10 papers
FINSKILLOPS: A Self-Evolving Multi-Agent System for SEC Filing QA
Yanzhang Ma, Zhenghan Tai, Hanwei Wu +25
Financial QA systems are typically improved before deployment through better retrieval, prompting, or agent coordination, leaving their reliability behavior fixed thereafter. In pr…
Patients-like-me: A Variational LM--GNN Framework for Explainable Clinical Prediction
Xinyu Wang, Yixuan Li, Hanwei Wu +4
Language models (LMs) offer strong textual representations for electronic health records (EHRs), but they encode patient sequences in isolation and provide limited explainability.…
FinSAgent: Corpus-Aligned Multi-Agent RAG Framework for Evidence-Grounded SEC Filing Question Answering
Jijun Chi, Zhenghan Tai, Hanwei Wu +21
Financial question answering over U.S. Securities and Exchange Commission (SEC) filings requires retrieving and synthesizing heterogeneous evidence dispersed across long, standardi…
SafeRx-Agent: A Knowledge-Grounded Multi-Agent Framework for Safe and Explainable Medication Recommendation
Xinyu Wang, Hanwei Wu, Zhenghan Tai +7
Medication recommendation predicts medications for patient visits, but existing methods still face two key challenges. At the model level, traditional drug recommendation methods o…
IFPV: An Integrated Multi-Agent Framework for Generative Operational Planning and High-Fidelity Plan Verification
Zhigao Huang, Zhengqing Hu, Dong Chen +5
Operational plan generation and verification are critical for modern complex and rapidly changing battlefield environments, yet traditional generation and verification methods stil…
From Table to Cell: Attention for Better Reasoning with TABALIGN
Tung Sum Thomas Kwok, Zeyong Zhang, Xinyu Wang +6
Multi-step LLM reasoning over structured tables fails because planning and execution share no explicit cell-grounding contract. Existing methods constrain the planner to a left-to-…
TABQAWORLD: Optimizing Multimodal Reasoning for Multi-Turn Table Question Answering
Tung Sum Thomas Kwok, Xinyu Wang, Xiaofeng Lin +7
Multimodal reasoning has emerged as a powerful framework for enhancing reasoning capabilities of reasoning models. While multi-turn table reasoning methods have improved reasoning…
Co-Evolution of Policy and Internal Reward for Language Agents
Xinyu Wang, Hanwei Wu, Jingwei Song +8
Large language model (LLM) agents learn by interacting with environments, but long-horizon training remains fundamentally bottlenecked by sparse and delayed rewards. Existing metho…
: A Route-to-Rerank Post-Training Framework for Multi-Domain Decoder-Only Rerankers
Xinyu Wang, Hanwei Wu, Qingchen Hu +13
Decoder-only rerankers are central to Retrieval-Augmented Generation (RAG). However, generalist models miss domain-specific nuances in high-stakes fields like finance and law, and…
VeritasFi: An Adaptable, Multi-tiered RAG Framework for Multi-modal Financial Question Answering
Zhenghan Tai, Hanwei Wu, Qingchen Hu +24
Retrieval-Augmented Generation (RAG) is becoming increasingly essential for Question Answering (QA) in the financial sector, where accurate and contextually grounded insights from…