Noise2Noise (N2N) trains denoisers on pairs of independently corrupted observations, eliminating clean references. We stress-test two natural conjectures about why the L1 loss outperforms L2 here. First, the hypothesis that the L1 loss confers robustness via parameter sparsity confuses the loss with Lasso regularizatio...
Ding-Yan Shang, Zhen-Yu Xu, You Wang et al.· 0 citations
An LLM-based CI/CD analysis pipeline that combines repository enrichment, anti-pattern detection, stage mining, and recommendation generation over a large GitHub corpus is presented, arguing for CI/CD observability that combines diagnosis, context, and human review.
Bo-Nan Shen, Jiazhou Gao, Tao Ning et al.· arXiv.org· 0 citations
Context masking is established as necessary for attributing early answer availability to an explanation rather than its hidden input when early-prefix evidence disappears after masking.
Bo-Nan Shen, Ding-Yan Shang, You Wang et al.· arXiv.org· 0 citations
ParEvalLayer, a decision layer that reads paired outcomes for two agent systems and a comparison policy chosen in advance, is introduced, a decision layer that reads paired outcomes for two agent systems and a comparison policy chosen in advance.
The results support truncated CoT auditing as a lightweight process-level diagnostic for answer-driven reasoning in math tutoring explanations and support truncated CoT auditing as a lightweight process-level diagnostic for answer-driven reasoning in math tutoring explanations.
Bo-Nan Shen, Ding-Yan Shang, You Wang et al.· 0 citations
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