6 papers
LEDGERMIND: Provenance-Constrained Multimodal Agentic Reasoning with a Structured Evidence Ledger
Enjun Du, Hange Zhou, Chenxu Du +4
The paper introduces LedgerMind, a framework that records and constrains the evidence used by multimodal agents during visual question answering, ensuring that each reasoning step…
CARA: Concept-Aware Risk Attention for Interpretable Collision Anticipation
Zhishan Tao, Ruoyu Wang, Yucheng Wu +6
Collision anticipation in autonomous driving requires not only accurate early warnings but also interpretable reasoning about what risk factors are being tracked and how risk evolv…
GraphOracle: Efficient Fully-Inductive Knowledge Graph Reasoning via Relation-Dependency Graphs
Enjun Du, Siyi Liu, Yongqi Zhang
Knowledge graph reasoning in the fully-inductive setting, where both entities and relations at test time are unseen during training, remains an open challenge. In this work, we int…
Mixture of Length and Pruning Experts for Knowledge Graphs Reasoning
Enjun Du, Siyi Liu, Yongqi Zhang
Knowledge Graph (KG) reasoning, which aims to infer new facts from structured knowledge repositories, plays a vital role in Natural Language Processing (NLP) systems. Its effective…
S2A: A Unified Framework for Parameter and Memory Efficient Transfer Learning
Tian Jin, Enjun Du, Changwei Wang +2
Parameter-efficient transfer learning (PETL) aims to reduce the scales of pretrained models for multiple downstream tasks. However, as the models keep scaling up, the memory footpr…
GraphMaster: Automated Graph Synthesis via LLM Agents in Data-Limited Environments
Enjun Du, Xunkai Li, Tian Jin +3
The era of foundation models has revolutionized AI research, yet Graph Foundation Models (GFMs) remain constrained by the scarcity of large-scale graph corpora. Traditional graph d…