7 papers
When Cognitive Graphs Meet LLMs: BDEI Cognitive Pathways for Panic Emotional Arousal Prediction
Mengzhu Liu, Long Qin, Chuan Ai +6
Predicting individual panic emotional arousal timing before manifestation is essential for proactive emergency intervention. Existing methods incorporate cognitive elements but non…
Advancing Edge Classification through High-Dimensional Causal Modeling of Node-Edge Interplay
Duanyu Feng, Li Ding, Hongru Liang +1
Edge classification, a crucial task for graph applications, remains relatively under-explored compared to link prediction. Current methods often overlook the potential causal influ…
BAR: A Backward Reasoning based Agent for Complex Minecraft Tasks
Weihong Du, Wenrui Liao, Binyu Yan +3
Large language model (LLM) based agents have shown great potential in following human instructions and automatically completing various tasks. To complete a task, the agent needs t…
Strength Lies in Differences! Improving Strategy Planning for Non-collaborative Dialogues via Diversified User Simulation
Tong Zhang, Chen Huang, Yang Deng +5
We investigate non-collaborative dialogue agents, which are expected to engage in strategic conversations with diverse users, for securing a mutual agreement that leans favorably t…
CARE: A Clue-guided Assistant for CSRs to Read User Manuals
Weihong Du, Jia Liu, Zujie Wen +3
It is time-saving to build a reading assistant for customer service representations (CSRs) when reading user manuals, especially information-rich ones. Current solutions don't fit…
PAGED: A Benchmark for Procedural Graphs Extraction from Documents
Weihong Du, Wenrui Liao, Hongru Liang +1
Automatic extraction of procedural graphs from documents creates a low-cost way for users to easily understand a complex procedure by skimming visual graphs. Despite the progress i…