1 citations · 3 across the 6 of their papers we have counts for
6 papers
CausalStock: Deep End-to-end Causal Discovery for News-driven Stock Movement Prediction
Shuqi Li, Yuebo Sun, Yuxin Lin +3
There are two issues in news-driven multi-stock movement prediction tasks that are not well solved in the existing works. On the one hand, "relation discovery" is a pivotal part wh…
MockLLM: A Multi-Agent Behavior Collaboration Framework for Online Job Seeking and Recruiting
Hongda Sun, Hongzhan Lin, Haiyu Yan +3
Online recruitment platforms have reshaped job-seeking and recruiting processes, driving increased demand for applications that enhance person-job matching. Traditional methods gen…
Selecting Query-bag as Pseudo Relevance Feedback for Information-seeking Conversations
Xiaoqing Zhang, Xiuying Chen, Shen Gao +4
Information-seeking dialogue systems are widely used in e-commerce systems, with answers that must be tailored to fit the specific settings of the online system. Given the user que…
Harnessing Multi-Role Capabilities of Large Language Models for Open-Domain Question Answering
Hongda Sun, Yuxuan Liu, Chengwei Wu +5
Open-domain question answering (ODQA) has emerged as a pivotal research spotlight in information systems. Existing methods follow two main paradigms to collect evidence: (1) The \t…
Masked Thought: Simply Masking Partial Reasoning Steps Can Improve Mathematical Reasoning Learning of Language Models
Changyu Chen, Xiting Wang, Ting-En Lin +6
In reasoning tasks, even a minor error can cascade into inaccurate results, leading to suboptimal performance of large language models in such domains. Earlier fine-tuning approach…
CharacterEval: A Chinese Benchmark for Role-Playing Conversational Agent Evaluation
Quan Tu, Shilong Fan, Zihang Tian +1
Recently, the advent of large language models (LLMs) has revolutionized generative agents. Among them, Role-Playing Conversational Agents (RPCAs) attract considerable attention due…