diff --git a/docs/local-model-uncertainty/README.ja.md b/docs/local-model-uncertainty/README.ja.md new file mode 100644 index 0000000..7182497 --- /dev/null +++ b/docs/local-model-uncertainty/README.ja.md @@ -0,0 +1,358 @@ +# 汎用のローカルモデルは、不確かな問いにどう答えるか：`jev.*` の挙動と聞き方の指針 + +技術報告（2026年10月） + +## 要約 + +`MultiOutputScript (Jev)` は、TypeSafe の Jev の代わりに、ローカルの GGUF モデルで判断を行える。この報告は、答えのわからない問いに対して、Jev、Clef-Flash、汎用モデル（Qwen3.5-9B）がどう答えるかを比べ、汎用モデルを使うときの聞き方を調べたものである。 + +- 答えのわかる問いでは、3つのモデルの答えはほぼ一致した。 +- 答えのわからない問いでは、振る舞いが分かれた。五分五分の問いに `jev.noul` で「真ですか？」と聞くと、平均は Jev が 0.44、Clef-Flash が 0.31、Qwen3.5-9B が 0.06 だった。 +- Qwen3.5-9B の低い値は、「起こる確率が低い」ではなく「真だとは言えない」を表している。確率が 0.92 の主張にも 0.02 と答えた。 +- 主張とその否定形の両方に聞き、2つの答えをまとめると、Qwen3.5-9B でも五分五分の問いが 0.51 になった。 +- 確率の段階を選ばせる（`jev.score`）と、確率の高さがある程度取り出せた。結果は、段階の作り方と並び順に左右された。 +- 「偽ですか？」と質問を反対向きにする方法は、否定形の代わりにならなかった。 + +31組62文の小さな試験であり、段階で聞く方法は Qwen3.5-9B の1つの量子化でしか試していない。わかるのは傾向である。 + +## 1. 目的 + +判断モデルの出力は、しきい値で区切って分岐に使うことが多い（`jev.yes(state, question, 0.5)` など）。このとき、判断材料が足りない入力が混ざると、モデルが「わからない」をどの値で表すかによって、分岐の結果が変わる。 + +この報告の目的は、次の2点を確かめることである。 + +1. 汎用のローカルモデルは、不確かな問いに対して、Jev とどう違う答え方をするか。 +2. その違いを、スクリプトの書き方（聞き方）でどこまで埋められるか。 + +確率で答えるモデルに期待する性質として、次の2つを基準にした。 + +- **基準1**：対になる主張の確率を足すと、1 になる。 +- **基準2**：五分五分の問いには、0.5 と答える。 + +## 2. 方法 + +### 2.1 モデル + +| モデル | 種類 | 答えの出し方 | +| --- | --- | --- | +| Jev | TypeSafe の判断モデル（API） | API が確率を返す | +| Clef-Flash | Qwen3.5-9B を判断用に追加学習したモデル（`ggml-org/Clef-Flash-GGUF`、Q8_0） | 判断専用の層が出す値を確率に直す | +| Qwen3.5-9B | 汎用の LLM（`unsloth/Qwen3.5-9B-GGUF`、Q8_0） | 選択肢の記号が次に出る確率を読む | + +汎用モデルでは、選択肢に記号を付けて示し（`jev.noul` なら A：Yes、B：No）、記号1文字だけで答えるよう指示する。文章は生成させず、次のトークンとして各記号が出る確率を読み、記号どうしの合計が 1 になるように直す。この方式は SemIf (OpenJev) と同じである。サンプリングをしないので、乱数のシードや温度の設定はない。較正はしていない。 + +指示文は次のとおりである。主張、質問、選択肢は、JSON にまとめて渡す。 + +```text +Apply the supplied criterion to the supplied evidence. Choose exactly one listed option. Respond with only its uppercase letter, with no explanation or reasoning. +``` + +3つとも、このノードの判定処理（v1.3.3）をそのまま使った。質問は1問ずつ送った。 + +### 2.2 設問 + +対になる主張を31組、合計62文用意した。主張と質問は英語である。一覧は [`data/items.json`](data/items.json) にある。 + +| グループ | 記号 | 組数 | 内容 | 例 | +| --- | --- | --- | --- | --- | +| 既知の事実 | K | 6 | 1つめが真、2つめが偽 | Paris is the capital of France. / ... of Germany. | +| ほぼ確実な未来 | N | 6 | 1つめがほぼ確実に起こる | The sun will rise tomorrow. / ... will not rise tomorrow. | +| 傾向のある未来 | T | 6 | 1つめが起こりやすいが、確実ではない | The S&P 500 index will be higher one year from now ... / lower ... | +| 五分五分の問い | U | 8 | どちらも約50% | The next coin I flip will land heads. / ... tails. | +| 確率のわかっている問い | P | 5 | 正しい確率が計算でわかる | The next roll of a fair six-sided die will show a 1.（1/6） / ... a number other than 1.