14 papers
Continual Pretraining on Encrypted Synthetic Data for Privacy-Preserving LLMs
Honghao Liu, Xuhui Jiang, Chengjin Xu +4
Preserving privacy in sensitive data while pretraining large language models on small, domain-specific corpora presents a significant challenge. In this work, we take an explorator…
ChartPoint: Guiding MLLMs with Grounding Reflection for Chart Reasoning
Zhengzhuo Xu, SiNan Du, Yiyan Qi +4
Multimodal Large Language Models (MLLMs) have emerged as powerful tools for chart comprehension. However, they heavily rely on extracted content via OCR, which leads to numerical h…
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…
GraphSearch: An Agentic Deep Searching Workflow for Graph Retrieval-Augmented Generation
Cehao Yang, Xiaojun Wu, Xueyuan Lin +6
Graph Retrieval-Augmented Generation (GraphRAG) enhances factual reasoning in LLMs by structurally modeling knowledge through graph-based representations. However, existing GraphRA…
Think-on-Graph 3.0: Efficient and Adaptive LLM Reasoning on Heterogeneous Graphs via Multi-Agent Dual-Evolving Context Retrieval
Xiaojun Wu, Cehao Yang, Xueyuan Lin +6
Graph-based Retrieval-Augmented Generation (GraphRAG) has become the important paradigm for enhancing Large Language Models (LLMs) with external knowledge. However, existing approa…
JudgeAgent: Beyond Static Benchmarks for Knowledge-Driven and Dynamic LLM Evaluation
Zhichao Shi, Xuhui Jiang, Chengjin Xu +6
Current evaluation methods for large language models (LLMs) primarily rely on static benchmarks, presenting two major challenges: limited knowledge coverage and fixed difficulties…