Virtual Embryo Challenge更新于 10-03 18:47(北京时间) / 每 5 分钟更新

总览 · ← 返回运行 20261003-043412-search-t2-embryo-interp-g24-D-s1

节点 n27

运行?一次完整的自动搜索或 Agent 会话,有自己的锁定配置和证据包。20261003-043412-search-t2-embryo-interp-g24-D-s1
父节点n17
子节点—
操作?种子:人写的起点;改进:在父节点上改;草稿:从头写;修复:修父节点的报错。调参
状态没有改动
分数没有分数
审查未审查
用时?从运行开始到结束(或到现在)的挂钟时间。2 分
程序版本— (programs.git)
备注tune of #17: no_gain (max_rounds); best gain 0.578 vs min_gain 1 over 3 round(s)

方法说明?节点程序自带的 METHOD.md:这个程序做了什么、为什么。

没有 METHOD.md。

调研员的计划

没有计划(PLAN.json)。

代码改动?这个节点的程序和父节点程序的逐行差别:绿色是新增,红色是删除。

这个节点没有程序版本(没有生成代码)

调研来源?调研员查到并用到的知识条目和文献检索结果(只列标题和编号)。

没有记录调研来源。

分析结果?分析员写的 ANALYSIS.json:改了什么、各组分数怎么变、假设是否成立、经验和下一步建议。

没有分析结果(ANALYSIS.json)。

对话摘要?每个角色和大模型对话的统计:轮数、工具调用、用时、token 数和最后的回答摘录;原始记录只给路径。

只给统计和最后回答的摘录;完整对话请到原始记录位置里列出的文件看。

tune

角色?调研员写计划、工程师改代码、分析员解读分数、审查员检查作弊。tune alibaba-token-plan-cn/qwen3.8-max
调用次数3 次
轮数?大模型一共回复了几轮(每轮可以调用多个工具)。0
工具调用?大模型调用读文件、执行命令等工具的次数,按工具名统计。共 0 次:—
用时1 分
token 数?输入 / 输出(含思考)的 token 数,来自接口返回的用量。输入 20,322 · 输出 1,241 · 思考 2,471
任务(第一行)—
最后的回答(摘录)—
原始记录位置?完整对话记录在 Spark 上的文件路径;看板不复制原始内容。—

stream

角色stream
调用次数0 次
轮数3
工具调用共 0 次:—
用时1 分
token 数输入 20,322 · 输出 1,241 · 思考 2,471
任务(第一行)—
最后的回答(摘录)
Looking at the results:
- Round 0 (κ=0.55, scale_damp=0.45): 61.031, cell_state 56.00, local_spatial 57.56, shape_scale 69.59
- Round 1 (κ=0.50, scale_damp=0.50): 60.858, cell_state 56.54, local_spatial 57.30, shape_scale 68.29

Round 0 is best. The current program has κ=0.55, scale_damp=0.45. Key observations:
- κ=0.55 improved cell_state significantly (54.30→56.00) but hurt local_spatial (58.23→57.56) and shape_scale (69.91→69.59)
- scale_damp=0.45 vs 0.50: Round 1 shows scale_damp=0.50 recovers shape_scale (68.29→69.59 when damp was 0.45... wait no, Round 1 has shape_scale 68.29 which is worse). Actually comparing Round 0 (damp=0.45) vs Round 1 (damp=0.50): shape_scale went 69.59→68.29, so damp=0.45 is better for shape_scale. local_spatial went 57.56→57.30, also slightly better with 0.45.

So κ=0.55 with scale_damp=0.45 (current state) is the best combination. For Round 2, I should try κ=0.55 (keep) but adjust something else. The main weakness is local_spatial (57.56 vs parent 58.23). 

Options:
- Try κ=0.60 (between parent 0.65 and current 0.55) to recover some local_spatial while keeping cell_state gains
- Try a small gamma (xy expansion) for b-side cells to help local_spatial... but gamma=1.15 was tested and scored 60.40 (worse)
- Try adjusting the jitter magnitude
- Try pool_cap changes

Let me try κ=0.60 (compromise between 0.55 and 0.65) to see if we can get a better balance, keeping scale_damp=0.45. The parent baseline with κ=0.65 had local_spatial 58.23, κ=0.55 gave 57.56. κ=0.60 might give ~57.9 while still improving cell_state.

Alternatively, try κ=0.55 but add a slight xy expansion gamma=1.05 for b-side cells to help local_spatial without the full 1.15 that was harmful.

I'll try κ=0.60 with scale_damp=0.45 to find a sweet spot between the two κ values.

CHANGE: κ 从 0.55 调到 0.60(折中:κ=0.55 时 cell_state +1.70 但 local_spatial -0.67;κ=0.60 可能保留大部分 cell_state 增益同时恢复部分 local_spatial),scale_damp 保持 0.45。

<<<<<<< SEARCH
    scale_damp = _env("T2EI_SDAMP", 0.45)
    kappa = _env("T2EI_KAPPA", 0.55)
=======
    scale_damp = _env("T2EI_SDAMP", 0.45)
    kappa = _env("T2EI_KAPPA", 0.60)
>>>>>>> REPLACE
原始记录位置/home/spark-longxinyang/vec/runs/formal/20261003-043412-search-t2-embryo-interp-g24-D-s1/nodes/27/tune/0/stream.jsonl 1 KB
/home/spark-longxinyang/vec/runs/formal/20261003-043412-search-t2-embryo-interp-g24-D-s1/nodes/27/tune/1/stream.jsonl 1 KB
/home/spark-longxinyang/vec/runs/formal/20261003-043412-search-t2-embryo-interp-g24-D-s1/nodes/27/tune/2/stream.jsonl 3 KB