（5/6） | + +K、N、T、U の26組は、3つのモデルすべてに聞いた。P の5組は、あとから Qwen3.5-9B だけに聞いた。 + +### 2.3 質問 + +| 記号 | 関数 | 質問 | 選択肢 | +| --- | --- | --- | --- | +| Q1 | `jev.noul` | Is this statement true? | Yes / No | +| Q2 | `jev.noul` | Is this statement more likely to be true than false? | Yes / No | +| F1 | `jev.noul` | Is this statement false? | Yes / No | +| S6 | `jev.score` | How likely is this statement to be true? | 0-10%、10-30%、30-50%、50-70%、70-90%、90-100% | +| S11 | `jev.score` | How likely is this statement to be true? | 0%、10%、…、100% | +| F6 | `jev.score` | How likely is this statement to be false? | S6 と同じ6段階 | + +Q1 と Q2 は3つのモデルに聞いた。F1、S6、S11、F6 は Qwen3.5-9B だけに聞いた。段階で聞く質問は、選択肢を低い順に並べた場合と、高い順に並べた場合の両方で聞いた。 + +対照として、Qwen3.5-9B に確率を数字で書かせた（20文）。指示は「What is the probability that the following statement is true? Answer with a single number from 0 to 100 (percent) and nothing else.」で、最も確率の高いトークンを順に選んで生成した。 + +### 2.4 指標 + +- **対の合計**：対の2つの主張への値の合計（基準1）。 +- **0.5 からのずれ**：五分五分の問い16文での、値と 0.5 の差の絶対値の平均（基準2）。 +- **誤差の平均**：確率のわかっている問い10文での、値と正しい確率の差の絶対値の平均。 +- **順位相関**：同じ10文での、値と正しい確率のスピアマンの順位相関。 +- **まとめた値**：（主張への値 ＋ 1 − 否定形への値）÷ 2。主張と否定形で足すと、必ず 1 になる。 +- **段階からの推定値**：各段階の値（S6 と F6 は段階の中央の 0.05、0.20、0.40、0.60、0.80、0.95、S11 はその点）を、モデルが各段階に付けた確率で重み付けした値。 + +まとめた値は、新しく測ったものではなく、測定済みの値から計算したものである。 + +## 3. 結果 + +### 3.1 3つのモデルの比較（Q1） + +値は Yes の確率の平均で、左が対の1つめ、右が2つめの主張である。 + +| グループ | Jev | Clef-Flash | Qwen3.5-9B | +| --- | --- | --- | --- | +| 既知の事実 | 0.92 / 0.03 | 0.95 / 0.02 | 0.99 / 0.01 | +| ほぼ確実な未来 | 0.88 / 0.07 | 0.86 / 0.11 | 0.85 / 0.13 | +| 傾向のある未来 | 0.58 / 0.37 | 0.62 / 0.36 | 0.07 / 0.08 | +| 五分五分の問い | 0.44 / 0.44 | 0.36 / 0.26 | 0.07 / 0.04 | + +| 指標 | Jev | Clef-Flash | Qwen3.5-9B | +| --- | --- | --- | --- | +| 対の合計：既知の事実 | 0.95 | 0.97 | 1.00 | +| 対の合計：ほぼ確実な未来 | 0.95 | 0.96 | 0.98 | +| 対の合計：傾向のある未来 | 0.95 | 0.98 | 0.15 | +| 対の合計：五分五分の問い | 0.88 | 0.62 | 0.11 | +| 0.5 からのずれ（五分五分の問い） | 0.06 | 0.22 | 0.44 | + +- 既知の事実は、3つとも12文すべてに正しい側の値を返した。 +- Jev は、五分五分の問い16文すべてに 0.34〜0.51 を返した。 +- Qwen3.5-9B は、不確かな主張のほぼすべてに No と答えた。未来のことをすべて No とするわけではなく、「明日、太陽は昇る」には 0.99 を返している。 +- Clef-Flash は、傾向のある未来では対の合計が 0.98 で、調整前の Qwen3.5-9B（0.15）と大きく違う。コインやサイコロのような問いでは 0.62 にとどまった（コイン投げは 0.16 / 0.10）。 + +Clef-Flash と Qwen3.5-9B では、答えの出し方も違う。2つの差が、重みの調整によるものか、答えの出し方によるものかは、この試験では分けられない。 + +Clef-Flash は、傾向のある未来で片方をはっきり選んだ（S&P 500 は 0.80 / 0.06。Jev は 0.53 / 0.31）。ただし、「来年の今日、東京で雨が降らない / 降る」には 0.09 / 0.81 と、実際の頻度とは逆向きの値を返し、「次の米大統領は就任時に50歳より上 / 下」には 0.81 / 0.71 と、両方に Yes と答えた。 + +### 3.2 Qwen3.5-9B の No は、何を表しているか + +**記号以外のトークンに確率が流れているわけではない。** 語彙全体の確率のうち、A と B が占める割合（SemIf の `allowed_token_mass`）を、62文 × Q1・Q2 の124問で記録した。 + +| | 最小 | 中央 | 最大 | +| --- | --- | --- | --- | +| A と B が占める割合 | 0.9971 | 0.9992 | 0.9999 | + +A・B 以外で最も確率が高かったトークンは「C」で、最大でも 0.15% だった。断りや説明の書き出しにあたるトークンは、上位10個に現れなかった。モデルは、B（No）をはっきり選んでいる。 + +**「わからない」と「ほぼ確実に起こらない」が、同じ値になる。** A と B のロジットの差（正なら Yes 寄り）の平均は、次のとおりである。 + +| 主張の種類 | ロジットの差 | 確率に直すと | +| --- | --- | --- | +| 真の事実 | ＋5.6 | 約 1.00 | +| ほぼ確実に起こる未来 | ＋2.9 | 約 0.95 | +| 傾向のある未来 | −3.0 | 約 0.05 | +| 五分五分の問い | −3.3 | 約 0.04 | +| ほぼ確実に起こらない未来 | −3.3 | 約 0.04 | +| 偽の事実 | −6.2 | 約 0.002 | + +**値は、確率の高さの順に並ばない。** 確率のわかっている問いへの Q1 の答えは、次のとおりである。10文での順位相関は −0.38 だった。 + +| 主張 | 正しい確率 | Q1 の値 | +| --- | --- | --- | +| トランプでエースを引く | 0.08 | 0.03 | +| サイコロで1が出る | 0.17 | 0.02 | +| トランプでハートを引く | 0.25 | 0.03 | +| サイコロで3〜6が出る | 0.67 | 0.35 | +| トランプでハート以外を引く | 0.75 | 0.02 | +| サイコロで1以外が出る | 0.83 | 0.01 | +| トランプでエース以外を引く | 0.92 | 0.02 | + +Qwen3.5-9B は、「真ですか？」に対して、「確実に真だと言えるか」という基準で答えていると考えられる。出てくる値は、出来事の確率ではなく、No という答えへの自信である。値の中に確率の高さの情報がないので、Q1 の値を後から直して確率にすること（較正）は難しい。 + +### 3.3 質問文を変える（Q2） + +質問を「偽であるより真である可能性のほうが高いですか？」に変えると、次のようになった。 + +- Jev と Clef-Flash は、Q1 とほぼ同じ傾向だった。 +- Qwen3.5-9B は、「すべて No」ではなくなった。確率のわかっている問いでは、10文中8文で正しい側（0.5 より上か下か）を選んだ。 +- ただし、Qwen3.5-9B の値は 0 か 1 に近く、確率の程度を表さない。五分五分の問いは、問いごとに Yes か No のどちらかに振れた（0.02〜0.99、0.5 からのずれは 0.36）。 + +汎用モデルの答えは、質問の言い回しに強く左右される。 + +### 3.4 主張と否定形の両方に聞く + +Qwen3.5-9B は、Q1 で「ほぼ確実に起こる」には Yes、「わからない」には No と答える。区別できないのは、「わからない」と「ほぼ確実に起こらない」である。後者の否定形は「ほぼ確実に起こる」なので、否定形にも聞けば区別できる。 + +| 主張の種類 | 主張への答え | 否定形への答え | +| --- | --- | --- | +| ほぼ確実に起こる | Yes | No | +| ほぼ確実に起こらない | No | Yes | +| わからない | No | No | + +設問は対で作ってあるので、対の相手を否定形とみなして、まとめた値を計算した（Q1）。かっこ内は、主張だけを聞いたときの値である。 + +| グループ | Jev | Clef-Flash | Qwen3.5-9B | +| --- | --- | --- | --- | +| 既知の事実 | 0.95（0.92） | 0.96（0.95） | 0.99（0.99） | +| ほぼ確実な未来 | 0.90（0.88） | 0.88（0.86） | 0.86（0.85） | +| 傾向のある未来 | 0.60（0.58） | 0.63（0.62） | 0.49（0.07） | +| 五分五分の問い | 0.50（0.44） | 0.55（0.36） | 0.51（0.07） | + +| 0.5 からのずれ（五分五分の問い） | Jev | Clef-Flash | Qwen3.5-9B | +| --- | --- | --- | --- | +| 主張だけ | 0.06 | 0.22 | 0.44 | +| 否定形と合わせる | 0.006 | 0.053 | 0.015 | + +Qwen3.5-9B について、2つの答えを 0.5 で区切って「真 / 偽 / わからない」に分けると、31組中29組が期待どおりになった。 + +- 既知の事実と、ほぼ確実な未来（12組）：10組が「真」。 +- 傾向のある未来、五分五分の問い、確率のわかっている問い（19組）：19組すべてが「わからない」。 + +外れた2組は、「来年1月に札幌で雪が降る / 降らない」（両方に No）と、「皆既日食が5年以内に起こる / 起こらない」（両方に Yes）である。両方に Yes という答えは、その答えが信頼できないことの目印になる。 + +この方法では、確率の程度は取り出せない。確率が 0.08 の主張も 0.92 の主張も、まとめた値は 0.5 付近になる（確率のわかっている問いでの誤差の平均は 0.244、順位相関は −0.12）。 + +### 3.5 確率の段階を選ばせる + +以下は、Qwen3.5-9B だけの結果である。 + +**対照：数字で書かせると、ほぼ正確である。** 確率のわかっている10文での誤差の平均は 0.003 だった（たとえば、正しい確率 7.7% に「9」、16.7% に「16.67」、92.3% に「92」）。コイン投げには「50」と答えた。モデルは確率の知識を持っている。Q1 で確率の高さが出ないのは、聞き方による。 + +**段階で聞くと、確率の高さがある程度出る。** 確率のわかっている10文での結果は、次のとおりである。 + +| 聞き方 | 順位相関 | 誤差の平均 | +| --- | --- | --- | +| Q1（Yes / No） | −0.38 | — | +| S6、低い順 | ＋0.88 | 0.095 | +| S6、高い順 | ＋0.76 | 0.208 | +| S11、低い順 | ＋0.77 | 0.202 | +| S11、高い順 | ＋0.80 | 0.203 | +| 数字で書かせる | ＋1.00 | 0.003 | + +**6段階の幅（S6）と11段階の点（S11）は、得意な点が違う。** + +| 指標 | S6 | S11 | +| --- | --- | --- | +| 0.5 からのずれ（五分五分の問い、低い順 / 高い順） | 0.118 / 0.140 | 0.027 / 0.029 | +| 並び順による推定値の差（62文の平均） | 0.087 | 0.042 | +| 対の合計：既知の事実（並び順2通りの平均） | 1.07 | 1.03 | +| 対の合計：ほぼ確実な未来（同上） | 1.14 | 1.04 | + +- S6 は、五分五分の問いが約 0.60 になった。50% が「30-50%」と「50-70%」の境目にあたり、モデルが16文中14文で「50-70%」を選んだためである。これは、段階の区切り方の問題である。 +- S6 は、並び順に強く左右された。「ハート以外を引く」（正しくは 0.75）は、低い順で 0.75、高い順で 0.24 だった。 +- S11 は、五分五分の問い16文中14文が 0.50 になり、対の合計も 1 に近い。主張だけを聞いても、基準1と基準2をほぼ満たす。 +- S11 は、確率の程度がほとんど出ない。モデルが、確実でない主張のほとんどに「50%」を選ぶためである。確率が 0.25 の「ハートを引く」にも、0.75 の「ハート以外を引く」にも、「50%」を選んだ。 + +「50%」という選択肢があると、五分五分の問いには正しく答えられるが、確実でない問いがそこに集まる。S11 は、「真 / 偽 / わからない」の3つに分ける方法に近い働きをする。 + +**6段階の幅を、主張と否定形の両方に聞くと、両方に対応できる。** + +| 聞き方（S6） | 0.5 からのずれ | 誤差の平均 | 順位相関 | +| --- | --- | --- | --- | +| 低い順、主張だけ | 0.118 | 0.095 | ＋0.88 | +| 低い順、否定形と合わせる | 0.027 | 0.069 | ＋0.90 | +| 高い順、否定形と合わせる | 0.034 | 0.148 | ＋0.92 | + +五分五分の問いのずれは、主張にも否定形にも同じ向きに出るので、まとめると打ち消し合う。段階は低い順に並べるほうがよい。 + +| 主張 | 正しい確率 | 主張だけ | 否定形と合わせる | +| --- | --- | --- | --- | +| トランプでエースを引く | 0.08 | 0.06 | 0.13 | +| サイコロで1が出る | 0.17 | 0.05 | 0.19 | +| トランプでハートを引く | 0.25 | 0.32 | 0.29 | +| コイン2回とも表 | 0.25 | 0.06 | 0.12 | +| サイコロで1か2が出る | 0.33 | 0.53 | 0.44 | + +### 3.6 「偽ですか？」は、否定形の代わりにならない + +否定形を書く代わりに、主張はそのままにして、質問を反対向きにする方法（F1、F6）を試した。まとめた値は、「（Q1 の値 ＋ 1 − F1 の値）÷ 2」で計算した。 + +| グループ | 否定形の主張と合わせる | F1 と合わせる | +| --- | --- | --- | +| 既知の事実 | 0.99 | 0.99 | +| ほぼ確実な未来 | 0.86 | 0.87 | +| 傾向のある未来 | 0.49 | 0.36 | +| 五分五分の問い | 0.51 | 0.42 | + +| 指標 | 否定形の主張と合わせる | 「偽」の質問と合わせる | +| --- | --- | --- | +| 0.5 からのずれ（Yes / No） | 0.015 | 0.109 | +| 0.5 からのずれ（6段階、低い順） | 0.027 | 0.072 | +| 誤差の平均（6段階、低い順） | 0.069 | 0.146 | + +確実な問いでは差がない。崩れるのは、不確かな問いである。Qwen3.5-9B は、不確かな主張に「真ですか？」と聞くとほぼ必ず No と答えるが、「偽ですか？」には Yes と答えることがあった（「コインは裏が出る」に、Q1 は 0.03、F1 は 0.60）。不確かな主張を「真だ」とは言わないが、「偽だ」とは言いやすい。 + +否定形の主張が効くのは、同じ質問文で聞くので、質問文による偏りが両方に同じようにかかり、打ち消し合うためと考えられる。 + +### 3.7 聞き方のまとめ（Qwen3.5-9B） + +| 聞き方 | 五分五分を 0.5 に | 確率の程度 | 否定形を書く | 質問の数 | +| --- | --- | --- | --- | --- | +| Yes / No、主張だけ | できない | 出ない | 不要 | 1 | +| Yes / No、否定形と合わせる | できる | 出ない | 必要 | 2 | +| 11段階の点、主張だけ | できる | ほぼ出ない | 不要 | 1 | +| 6段階の幅、主張だけ | ずれる（約 0.60） | ある程度出る | 不要 | 1 | +| 6段階の幅、否定形と合わせる | できる | ある程度出る | 必要 | 2 | +| 「偽」の質問と合わせる | ずれる | 出ない | 不要 | 2 | +| 数字で書かせる | できる | 出る | 不要 | 文章の生成が必要 | + +## 4. 汎用モデルを使うときの指針 + +以上から、汎用のローカルモデルで `jev.*` を使うスクリプトについて、次のように言える。 + +1. **`jev.noul` や `jev.yes` の低い値を、「起こりにくい」と読まない。