6 papers
SKIP: a Self-knowledge-guided Step-wise Preference Learning Framework for Concise Reasoning
Qinhong Lin, Yuhao Zhang, Yinglun Feng +2
While Chain-of-Thought (CoT) reasoning has been proven to be effective, it often leads to overthinking, resulting in computational overhead, inference latency, and even degraded pe…
FactorEngine: A Program-level Knowledge-Infused Factor Mining Framework for Quantitative Investment
Qinhong Lin, Ruitao Feng, Yinglun Feng +7
We study alpha factor mining, the automated discovery of predictive signals from noisy, non-stationary market data-under a practical requirement that mined factors be directly exec…
FinCPRG: A Bidirectional Generation Pipeline for Hierarchical Queries and Rich Relevance in Financial Chinese Passage Retrieval
Xuan Xu, Beilin Chu, Qinhong Lin +7
In recent years, large language models (LLMs) have demonstrated significant potential in constructing passage retrieval datasets. However, existing methods still face limitations i…
FinBERT2: A Specialized Bidirectional Encoder for Bridging the Gap in Finance-Specific Deployment of Large Language Models
Xuan Xu, Fufang Wen, Beilin Chu +7
In natural language processing (NLP), the focus has shifted from encoder-only tiny language models like BERT to decoder-only large language models(LLMs) such as GPT-3. However, LLM…
Label-Confidence-Aware Uncertainty Estimation in Natural Language Generation
Qinhong Lin, Linna Zhou, Yinglun Feng +3
Large Language Models (LLMs) demonstrate remarkable capabilities in generative tasks but pose potential risks due to their tendency to generate hallucinatory responses. Therefore,…
Approximated Variational Bayesian Inverse Reinforcement Learning for Large Language Model Alignment
Yuang Cai, Yuyu Yuan, Jinsheng Shi +1
The alignment of large language models (LLMs) is crucial for generating helpful and harmless content. Existing approaches leverage preference-based human feedback data to learn the…