5 papers · 1 filter
RETuning: Upgrading Inference-Time Scaling for Stock Movement Prediction with Large Language Models
Xueyuan Lin, Cehao Yang, Ye Ma +7
Recently, large language models (LLMs) have demonstrated outstanding reasoning capabilities on mathematical and coding tasks. However, their application to financial tasks-especial…
CARFT: Boosting LLM Reasoning via Contrastive Learning with Annotated Chain-of-Thought-based Reinforced Fine-Tuning
Wenqiao Zhu, Ji Liu, Rongjuncheng Zhang +2
Reasoning capability plays a significantly critical role in the the broad applications of Large Language Models (LLMs). To enhance the reasoning performance of LLMs, diverse Reinfo…
PuzzleClone: A DSL-Powered Framework for Synthesizing Verifiable Data
Kai Xiong, Yanwei Huang, Rongjunchen Zhang +3
High-quality mathematical and logical datasets with verifiable answers are essential for strengthening the reasoning capabilities of large language models (LLMs). While recent data…
BizFinBench: A Business-Driven Real-World Financial Benchmark for Evaluating LLMs
Guilong Lu, Xuntao Guo, Rongjunchen Zhang +2
Large language models excel in general tasks, yet assessing their reliability in logic-heavy, precision-critical domains like finance, law, and healthcare remains challenging. To a…
Nexus: An Omni-Perceptive And -Interactive Model for Language, Audio, And Vision
Che Liu, Yingji Zhang, Dong Zhang +13
This work proposes an industry-level omni-modal large language model (LLM) pipeline that integrates auditory, visual, and linguistic modalities to overcome challenges such as limit…