** 「真だとは言えない」を含む。判断材料が足りない入力は、ほぼ常に No 側に分岐する。 +2. **「真 / 偽 / わからない」がわかればよいなら、11段階の点で1回聞く。** +3. **Yes / No で聞くなら、主張と否定形の両方に聞く。** 両方が No なら「わからない」、両方が Yes なら「信頼できない答え」として扱う。 +4. **確率の程度も知りたいなら、6段階の幅を低い順に並べ、主張と否定形の両方に聞く。** +5. **否定形は、主張として書く。** 質問を「偽ですか？」に変える方法は、代わりにならない。 +6. **聞きたいことを、そのまま質問文にする。** 「真か」と「起こりやすいほうか」では、答えが大きく変わる。 +7. **モデルを替えたら、しきい値を見直す。** 同じスクリプトでも、Jev、Clef-Flash、汎用モデルで、不確かな入力の分岐が変わる。 + +主張と否定形の両方に聞く例： + +```python +# it1: 主張、it2: その否定形 +a = jev.noul(it1, "Is this statement true?") +b = jev.noul(it2, "Is this statement true?") +ov1 = (a + 1 - b) / 2 + +if a < 0.5 and b < 0.5: + ot1 = "unsure" +elif a >= 0.5 and b >= 0.5: + ot1 = "contradiction" +elif a >= 0.5: + ot1 = "true" +else: + ot1 = "false" +``` + +11段階の点で聞く例。`jev.score` は選ばれた段階の番号の期待値（0〜10）を返すので、10 で割ると 0〜1 の値になる。 + +```python +levels = ["0%", "10%", "20%", "30%", "40%", "50%", "60%", "70%", "80%", "90%", "100%"] +ov1 = jev.score(it1, "How likely is this statement to be true?", levels) / 10 +``` + +6段階の幅では、段階の中央の値が等間隔でないので、`jev.score` の値を 5 で割っても、3.5 節の推定値とは同じにならない。近似として使う場合は、その点に注意する。 + +## 5. 限界 + +- 31組62文の小さな試験である。確率のわかっている問いは5組10文だけで、聞き方の比較はこの少ない問いにもとづく。 +- モデルの優劣を評価したものではない。未来の問いには正解がなく、予測の正しさは測っていない。 +- 否定形と合わせる方法は、このデータを見て思いついたもので、同じデータで効果を確かめている。別の設問で確かめてはいない。 +- 設問の対は、厳密な否定になっていないものがある（「高い」と「低い」など）。否定形の作り方で、結果は変わりうる。 +- 段階で聞く方法（S6、S11）、否定形と合わせる方法の段階での効果、「偽」の質問（F1、F6）は、Qwen3.5-9B でしか試していない。Jev と Clef-Flash には聞いていない。 +- 段階の作り方は、2通りしか試していない。 +- 汎用モデルは Qwen3.5-9B の Q8_0 だけである。別のモデル、別の量子化、別の判定方式では、違う結果になりうる。 +- 汎用モデルの値は、較正をしていない。SemIf (OpenJev) は、用途ごとに較正して使うよう勧めている。 +- どの質問も1回ずつの測定である。ローカルのモデルの値は、サンプリングをしないので、同じ条件なら変わらない。Jev は、同じ質問でも値が少し変わる。五分五分の問い16文を Q1 で3回聞いたところ、値の幅は最大で 0.04 だった。 +- 主張と質問は英語である。ほかの言語では試していない。 + +## 6. データ + +[`data/`](data/) に、設問と結果を置いている。主張の ID は、対の記号に `a`（1つめ）か `b`（2つめ）を付けたものである（例：`U1a`）。 + +| ファイル | 内容 | +| --- | --- | +| `items.json` | 設問（`pairs`）、質問文（`questions`）、グループの説明（`groups`）、確率のわかっている問いの正しい確率（`probabilities`） | +| `results_jev.json` | Jev。Q1・Q2 の `p_yes`。五分五分の問いの Q1 は、`run` 1〜3 の3回分 | +| `results_clef_flash.json` | Clef-Flash。Q1・Q2 の `p_yes` | +| `results_qwen35.json` | Qwen3.5-9B。Q1・Q2 の `p_yes`（26組） | +| `results_qwen35_mass.json` | Qwen3.5-9B。Q1・Q2（31組）の `p_yes`、A と B のロジット、`allowed_token_mass`、確率の高い上位10トークン | +| `results_qwen35_score.json` | Qwen3.5-9B。S6 の段階ごとの確率（`score`）と、数字で書かせた対照の答え（`text`） | +| `results_qwen35_score11.json` | Qwen3.5-9B。S11 の段階ごとの確率 | +| `results_qwen35_false.json` | Qwen3.5-9B。F1 の `p_yes`（`noul`）と、F6 の段階ごとの確率（`score`） | + +段階ごとの確率（`p`）は、選択肢をどちらの順で示した場合も、低い段階から順に並べて保存している。`order` は、示した順である。 + +## 7. 測定の条件 + +- 実施日：2026年10月5日（3つのモデルの比較）、10月6日〜8日（Qwen3.5-9B の追加の測定） +- ノード：ComfyUI-ScriptFlow v1.3.3 +- Jev：TypeSafe API（typesafe-sdk 0.7.1）。