5 citations · 24 across the 91 of their papers we have counts for
9 papers · 1 filter
Experimental Experience Modeling for Autonomous Research
Wenda Wei, Yingchen Zhang, Ruqing Zhang +3
Autonomous research agents can generate hypotheses and conduct experiments, but experimentation remains a major source of computational cost. A fundamental challenge is deciding wh…
Code-on-Graph: Iterative Programmatic Reasoning via Large Language Models on Knowledge Graphs
Weiwei Ding, Zixuan Li, Long Bai +7
Knowledge Graphs (KGs) are widely used to mitigate the limitations of Large Language Models (LLMs), such as outdated knowledge and hallucinations. Existing LLM-KG integration frame…
LatentRouter: Can We Choose the Right Multimodal Model Before Seeing Its Answer?
Xueqi Cheng, Yushun Dong
Multimodal large language models (MLLMs) have heterogeneous strengths across OCR, chart understanding, spatial reasoning, visual question answering, cost, and latency. Effective ML…
Beyond Dialogue Time: Temporal Semantic Memory for Personalized LLM Agents
Miao Su, Yucan Guo, Zhongni Hou +8
Memory enables Large Language Model (LLM) agents to perceive, store, and use information from past dialogues, which is essential for personalization. However, existing methods fail…
A Survey of Link Prediction in N-ary Knowledge Graphs
Jiyao Wei, Saiping Guan, Da Li +3
N-ary Knowledge Graphs (NKGs) are a specialized type of knowledge graph designed to efficiently represent complex real-world facts. Unlike traditional knowledge graphs, where a fac…
KnowCoder-V2: Deep Knowledge Analysis
Zixuan Li, Wenxuan Liu, Long Bai +13
Deep knowledge analysis tasks always involve the systematic extraction and association of knowledge from large volumes of data, followed by logical reasoning to discover insights.…
Mixture Policy based Multi-Hop Reasoning over N-tuple Temporal Knowledge Graphs
Zhongni Hou, Miao Su, Xiaolong Jin +4
Temporal Knowledge Graphs (TKGs), which utilize quadruples in the form of (subject, predicate, object, timestamp) to describe temporal facts, have attracted extensive attention. N-…
Retrieval-Augmented Code Generation for Universal Information Extraction
Yucan Guo, Zixuan Li, Xiaolong Jin +8
Information Extraction (IE) aims to extract structural knowledge (e.g., entities, relations, events) from natural language texts, which brings challenges to existing methods due to…
Few-shot Link Prediction on N-ary Facts
Jiyao Wei, Saiping Guan, Xiaolong Jin +2
Hyper-relational facts, which consist of a primary triple (head entity, relation, tail entity) and auxiliary attribute-value pairs, are widely present in real-world Knowledge Graph…