From the 1 of 12 linked papers with an AI index.
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FinSMART: Financial Sentiment Analysis for Algorithmic Trading through Market-Aligned Reinforcement Learning
Giorgos Iacovides, Wuyang Zhou, Danilo Mandic
FinSMART is a reinforcement‑learning framework that trains financial sentiment analysis models directly on realized market outcomes, enabling adaptive sentiment signals for algorit…
Tensorizing Engram: Sharing Latents Across N-Gram Embeddings is Beneficial in LLMs
Wuyang Zhou, Yuxuan Gu, Giorgos Iacovides +3
Modern language models represent text using discrete token-level embeddings, which forces recurring multi-token patterns to be learned implicitly across Transformer layers. Both Ov…
KromHC: Manifold-Constrained Hyper-Connections with Kronecker-Product Residual Matrices
Wuyang Zhou, Yuxuan Gu, Giorgos Iacovides +1
The success of Hyper-Connections (HC) in neural networks (NN) has also highlighted issues related to training instability and restricted scalability. The Manifold-Constrained Hyper…
FinDPO: Financial Sentiment Analysis for Algorithmic Trading through Preference Optimization of LLMs
Giorgos Iacovides, Wuyang Zhou, Danilo Mandic
Opinions expressed in online finance-related textual data are having an increasingly profound impact on trading decisions and market movements. This trend highlights the vital role…
TensorLLM: Tensorising Multi-Head Attention for Enhanced Reasoning and Compression in LLMs
Yuxuan Gu, Wuyang Zhou, Giorgos Iacovides +1
The reasoning abilities of Large Language Models (LLMs) can be improved by structurally denoising their weights, yet existing techniques primarily focus on denoising the feed-forwa…