API が返すモデル名は、2026年10月8日に確認した時点で `jev-1.13.0` だった。測定時（10月5日）のモデル名は記録していない。 +- ローカルのモデルの実行：llama-cpp-python 0.4.2（SYCL ビルド）、Windows 11 diff --git a/docs/local-model-uncertainty/data/items.json b/docs/local-model-uncertainty/data/items.json new file mode 100644 index 0000000..d58429b --- /dev/null +++ b/docs/local-model-uncertainty/data/items.json @@ -0,0 +1,182 @@ +{ + "questions": { + "Q1": "Is this statement true?", + "Q2": "Is this statement more likely to be true than false?" + }, + "groups": { + "U": "Unknowable, symmetric: each statement of a pair should be about 50%", + "T": "Future with a tendency: one statement of a pair is more likely, but not certain", + "N": "Future, near-certain: the first statement of a pair is almost sure", + "K": "Known facts (control): the first statement of a pair is true, the second false", + "P": "Known probability: the statement has an exact probability, listed under probabilities" + }, + "pairs": [ + [ + "U1", + "The next coin I flip will land heads.", + "The next coin I flip will land tails." + ], + [ + "U2", + "The next roll of a fair six-sided die will show an even number.", + "The next roll of a fair six-sided die will show an odd number." + ], + [ + "U3", + "The next card I draw from a well-shuffled standard deck will be red.", + "The next card I draw from a well-shuffled standard deck will be black." + ], + [ + "U4", + "A fair spinner with two equal halves labelled A and B will land on A on its next spin.", + "A fair spinner with two equal halves labelled A and B will land on B on its next spin." + ], + [ + "U5", + "The last digit of the next winning lottery number will be even.", + "The last digit of the next winning lottery number will be odd." + ], + [ + "U6", + "A person chosen at random from the world's population was born in the first half of the year.", + "A person chosen at random from the world's population was born in the second half of the year." + ], + [ + "U7", + "The number of grains of sand on the nearest beach is even.", + "The number of grains of sand on the nearest beach is odd." + ], + [ + "U8", + "The next ball drawn from a bag holding five white and five black balls will be white.", + "The next ball drawn from a bag holding five white and five black balls will be black." + ], + [ + "T1", + "The S&P 500 index will be higher one year from now than it is today.", + "The S&P 500 index will be lower one year from now than it is today." + ], + [ + "T2", + "The price of Bitcoin will be higher one year from now than it is today.", + "The price of Bitcoin will be lower one year from now than it is today." + ], + [ + "T3", + "It will not rain in