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cs.LG2026
CODEBLOCK: Learning to Supervise Code at the Right Granularity
Zhijie Deng, Ling Li, Jinlong Pang +5
Supervised fine-tuning of code LLMs typically applies uniform cross-entropy loss to all response tokens, implicitly assuming that every token provides equally useful learning signa…
cs.LG2026
Do VLMs Truly "Read" Candlesticks? A Multi-Scale Benchmark for Visual Stock Price Forecasting
Kaiqi Hu, Linda Xiao, Shiyue Xu +2
Vision-language models(VLMs) are increasingly applied to visual stock price forecasting, yet existing benchmarks inadequately evaluate their understanding of stock price in candles…