activity
20202026
most citedLearning to Generate Explainable Stock Predictions using Self-Reflective Large Language Models

42 citations · 104 across the 22 of their papers we have counts for

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Showing 2025Show all

5 papers · 1 filter

q-fin.ST2025

Reasoning on Time-Series for Financial Technical Analysis

Kelvin J. L. Koa, Jan Chen, Yunshan Ma +2

While Large Language Models have been used to produce interpretable stock forecasts, they mainly focus on analyzing textual reports but not historical price data, also known as Tec…

cs.IR2025

SemCORE: A Semantic-Enhanced Generative Cross-Modal Retrieval Framework with MLLMs

Haoxuan Li, Yi Bin, Yunshan Ma +4

Cross-modal retrieval (CMR) is a fundamental task in multimedia research, focused on retrieving semantically relevant targets across different modalities. While traditional CMR met…

cs.IR2025

Distilling Transitional Pattern to Large Language Models for Multimodal Session-based Recommendation

Jiajie Su, Qiyong Zhong, Yunshan Ma +5

Session-based recommendation (SBR) predicts the next item based on anonymous sessions. Traditional SBR explores user intents based on ID collaborations or auxiliary content. To fur…

cs.IR2025

Large Language Model Empowered Recommendation Meets All-domain Continual Pre-Training

Haokai Ma, Yunshan Ma, Ruobing Xie +5

Recent research efforts have investigated how to integrate Large Language Models (LLMs) into recommendation, capitalizing on their semantic comprehension and open-world knowledge f…

cs.MM2025★ 1 cited

Extending Visual Dynamics for Video-to-Music Generation

Xiaohao Liu, Teng Tu, Yunshan Ma +1

Music profoundly enhances video production by improving quality, engagement, and emotional resonance, sparking growing interest in video-to-music generation. Despite recent advance…