5 papers
S2Aligner: Pair-Efficient and Transferable Pre-Training for Sparse Text-Attributed Graphs
Yuhan Wang, Haopeng Zhang, Yibo Ding +6
Pre-training on text-attributed graphs (TAGs) is central to building transferable graph foundation models, where LLM-as-Aligner methods align graph and text representations through…
ClinSeekAgent: Automating Multimodal Evidence Seeking for Agentic Clinical Reasoning
Juncheng Wu, Letian Zhang, Yuhan Wang +5
Large language models (LLMs) and agentic systems have shown promise for clinical decision support, but existing works largely assume that evidence has already been curated and hand…
Divergence Meets Consensus: A Multi-Source Negative Sampling Framework for Sequential Recommendation
Yuanzi Li, Lingjie Wang, Jingyu Zhao +4
Negative sampling is significant for training sequential recommendation models under implicit feedback. The predominant strategy, self-guided hard negative sampling, selects negati…
Don't Settle Too Early: Self-Reflective Remasking for Diffusion Language Models
Zemin Huang, Yuhang Wang, Zhiyang Chen +1
Mask-based Diffusion Language Models (DLMs) struggle to revise incorrect tokens: once a token is generated, it typically remains fixed. The key challenge is to identify potential e…
C-Evolve: Consensus-based Evolution for Prompt Groups
Tiancheng Li, Yuhang Wang, Zhiyang Chen +3
Prompt evolution algorithms offer a powerful paradigm for enhancing AI systems based on closed-source models, while few work explores whether aggregating results from multiple prom…