5 citations · 5 across the 10 of their papers we have counts for
10 papers
HARP: Hierarchical Adaptive Ranking with Preference-Adaptive Fusion for Query-Based CVE Prioritization
Haochen Liu, Zhengzhang Chen, Haoyu Wang +3
Vulnerability prioritization is inherently preference dependent, since the same CVE can receive different remediation priority under different operational preference scenarios. Exi…
KAT-Coder-V2.5 Technical Report
Bo Huang, Fengxiang Li, Hao Xu +50
We present KAT-Coder-V2.5, a coding-focused agentic model trained to act autonomously inside real, executable repositories rather than as a single-turn code generator. Its capabili…
MINER: Mining Multimodal Internal Representation for Efficient Retrieval
Weien Li, Rui Song, Zeyu Li +8
Visual document retrieval has become essential for accessing information in visually rich documents. Existing approaches fall into two camps. Late-interaction retrievers achieve st…
LegalDrill: Diagnosis-Driven Synthesis for Legal Reasoning in Small Language Models
Tianchun Li, Haochen Liu, Vishwa Pardeshi +5
Small language models (SLMs) are promising for real-world deployment due to their efficiency and low operational cost. However, their limited capacity struggles with high-stakes le…
KAT-Coder-V2 Technical Report
Fengxiang Li, Han Zhang, Haoyang Huang +43
We present KAT-Coder-V2, an agentic coding model developed by the KwaiKAT team at Kuaishou. KAT-Coder-V2 adopts a "Specialize-then-Unify" paradigm that decomposes agentic coding in…
Question-Aware Knowledge Graph Prompting for Enhancing Large Language Models
Haochen Liu, Song Wang, Chen Chen +1
Large Language Models (LLMs) often struggle with tasks requiring external knowledge, such as knowledge-intensive Multiple Choice Question Answering (MCQA). Integrating Knowledge Gr…
KG-CF: Knowledge Graph Completion with Context Filtering under the Guidance of Large Language Models
Zaiyi Zheng, Yushun Dong, Song Wang +3
Large Language Models (LLMs) have shown impressive performance in various tasks, including knowledge graph completion (KGC). However, current studies mostly apply LLMs to classific…
Few-shot Knowledge Graph Relational Reasoning via Subgraph Adaptation
Haochen Liu, Song Wang, Chen Chen +1
Few-shot Knowledge Graph (KG) Relational Reasoning aims to predict unseen triplets (i.e., query triplets) for rare relations in KGs, given only several triplets of these relations…
Knowledge Graph-Enhanced Large Language Models via Path Selection
Haochen Liu, Song Wang, Yaochen Zhu +2
Large Language Models (LLMs) have shown unprecedented performance in various real-world applications. However, they are known to generate factually inaccurate outputs, a.k.a. the h…
Knowledge Editing for Large Language Models: A Survey
Song Wang, Yaochen Zhu, Haochen Liu +3
Large language models (LLMs) have recently transformed both the academic and industrial landscapes due to their remarkable capacity to understand, analyze, and generate texts based…