arXiv:2607. 20498v1 Announce Type: new Abstract: Large language models (LLMs) augmented with tools are emerging as autonomous agents capable of using Web engine, APIs, and code to solve complex, long-horizon tasks.
By Fanjin Zhang, Zhengyang Wang, Ruixuan Huang, Kefan Zhang, Amy Xin, Yuanchun Wang, Shu Zhao, Evgeny Kharlamov, Jie Tang, Juanzi Li
The paper introduces proFILL, a method that transforms the existing rule-based advising chatbot hoBIT into a profile-aware retrieval-augmented generation system. Instead of needing a full student profile at the start, proFILL incrementally gathers only the attributes required for each query, using both the query intent and initially retrieved evidence to guide retrieval from a profile-aware index. Experiments and a human preference study demonstrate that proFILL outperforms various RAG baselines, is favored by users, and remains effective when deployed with open-weight models for cost-efficient on‑premise use.
By Yoonseo Kim, Seongmin Lee, Joongheon Kim, SeongKu Kang
arXiv:2607. 22713v1 Announce Type: new Abstract: Enterprise IT support knowledge graphs capture rich relationships among cases, users, devices, symptoms, taxonomic categories, root causes, and historical resolutions.
By Saiyue Lyu, Mariam Dundua, Vishaal Kapoor, Sarthak Ahuja, Neda Kordjazi, Evren Yortucboylu, Harsh Amin, Rebecca Steinert
arXiv:2607. 22598v1 Announce Type: cross Abstract: Educational chatbots powered by large language models (LLMs) show promising effects on learning outcomes, yet most systems delegate pedagogical decisions such as content selection and didactic structuring implicitly to the LLM, making tutoring strategies difficult to trace, evaluate, and reproduce.
By Laurent Brisson (IMT Atlantique - DSD), Maria Segarra (IMT Atlantique - INFO, Lab-STICC\_MOTEL), Gr\'egory Smits (IMT Atlantique - INFO, Lab-STICC\_MOTEL)
arXiv:2606. 28360v1 Announce Type: cross Abstract: University students often struggle to navigate complex academic policies, leading to advising bottlenecks and delayed access to critical information.
By Ben Torsion, Jun Zhou
arXiv:2606. 05901v1 Announce Type: cross Abstract: Large language models (LLMs) have fundamentally transformed the landscape of Natural Language Processing.
By Christopher J. Wedge, Joshua Stutter, Danny Dixon, Jacek Ca{\l}a