Tokyo on this day next year.", + "It will rain in Tokyo on this day next year." + ], + [ + "T4", + "The next FIFA World Cup will be won by a European team.", + "The next FIFA World Cup will be won by a team from outside Europe." + ], + [ + "T5", + "The men's 100 metres world record will not be broken within the next year.", + "The men's 100 metres world record will be broken within the next year." + ], + [ + "T6", + "The next person elected president of the United States will be older than 50 when taking office.", + "The next person elected president of the United States will be younger than 50 when taking office." + ], + [ + "N1", + "The sun will rise tomorrow.", + "The sun will not rise tomorrow." + ], + [ + "N2", + "The world's population will be larger one year from now than it is today.", + "The world's population will be smaller one year from now than it is today." + ], + [ + "N3", + "An earthquake of magnitude 6 or greater will occur somewhere in the world during the next year.", + "No earthquake of magnitude 6 or greater will occur anywhere in the world during the next year." + ], + [ + "N4", + "It will snow in Sapporo at some point next January.", + "It will not snow in Sapporo at any point next January." + ], + [ + "N5", + "Next year will have 365 or 366 days.", + "Next year will have 400 days." + ], + [ + "N6", + "The next total solar eclipse visible from Earth will occur within the next five years.", + "No total solar eclipse will be visible from Earth during the next five years." + ], + [ + "K1", + "Paris is the capital of France.", + "Paris is the capital of Germany." + ], + [ + "K2", + "Water boils at 100 degrees Celsius at sea level.", + "Water boils at 50 degrees Celsius at sea level." + ], + [ + "K3", + "In April 1986, a reactor at the Chernobyl nuclear power plant exploded, and people were killed.", + "No one was killed in the accident at the Chernobyl nuclear power plant in April 1986." + ], + [ + "K4", + "The potato blight of the 1840s led to a famine in Ireland in which about one million people died.", + "No famine occurred in Ireland during the 1840s." + ], + [ + "K5", + "A 1964 report by the US Surgeon General found that smoking causes lung cancer.", + "The 1964 report by the US Surgeon General on smoking found no evidence that smoking harms health." + ], + [ + "K6", + "The Earth orbits the Sun.", + "The Sun orbits the Earth." + ], + [ + "P1", + "The next roll of a fair six-sided die will show a 1.", + "The next roll of a fair six-sided die will show a number other than 1." + ], + [ + "P2", + "The next card I draw from a well-shuffled standard deck will be a heart.", + "The next card I draw from a well-shuffled