Round 1: final-turn blame baseline

Autoresearch loop: 主 agent 读取数据和指标 → 诊断具体问题 → 决定 patch → 改代码/评测 → 生成本轮可视化。当前小说场景 AHEAD intentionally disabled。

Idea tested

Attribute delayed negative feedback to the most recent turn.

Diagnosed issues

Long-horizon round 1 dominant issue: temporal_credit_blame_errors.

Baseline round; no previous round exists yet.

Selected next patch

Move beyond final-turn blame by scanning trajectory-wide evidence and delayed-feedback text.

Data used this round

TRACE-USER-Bench synthetic delayed-feedback traces

One row per multi-turn episode: turn trace, utility/implicit feedback, delayed comment, gold culprit step/dimension, counterfactual repairs.

sample_count: 120 · splits: {"culprit_dimensions": {"lore_density": 27, "pacing": 35, "trope_misunderstanding": 32, "female_agency": 26}}

Evaluation protocol

Rank culprit steps from the full trace, compare top prediction and reciprocal rank to gold, then estimate counterfactual repair gain and confidence calibration.

Metric definitions

Metric	Definition
`culprit_step_accuracy`	Exact-match accuracy for the delayed-feedback culprit step.
`culprit_dimension_accuracy`	Accuracy for the causal preference/content dimension.
`credit_mrr`	Mean reciprocal rank of the gold culprit step.
`repair_gain`	Mean expected utility gain from the selected counterfactual repair.
`credit_calibration`	One minus confidence error; higher means confidence tracks correctness.

Metrics vs previous

Metric	Value	vs previous
culprit_step_accuracy	0.0000	baseline
culprit_dimension_accuracy	0.7917	baseline
credit_mrr	0.2863	baseline
repair_gain	0.0760	baseline
counterfactual_repair_gain	0.0760	baseline
credit_calibration	0.3800	baseline

Concrete problems found

trace_0000
step_miss:gold=6:pred=7, dimension_miss:gold=lore_density:pred=pacing
前面设定解释太密，后面节奏被拖住了。
trace_0004
step_miss:gold=4:pred=5, dimension_miss:gold=pacing:pred=female_agency
读到后面才发现前面铺垫太拖，剧情推进慢了。
trace_0008
step_miss:gold=4:pred=5, dimension_miss:gold=trope_misunderstanding:pred=pacing
那个误会梗埋得太早，后面解释让我出戏。
trace_0019
step_miss:gold=1:pred=7, dimension_miss:gold=trope_misunderstanding:pred=pacing
那个误会梗埋得太早，后面解释让我出戏。
trace_0022
step_miss:gold=1:pred=6, dimension_miss:gold=lore_density:pred=pacing
前面设定解释太密，后面节奏被拖住了。

Top failure examples

trace_0000 — step_miss:gold=6:pred=7, dimension_miss:gold=lore_density:pred=pacing
前面设定解释太密，后面节奏被拖住了。
trace_0004 — step_miss:gold=4:pred=5, dimension_miss:gold=pacing:pred=female_agency
读到后面才发现前面铺垫太拖，剧情推进慢了。
trace_0008 — step_miss:gold=4:pred=5, dimension_miss:gold=trope_misunderstanding:pred=pacing
那个误会梗埋得太早，后面解释让我出戏。
trace_0019 — step_miss:gold=1:pred=7, dimension_miss:gold=trope_misunderstanding:pred=pacing
那个误会梗埋得太早，后面解释让我出戏。
trace_0022 — step_miss:gold=1:pred=6, dimension_miss:gold=lore_density:pred=pacing
前面设定解释太密，后面节奏被拖住了。

Why zero-valued metrics appear

culprit_step_accuracy = 0 出现在 final-turn blame baseline：延迟反馈的真实 culprit 不在最后一步。

Research-state update

本轮将失败模式写回下一轮方法假设：Move beyond final-turn blame by scanning trajectory-wide evidence and delayed-feedback text.