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From the 2 of 8 linked papers with an AI index.

collaborators

8 papers

cs.CV2026

From Hindsight to Foresight: Self-Encouraged Hindsight Distillation for Knowledge-based Visual Question Answering

Yu Zhao, Ying Zhang, Xuhui Sui +4

The paper introduces a teacher‑student framework called Hindsight Distillation (HinD) that uses privileged answer information to generate reasoning trajectories for a multimodal LL…

cs.LG2026

Hyper-modal Imputation Diffusion Embedding with Dual-Distillation for Federated Multimodal Knowledge Graph Completion

Ying Zhang, Yu Zhao, Xuhui Sui +5

The paper introduces a federated learning framework for multimodal knowledge graph completion that recovers missing multimodal information with a hyper-modal imputation diffusion e…

cs.CV2026

Can Retrieval Heads See Images? Multimodal Retrieval Heads in Long-Context Vision-Language Models

Aaron Branson Cigres Li, Zhaowei Wang, Yu Zhao +9

Large vision-language models increasingly rely on long-context modeling to reason over documents, hour-level videos, and long-horizon agent trajectories, requiring them to locate r…

cs.CV2026

ClueAegis: Heuristic-to-Reasoning Cognitive-skill Learning for Unified Evidence-based Synthetic Image Detection

Huangsen Cao, Hongkang Chu, Yuxi Li +6

The rapid advancement of generative models has made synthetic images increasingly realistic, challenging reliable detection. Existing methods are often limited to end-to-end classi…

cs.MM2026

Hyperbolic Multimodal Generative Representation Learning for Generalized Zero-Shot Multimodal Information Extraction

Baohang Zhou, Kehui Song, Rize Jin +5

Multimodal information extraction (MIE) constitutes a set of essential tasks aimed at extracting structural information from Web texts with integrating images, to facilitate the st…

cs.CL2025

Plan of Knowledge: Retrieval-Augmented Large Language Models for Temporal Knowledge Graph Question Answering

Xinying Qian, Ying Zhang, Yu Zhao +3

Temporal Knowledge Graph Question Answering (TKGQA) aims to answer time-sensitive questions by leveraging factual information from Temporal Knowledge Graphs (TKGs). While previous…