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cs.LG2026
Reasoning through Verifiable Forecast Actions: Consistency-Grounded RL for Financial LLMs
Jialin Chen, Aosong Feng, Harshit Verma +7
Financial markets are characterized by extreme non-stationarity, low signal-to-noise ratios, and strong dependence on external information such as news, company fundamentals, and m…
cs.LG2026
Parameter-Efficient Fine-Tuning of LLMs with Mixture of Space Experts
Buze Zhang, Jinkai Tao, Zilang Zeng +4
Large Language Models (LLMs) have achieved remarkable progress, with Parameter-Efficient Fine-Tuning (PEFT) emerging as a key technique for downstream task adaptation. However, exi…
cs.LG2026
Multi-Modal Time Series Prediction via Mixture of Modulated Experts
Lige Zhang, Ali Maatouk, Jialin Chen +3
Real-world time series exhibit complex and evolving dynamics, making accurate forecasting extremely challenging. Recent multi-modal forecasting methods leverage textual information…