56 lines
2.5 KiB
Markdown
56 lines
2.5 KiB
Markdown
# Paper Insights
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status: seed
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这个文件沉淀论文阅读后的研究判断。单篇论文放在 `papers/items/`,这里记录跨论文的趋势和结论。
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## Current Snapshot
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- date: 2026-07-08
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- scope: Agent evaluation, memory, coding-agent benchmarks
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- papers reviewed: 6 starter items
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- caveat: sources are provisional; source approval workflow still needs user confirmation.
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## Strong Signals
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- Agent safety/eval 正在转向真实工具、多轮任务、trajectory、失败定位和系统级 guardrail。
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- Memory 不能只看事实召回;更重要的是是否改善流程执行和跨任务决策。
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- Coding-agent benchmark 正在从单 issue patch 转向长程软件演进和人机对话。
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- JD 高频词和论文趋势高度重合:memory、eval、planning/tool use、coding agent。
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## Weak or Unproven Claims
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- “加 memory 就更强”不成立;EvoMemBench 显示长上下文 baseline 很强,memory 价值依赖任务。
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- 单一 safety benchmark 不足以说明 Agent 安全;不同 benchmark 的方法差异可能改变结论。
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- SWE-Bench 类单点任务不足以代表真实 coding agent 生产力。
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## Mature Directions
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- Agent evaluation harness
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- Memory benchmark and memory architecture comparison
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- Coding agent benchmark beyond SWE-Bench
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- Agent failure diagnosis and trajectory analysis
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## Emerging Directions
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- Dialogue-driven coding agents
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- Stateful enterprise task benchmarks
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- Agent safety benchmark taxonomy
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- Skill/prompt optimization as trainable artifacts
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## Experiment Candidates
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| Idea | Related Papers | Metric | Notes |
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| --- | --- | --- | --- |
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| Mini Agent Safety Suite | OpenAgentSafety, Agent safety benchmark taxonomy | unsafe action rate, refusal precision, tool misuse | 选 10-20 个本地工具任务先跑 |
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| Memory vs Long Context | Memory survey, EvoMemBench, STATE-Bench | success rate, token cost, latency, contradiction rate | 必须包含 long-context baseline |
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| Long-horizon Coding Eval | SWE-EVO, Dialogue-SWEBench | task success, fix rate, clarification quality | 从真实 repo release notes 构造小任务 |
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| Failure Step Diagnosis | AgentRx, OpenAgentSafety | critical failure step accuracy | 需要统一 trace schema |
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## Links Back to Knowledge Base
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- docs to update: evaluation, memory, coding-agent, safety
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- experiments to create: memory comparison, mini safety suite, coding-agent eval
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- projects affected: future front-end/indexing project, coding-agent experiments
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- job skills connected: agent-evaluation, memory, coding-agent, tool-use, planning
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