standard deck will not be a heart." + ], + [ + "P3", + "The next card I draw from a well-shuffled standard deck will be an ace.", + "The next card I draw from a well-shuffled standard deck will not be an ace." + ], + [ + "P4", + "The next roll of a fair six-sided die will show a 1 or a 2.", + "The next roll of a fair six-sided die will show a 3, 4, 5, or 6." + ], + [ + "P5", + "The next two flips of a fair coin will both land heads.", + "The next two flips of a fair coin will not both land heads." + ] + ], + "probabilities": { + "P1a": 0.1667, + "P1b": 0.8333, + "P2a": 0.25, + "P2b": 0.75, + "P3a": 0.0769, + "P3b": 0.9231, + "P4a": 0.3333, + "P4b": 0.6667, + "P5a": 0.25, + "P5b": 0.75 + } +} \ No newline at end of file diff --git a/docs/local-model-uncertainty/data/results_clef_flash.json b/docs/local-model-uncertainty/data/results_clef_flash.json new file mode 100644 index 0000000..2e4495b --- /dev/null +++ b/docs/local-model-uncertainty/data/results_clef_flash.json @@ -0,0 +1,626 @@ +[ +{ +"id": "U1a", +"q": "Q1", +"run": 1, +"p_yes": 0.1563546622523346 +}, +{ +"id": "U1b", +"q": "Q1", +"run": 1, +"p_yes": 0.10298498607890458 +}, +{ +"id": "U2a", +"q": "Q1", +"run": 1, +"p_yes": 0.27531802064465766 +}, +{ +"id": "U2b", +"q": "Q1", +"run": 1, +"p_yes": 0.29130223232773783 +}, +{ +"id": "U3a", +"q": "Q1", +"run": 1, +"p_yes": 0.596886783643548 +}, +{ +"id": "U3b", +"q": "Q1", +"run": 1, +"p_yes": 0.3328182831349319 +}, +{ +"id": "U4a", +"q": "Q1", +"run": 1, +"p_yes": 0.4135071008052303 +}, +{ +"id": "U4b", +"q": "Q1", +"run": 1, +"p_yes": 0.25353891261846645 +}, +{ +"id": "U5a", +"q": "Q1", +"run": 1, +"p_yes": 0.3597190663096565 +}, +{ +"id": "U5b", +"q": "Q1", +"run": 1, +"p_yes": 0.3477136050354511 +}, +{ +"id": "U6a", +"q": "Q1", +"run": 1, +"p_yes": 0.6314669640969492 +}, +{ +"id": "U6b", +"q": "Q1", +"run": 1, +"p_yes": 0.3741538921045834 +}, +{ +"id": "U7a", +"q": "Q1", +"run": 1, +"p_yes": 0.31978838456545733 +}, +{ +"id": "U7b", +"q": "Q1", +"run": 1, +"p_yes": 0.2546097220836936 +}, +{ +"id": "U8a", +"q": "Q1", +"run": 1, +"p_yes": 0.15263059327321835 +}, +{ +"id": "U8b", +"q": "Q1", +"run": 1, +"p_yes": 0.13091564626756208 +}, +{ +"id": "T1a", +"q": "Q1", +"run": 1, +"p_yes": 0.803736698937114 +}, +{ +"id": "T1b", +"q": "Q1", +"run": 1, +"p_yes": 0.056274844577240885 +}, +{ +"id": "T2a", +"q": "Q1", +"run": 1, +"p_yes": 0.3678579990777839 +}, +{ +"id": "T2b", +"q": "Q1", +"run": 1, +"p_yes": 0.37329297956124446 +}, +{ +"id": "T3a", +"q": "Q1", +"run": 1, +"p_yes": 0.08927474404407679 +}, +{ +"id": "T3b", +"q": "Q1", +"run": 1, +"p_yes": 0.8137230093194368 +}, +{ +"id": 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