记忆专场金句：ChatGPT 记错旅行，上下文学习赢过专用记忆，改推理就让任务完成率从22%提到60%。
在记忆与持续学习专场，演讲者举例称 ChatGPT 认为 Shlok Khemani 在 2025 年去过土耳其，但他从未去，模型只是读过他犹豫要不要去的对话，无法识别记录冲突。在首个真实持续学习基准上，普通上下文学习击败了专用记忆系统。将策略自蒸馏扩展到 100 次工具调用后，教师模型的频繁纠正会让模型退化成一个劲说“maybe”。另一个实验里，教师不改动工具调用 token，只重塑调用前的推理，就把智能体任务完成率从 22% 提到 60%。演讲者还提醒，智能体不擅长发现异常，最好直接让它调查你已经发现的异常。
Memory talks on what happens after training stops: - ChatGPT thinks Shlok Khemani went to Turkey in...
Memory talks on what happens after training stops: - ChatGPT thinks Shlok Khemani went to Turkey in 2025. He never did. It read a conversation where he was deciding whether to go, and it still cannot tell that its own record conflicts - On the first real continual learning benchmark, plain in context learning beat the dedicated memory systems - Scale on policy self distillation to a hundred tool calls and the teacher course corrects so often the model collapses into saying "maybe" - A teacher moved an agent from finishing 22% of its tasks to 60% without ever changing the tool call tokens. It only reshaped the reasoning leading up to the call - Agents are bad at finding anomalies. Ask them to investigate the anomalies you already found Watch the Memory & Continual Learning track: youtube.com/watch?v=iqloyW… 💬 0 🔄 0 ❤️ 1 👀 261 ⚡