挑战测试时训练新范式：用语言模型自监督的下一词预测信号作为内循环目标，无需额外损失函数。
arXiv:2606.21803v1 Announce Type: new Abstract: Next-token prediction is the self-supervised signal that trains language models, and every observed pr…
让大模型自主决定测试时计算如何分配，突破固定预算与策略的局限。
arXiv:2606.01667v1 Announce Type: new Abstract: Test-time scaling has become a major way to improve large language model reasoning, but its orchestrat…
提出请求专属测试时训练状态的批处理服务方法，助力大模型高效推理部署。
arXiv:2605.28053v1 Announce Type: new Abstract: Test-time training (TTT) adapts an LLM during generation by reading and updating request-owned state, …
探索测试时深度思考机制，让模型挖掘数据中的隐式规则，提升推理能力
arXiv:2605.24828v1 Announce Type: new Abstract: With the continuous advancement of Large Language Models (LLMs), intelligent agents are becoming incre…
将GUI批评从二元判断重构为连续语义对齐，提升智能体测试时扩展的排序能力
arXiv:2605.14311v1 Announce Type: cross Abstract: Test-Time Scaling (TTS), which samples multiple candidate actions and ranks them via a Critic Model,…