4 papers · 1 filter
Noise2Noise Revisited: Training Pair Distributions Dominate Loss Choice in Self-Supervised Denoising
Dingyan Shang, Zhenyu Xu, Youting Wang +2
Noise2Noise (N2N) trains denoisers on pairs of independently corrupted observations, eliminating clean references. We stress-test two natural conjectures about why the L1 loss outp…
DACRI: Decision-Aware Causal Intervention Ranking for Critical Supply Chains
Shiqi Huang, Jiani He, Dingyan Shang +4
Detecting or attributing a supply-chain disruption is not the same as selecting the intervention that maximizes recoverable net value. We present CriticalSCM-Bench v1, a controlled…
Accuracy-Preserving Stability Regularization for Large-Scale Retail Demand Forecasting
Jize Li, Jiani He, Dishu Yang +3
Retail demand forecasts are reused across replenishment, capacity, labor, and transportation planning cycles. Point-error objectives do not constrain abrupt movement between adjace…
When LLM Reward Design Fails: Diagnostic-Driven Refinement for Sparse Structured RL
Youting Wang, Yuan Tang, Bowen Liu +2
For sparse, structured reinforcement-learning tasks with semantic reward-function interfaces, LLM-generated reward shaping is better framed as debugging than one-shot generation. W…