1 citations · 1 across the 8 of their papers we have counts for
8 papers
ASARL: Autonomous Social-Aware Relevance Learning for QQ Search
Tao Su, Jinjing Hu, Xiao Wang +2
The rapid growth of online social platforms has transformed communication and information retrieval, giving rise to social search, where queries-titles are typically expressed in i…
MolSafeEval: A Benchmark for Uncovering Safety Risks in AI-Generated Molecules
Tong Xu, Xinzhe Cao, Zhihui Zhu +2
Current molecular generation benchmarks emphasize task complexity, molecule novelty, and property alignment; they largely overlook a critical concern: the potential safety risks of…
TRACE: Tourism Recommendation with Accountable Citation Evidence
Zixu Zhao, Sijin Wang, Yu Hou +6
Tourism is a high-stakes setting for conversational recommender systems (CRS): a plausible-sounding suggestion can waste real money and trip time once a traveler acts on it. Existi…
RLMiner: Finding the Most Frequent k-sized Subgraph via Reinforcement Learning
Wei Huang, Hanchen Wang, Dong Wen +4
Identifying the most frequent induced subgraph of size in a target graph is a fundamental graph mining problem with direct implications for Web-related data mining and social n…
A2RAG: Adaptive Agentic Graph Retrieval for Cost-Aware and Reliable Reasoning
Jiate Liu, Zebin Chen, Shaobo Qiao +10
Graph Retrieval-Augmented Generation (Graph-RAG) enhances multihop question answering by organizing corpora into knowledge graphs and routing evidence through relational structure.…
Knowledge-Augmented Long-CoT Generation for Complex Biomolecular Reasoning
Tianwen Lyu, Xiang Zhuang, Keyan Ding +5
Understanding complex biomolecular mechanisms requires multi-step reasoning across molecular interactions, signaling cascades, and metabolic pathways. While large language models(L…
SIADAFIX: issue description response for adaptive program repair
Xin Cao, Nan Yu
We propose utilizing fast and slow thinking to enhance the capabilities of large language model-based agents on complex tasks such as program repair. In particular, we design an ad…
Do They Understand Them? An Updated Evaluation on Nonbinary Pronoun Handling in Large Language Models
Xushuo Tang, Yi Ding, Zhengyi Yang +7
Large language models (LLMs) are increasingly deployed in sensitive contexts where fairness and inclusivity are critical. Pronoun usage, especially concerning gender-neutral and ne…