activity
20242026
most citedSNFinLLM: Systematic and Nuanced Financial Domain Adaptation of Chinese Large Language Models

1 citations · 2 across the 8 of their papers we have counts for

collaborators

8 papers

cs.AI2026

Internalizing the Future: A Unified Agentic Training Paradigm for World Model Planning

Xuan Zhang, Zhijian Zhou, Lingfeng Qiao +6

Large language model (LLM) agents have demonstrated strong capability in sequential decision-making, yet they remains fundamentally reactive in long-horizon tasks. Unlike humans wh…

cs.CL2026

Youtu-LLM: Unlocking the Native Agentic Potential for Lightweight Large Language Models

Junru Lu, Jiarui Qin, Lingfeng Qiao +35

We introduce Youtu-LLM, a lightweight yet powerful language model that harmonizes high computational efficiency with native agentic intelligence. Unlike typical small models that r…

cs.CL2025

InvestAlign: Overcoming Data Scarcity in Aligning Large Language Models with Investor Decision-Making Processes under Herd Behavior

Huisheng Wang, Zhuoshi Pan, Hangjing Zhang +3

Aligning Large Language Models (LLMs) with investor decision-making processes under herd behavior is a critical challenge in behavioral finance, which grapples with a fundamental l…

cs.CL2025

Towards Reliable Long-Context Reasoning: Detecting Unanswerable Questions via FactGuard

Qian-Wen Zhang, Biao Liu, Fang Li +5

Despite the success of Large Language Models (LLMs) in long-context tasks, their reliability in recognizing unanswerable questions remains a critical challenge. In information-seek…

cs.CL2025

Sequential-NIAH: A Needle-In-A-Haystack Benchmark for Extracting Sequential Needles from Long Contexts

Yifei Yu, Qian-Wen Zhang, Lingfeng Qiao +7

Evaluating the ability of large language models (LLMs) to process lengthy contexts is critical, especially for retrieving query-relevant information embedded within them. We introd…

cs.CL2024

Let's Be Self-generated via Step by Step: A Curriculum Learning Approach to Automated Reasoning with Large Language Models

Kangyang Luo, Zichen Ding, Zhenmin Weng +5

While Chain of Thought (CoT) prompting approaches have significantly consolidated the reasoning capabilities of large language models (LLMs), they still face limitations that requi…

cs.AI2024★ 1 cited

CJEval: A Benchmark for Assessing Large Language Models Using Chinese Junior High School Exam Data

Qian-Wen Zhang, Haochen Wang, Fang Li +5

Online education platforms have significantly transformed the dissemination of educational resources by providing a dynamic and digital infrastructure. With the further enhancement…

cs.CL2024★ 1 cited

SNFinLLM: Systematic and Nuanced Financial Domain Adaptation of Chinese Large Language Models

Shujuan Zhao, Lingfeng Qiao, Kangyang Luo +3

Large language models (LLMs) have become powerful tools for advancing natural language processing applications in the financial industry. However, existing financial LLMs often fac…