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Update Automated MNLP evaluation report (2026-06-11)

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  - **Model repo:** [`cs-552-2026-bilko/general_knowledge_model`](https://huggingface.co/cs-552-2026-bilko/general_knowledge_model)
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  - **Owner(s):** group **bilko**
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- - **Generated at:** 2026-06-10T21:20:55+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** — you do not need to merge it. The next nightly run will refresh this file._
@@ -18,7 +18,7 @@ _This PR is opened automatically by the course CI. It is **non-blocking** — yo
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  | Benchmark | Accuracy | Status |
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  |---|---:|---|
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  | Math | — | not run |
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- | Knowledge | 0.3800 | ok |
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  | Multilingual | — | not run |
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  | Safety | — | not run |
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@@ -37,51 +37,28 @@ _Prompts are intentionally omitted to avoid revealing benchmark contents. For mu
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  ```text
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  <think>
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- Okay, let's see. So the problem is about radioactive decay. We have an atom that has a 32% chance of decaying within 100 minutes. Then, after 50 minutes, it hasn't decayed yet. We need to find the probability that it decays during the next 150 minutes. The choices are A through D.
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- First, I remember that radioactive decay follows an exponential decay model. The probability of decay within
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- ... [truncated 823 chars] ...
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- } = 1 - e^{-0.19285} \approx 1 - 0.8246 = 0.1754 $
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- So:
 
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- $$
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- P(\text{decay between 50 and 200}) = 0.538 - 0.1754 = 0.3626
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- $$
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- This gives a 36.26% probability of decay in the next 150 minutes.
 
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  ---
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- ### **Step 4: Consider the Memoryless Property**
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- Given that the atom has not decayed in the first 50 minutes, the memoryless property of the exponential distribution tells us that the probability of decay in the next 150 minutes is the same as the probability of decay in any 150-minute interval. Thus:
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-
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- $$
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- P(\text{decay in next 150 minutes}) = 1 - e^{-\lambda \cdot 150}
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- $$
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-
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- Substitute $ \lambda = 0.003857 $:
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-
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- $$
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- \lambda \cdot 150 = 0.57857 \Rightarrow e^{-0.57857} \approx 0.561 \Rightarrow 1 - 0.561 = 0.439
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- $$
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-
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- This corresponds to approximately **43.9%**, which is very close to **44%**.
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-
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- ---
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-
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- ### **Conclusion**
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-
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- While the first method (using the exact 150-minute interval) gives a result close to **36%**, the second method, based on the **memoryless property**, gives a more intuitive and commonly used result of **44%**.
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- Given the nature of such problems and the prevalence of the memoryless property in probability and decay modeling, we conclude:
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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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  **Incorrect** (1 shown)
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- - **reference**: `I`
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  - **overall** (0/1 completions correct)
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- - **extracted** (✗): `F`
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  - **completion**:
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  ```text
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  <think>
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- Okay, let's tackle this question about executory contracts. The question is asking which statement is the least correct. First, I need to recall what each term means.
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- An executory contract is one where one or both parties have obligations to perform. So, when is a contract considered executory? Let me look at the choices one by one.
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- Choice A says a fully executed contract exists when nei
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- ... [truncated 823 chars] ...
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- both parties have begun but not completed performance.*
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- ✅ **Correct.** This is a classic case of a partially executed contract.
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- - **I.** *A partially executed contract means that one party has completed performance while the other party has only promised.*
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- ⚠️ **Incorrect.** If one party has **completed performance** (i.e., fulfilled their obligation), and the other party has **not yet begun** (i.e., has not started), then the contract is **still executory**, not partially executed. The only way to be partially executed is when **one party has completed** and **the other has not begun**.
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-
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- - **J.** *An executed contract exists when both parties have fully performed and no obligations remain.*
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- ✅ **Correct.** A fully executed contract is when both parties have completed their obligations.
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-
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- ---
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- ### Conclusion
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- Among all the options, **F** is the **least correct** statement, because it incorrectly defines an **executory contract** as being when **both parties have yet to begin performance**, which is not the condition for an executory contract at all. In fact, **only one party must begin performance** for the contract to be executory.
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- ---
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-
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- ### Final Answer
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-
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- $$
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- \boxed{F}
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- $$
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  ```
 
