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cs.LG2026
Uni-FinLLM: A Unified Multimodal Large Language Model with Modular Task Heads for Micro-Level Stock Prediction and Macro-Level Systemic Risk Assessment
Gongao Zhang, Haijiang Zeng, Lu Jiang
Financial institutions and regulators require systems that integrate heterogeneous data to assess risks from stock fluctuations to systemic vulnerabilities. Existing approaches oft…
cs.LG2025
A Mathematical Theory of Top- Sparse Attention via Total Variation Distance
Georgios Tzachristas, Lei Deng, Ioannis Tzachristas +2
We develop a unified mathematical framework for certified Top- attention truncation that quantifies approximation error at both the distribution and output levels. For a single…
cs.LG2025
HATA: Trainable and Hardware-Efficient Hash-Aware Top-k Attention for Scalable Large Model Inference
Ping Gong, Jiawei Yi, Shengnan Wang +13
Large Language Models (LLMs) have emerged as a pivotal research area, yet the attention module remains a critical bottleneck in LLM inference, even with techniques like KVCache to…