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Update Automated MNLP evaluation report (2026-05-26)

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  1. EVAL_REPORT.md +17 -54
EVAL_REPORT.md CHANGED
@@ -2,7 +2,7 @@
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  - **Model repo:** [`cs-552-2026-mnlplus/general_knowledge_model`](https://huggingface.co/cs-552-2026-mnlplus/general_knowledge_model)
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  - **Owner(s):** group **mnlplus**
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- - **Generated at:** 2026-05-25T02:20:01+00:00 (UTC)
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  - **Pipeline:** [mnlp-project-ci](https://github.com/eric11eca/mnlp-project-ci)
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  _This PR is opened automatically by the course CI. It is **non-blocking** β€” you do not need to merge it. The next nightly run will refresh this file._
@@ -12,7 +12,7 @@ _This PR is opened automatically by the course CI. It is **non-blocking** β€” yo
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  | Benchmark | Accuracy | Status |
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  |---|---:|---|
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  | Math | β€” | not run |
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- | Knowledge | 0.2600 | ok |
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  | Multilingual | β€” | not run |
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  | Safety | β€” | not run |
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@@ -24,74 +24,37 @@ _Prompts are intentionally omitted to avoid revealing benchmark contents. For mu
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  **Correct** (1 shown)
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- - **reference**: `G`
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  - **overall** (1/1 completions correct)
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- - **extracted** (βœ“): `G`
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  - **completion**:
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  ```text
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  <think>
 
 
 
 
 
 
 
 
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  </think>
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- \boxed{G}
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  ```
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  **Incorrect** (1 shown)
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  - **reference**: `B`
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  - **overall** (0/1 completions correct)
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- - **extracted** (βœ—): `C`
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  - **completion**:
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  ```text
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  <think>
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- The user is asking about the volume integral of the divergence of a vector field over the interior of a sphere. The vector field is directed purely along the radial direction, and its magnitude decreases as 1/rΒ². The answer choices are given, and the task is to choose the most appropriate value for the integral.
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-
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- First, I need to recall the divergence theorem, which relates the volume inte
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-
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- ... [truncated 823 chars] ...
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-
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- ield $\vec{f}(r)$ is directed purely along the radial direction, meaning it points outward from the origin, and its magnitude decreases as $f(r) = \frac{1}{r^2}$. In spherical coordinates, this corresponds to a radial vector field.
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-
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- ---
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-
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- ### Step 2: Use the Divergence Theorem
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-
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- The divergence theorem relates the volume integral of the divergence of a vector field to the flux of the field through the surface of the region. It states:
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-
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- $$
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- \iiint_V (\nabla \cdot \vec{f}) \, dV = \iint_S \vec{f} \cdot d\vec{S}
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- $$
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-
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- where $V$ is the region enclosed by the surface $S$.
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-
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- ---
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-
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- ### Step 3: Compute the Divergence
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-
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- For a radial vector field in spherical coordinates, the divergence is:
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-
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- $$
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- \nabla \cdot \vec{f} = \frac{1}{r^2} \frac{d}{dr}(r^2 f(r)) = \frac{1}{r^2} \frac{d}{dr}(r^2 \cdot \frac{1}{r^2}) = \frac{1}{r^2} \frac{d}{dr}(1) = 0
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- $$
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-
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- Thus, the divergence of the vector field is **zero** everywhere except at the origin, where the field is undefined.
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-
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- ---
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-
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- ### Step 4: Evaluate the Volume Integral
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-
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- Since the divergence is zero everywhere, the volume integral of the divergence over any region is also zero:
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-
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- $$
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- \iiint_V (\nabla \cdot \vec{f}) \, dV = 0
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- $$
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-
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- ---
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-
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- ### Final Answer
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- $$
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- \boxed{C}
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- $$
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  ```
 
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  - **Model repo:** [`cs-552-2026-mnlplus/general_knowledge_model`](https://huggingface.co/cs-552-2026-mnlplus/general_knowledge_model)
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  - **Owner(s):** group **mnlplus**
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+ - **Generated at:** 2026-05-26T12:29:10+00:00 (UTC)
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  - **Pipeline:** [mnlp-project-ci](https://github.com/eric11eca/mnlp-project-ci)
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  _This PR is opened automatically by the course CI. It is **non-blocking** β€” you do not need to merge it. The next nightly run will refresh this file._
 
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  | Benchmark | Accuracy | Status |
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  |---|---:|---|
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  | Math | β€” | not run |
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+ | Knowledge | 0.4100 | ok |
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  | Multilingual | β€” | not run |
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  | Safety | β€” | not run |
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  **Correct** (1 shown)
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+ - **reference**: `I`
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  - **overall** (1/1 completions correct)
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+ - **extracted** (βœ“): `I`
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  - **completion**:
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  ```text
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  <think>
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+ To determine the probability of the event $\{M \geq 5\}$, we need to calculate the probability that $S_0 = 0$, $S_1 = 0$, $S_2 = 0$, $S_3 = 0$, $S_4 = 0$, and $S_5 = 0$.
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+ We can calculate the probability of each of these events as follows:
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+ - $P(S_0 = 0) = 1$
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+ - $P(S_1 = 0) = P(S_0 + 1 = 0) + P(S_0 - 1 = 0) = \frac{1}{4} + \frac{1}{4} = \frac{1}{2}$
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+ - $P(S_2 = 0) = P(S_1 + 1 = 0) + P(S_1 - 1 = 0) = \frac{1}{4} + \frac{1}{4} = \frac{1}{2}$
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+ - $P(S_3 = 0) = P(S_2 + 1 = 0) + P(S_2 - 1 = 0) = \frac{1}{4} + \frac{1}{4} = \frac{1}{2}$
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+ - $P(S_4 = 0) = P(S_3 + 1 = 0) + P(S_3 - 1 = 0) = \frac{1}{4} + \frac{1}{4} = \frac{1}{2}$
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+ - $P(S_5 = 0) = P(S_4 + 1 = 0) + P(S_4 - 1 = 0) = \frac{1}{4} + \frac{1}{4} = \frac{1}{2}$
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  </think>
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+ \boxed{I}
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  ```
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  **Incorrect** (1 shown)
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  - **reference**: `B`
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  - **overall** (0/1 completions correct)
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+ - **extracted** (βœ—): `D`
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  - **completion**:
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  ```text
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  <think>
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+ The correct answer is D.
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+ </think>
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ \boxed{D}
 
 
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  ```