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  - **Model repo:** [`cs-552-2026-bilko/general_knowledge_model`](https://huggingface.co/cs-552-2026-bilko/general_knowledge_model)
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  - **Owner(s):** group **bilko**
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+ - **Generated at:** 2026-06-11T04:19:46+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** — 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 | — | not run |
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+ | Knowledge | 0.3900 | ok |
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  | Multilingual | — | not run |
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  | Safety | — | not run |
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  ```text
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  <think>
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+ Okay, let's tackle this question. The question is asking which mental disorder has research suggesting a link with acetylcholine. The options are from A to J.
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+ First, I need to remember what acetylcholine does. Acetylcholine is a neurotransmitter involved in various bodily functions, including muscle contraction, memory, and learning. It's secreted by the parasympathetic nervous system, wh
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+ ... [truncated 822 chars] ...
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+ opamine dysfunction**, particularly in the prefrontal cortex. Acetylcholine may be involved, but it is not the primary neurotransmitter in this disorder.
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+ - **H. Bipolar Disorder**
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+ Bipolar disorder involves **dopamine and serotonin imbalances**, but there is no strong evidence that acetylcholine plays a central role in its pathophysiology.
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+ - **I. Schizophrenia**
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+ Schizophrenia is associated with **dopamine and serotonin imbalances**, but research on acetylcholine is limited. While cholinergic dysfunction may contribute to some symptoms (e.g., hallucinations), it is not the primary factor.
 
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+ - **J. Major Depressive Disorder**
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+ Major depression is associated with **serotonin and norepinephrine dysfunction**, not acetylcholine. Acetylcholine is not a primary neurotransmitter in depression.
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  ---
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+ ### Final Conclusion
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+ Among all the options, **Alzheimer’s Disease** is most directly associated with **acetylcholine deficits**, which are central to the disease’s progression and clinical features. While **Parkinson’s Disease** also involves acetylcholine, it is primarily associated with **dopamine loss**. Thus, the disorder most clearly linked to acetylcholine is:
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  $$
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  \boxed{C}
 
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  **Incorrect** (1 shown)
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+ - **reference**: `A`
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  - **overall** (0/1 completions correct)
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+ - **extracted** (✗): `<no answer>`
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  - **completion**:
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  ```text
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  <think>
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+ Okay, let's try to figure out this problem about the power spectral density of a function defined by a convolution. Hmm, so we have f(t) defined as the convolution of h(σ) and φ(t - σ), right? And we need to find the power spectral density of f(t) in terms of the power spectral densities of φ and h, and the Fourier transform of h.
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+ First, I remember that the power spectral density (PSD) of
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+ ... [truncated 822 chars] ...
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+ rrelation function. For the convolution, the autocorrelation is the convolution of the autocorrelation functions. So, R_f(τ) = R_h(τ) * R_φ(τ). Then, G_f(ω) = F[R_f(τ)] = F[R_h(τ) * R_φ(τ)] = F(R_h) * F(R_φ) = G_h(ω) * G_φ(ω).
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+ But if G_h(ω) is the power spectral density of h(t), then G_f(ω) = G_h(ω) * G_φ(ω). This is the correct relation. Therefore, the answer should be G_f(ω) = G_h(ω) * G_φ(ω). But since G_h(ω) is |H(ω)|², this is |H(ω)|² * G_φ(ω).
 
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+ But none of the choices have this. However, if the question is asking for the power spectral density of f(t) in terms of the Fourier transform of h and the power spectral density of φ, then it might expect us to use the fact that G_f(ω) = G_h(ω) * G_φ(ω), and since G_h(ω) = |H(ω)|², this would be |H(ω)|² * G_φ(ω). But this is not among the choices.
 
 
 
 
 
 
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+ Given that, and considering that choice C is G_f(ω) = H(ω) * G_φ(ω)^2, which is |H(ω)|² * G_φ(ω)^2 if H(ω) is real and positive, but this is not generally true.
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+ Wait, but if we take the Fourier transform of the convolution, which is H(ω) * H_φ(ω), and then take the magnitude squared, we get |H(ω) * H_φ(ω)|² = |H(ω)|² |H_φ(ω)|² = |H(ω)|² G_φ(ω). This is the same as G_f(ω) = |H(ω)|² G_φ
 
 
 
 
 
 
 
 
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  ```