9 citations · 23 across the 21 of their papers we have counts for
9 papers · 1 filter
Scenes as an Attack Surface: Uncovering Scene-Grounded Safety Failures in MLLMs
Tongxi Wu, Yuyang Cheng, Jiacheng Xian +5
Existing jailbreak attacks have exposed serious safety weaknesses in multimodal large language models (MLLMs). Most prior attacks rely on specially constructed visual inputs to car…
Think Wider: Mitigating Latent Rank Collapse in Implicit Chain-of-Thought Reasoning
Yuwen Hao, Menglin Yang
Chain-of-thought (CoT) reasoning improves the reasoning ability of large language models by introducing intermediate computation, but explicit rationales increase decoding length,…
FlatLand: Personalized Graph Federated Learning via Tailored Lorentz Space
Jiahong Liu, Ram Samarth B B, Xinyu Fu +4
Federated learning enables privacy-preserving collaborative training, but highly heterogeneous client data remain challenging, especially in graph federated learning where clients…
MGAL: A Multilingual Granularity-Aware Long-Context Benchmark
Chunhan Li, Chenglin Xu, Zongyang Zhang +8
Evaluation of long-context Large Language Models (LLMs) has advanced rapidly. However, most existing benchmarks are limited to the document level and focus mainly on high-resource…
Hyperbolic Multimodal Continual Learning
Jiahong Liu, Ming Shen, Xiaohao Liu +4
Hyperbolic geometry has recently emerged as a powerful representation space for multimodal learning, as it naturally captures hierarchical semantic structure across modalities. Des…
ProWorld: Progress-Aware Hyperbolic World Models for Long-Horizon Visual Goal Reaching
Zihan Liu, Yuzhe Zhuang, Yuanzu Li +4
JEPA-style visual world models offer an effective paradigm for visual goal planning by predicting future latent representations. Existing methods typically learn local transition c…
Hierarchical Abstract Tree for Cross-Document Retrieval-Augmented Generation
Ziwen Zhao, Menglin Yang
Retrieval-augmented generation (RAG) enhances large language models with external knowledge, and tree-based RAG organizes documents into hierarchical indexes to support queries at…
Parameter-Efficient Fine-Tuning of LLMs with Mixture of Space Experts
Buze Zhang, Jinkai Tao, Zilang Zeng +4
Large Language Models (LLMs) have achieved remarkable progress, with Parameter-Efficient Fine-Tuning (PEFT) emerging as a key technique for downstream task adaptation. However, exi…
HypRAG: Hyperbolic Dense Retrieval for Retrieval Augmented Generation
Hiren Madhu, Ngoc Bui, Ali Maatouk +6
Embedding geometry plays a fundamental role in retrieval quality, yet dense retrievers for retrieval-augmented generation (RAG) remain largely confined to Euclidean space. However,…