO Routes Positive and Negative Trajectories by Majority Vote, Enabling Models to Update at Test Time Without Ground-Truth Answers

Rather than treating the majority-vote answer as ground truth, TTPO distills trajectories that agree with the consensus and uses grouped reinforcement learning to penalize high-confidence disagreements. The authors report that Qwen3-1.7B’s Avg@12 across three mathematics competitions rises from 38.0 to 45.2, though this remains a transductive setting in which parameters are updated directly on the test problems.