works on

From the 1 of 23 linked papers with an AI index.

activity
20242026
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23 papers

cs.CV2026

ObliCity: A Benchmark and Baseline for Roof-to-Ground Projection Displacement Correction

Kai Li, Yupeng Deng, Ligao Deng +6

The paper presents ObliCity, a large-scale benchmark for extracting roof-to-footprint offset vectors in oblique urban remote sensing images, and introduces DragRoof, an ODE-based m…

cs.LG2026

Latent Block-Diffusion Temporal Point Processes: A Semi-Autoregressive Framework for Asynchronous Event Sequence Generation

Shuai Zhang, Yancheng Chen, Chuan Zhou +5

Modeling and sampling from the underlying distribution of asynchronous event sequences are crucial in various real-world applications, including social networks, medical diagnosis,…

cs.CL2026

Logic Jailbreak: Efficiently Unlocking LLM Safety Restrictions Through Formal Logical Expression

Jingyu Peng, Maolin Wang, Nan Wang +7

Despite substantial advancements in aligning large language models (LLMs) with human values, current safety mechanisms remain susceptible to jailbreak attacks. We hypothesize that…

eess.AS2026

Discrete Token Modeling for Multi-Stem Music Source Separation with Language Models

Pengbo Lyu, Xiangyu Zhao, Chengwei Liu +4

We propose a generative framework for multi-track music source separation (MSS) that reformulates the task as conditional discrete token generation. Unlike conventional approaches…

cs.IR2026

Scalable Dynamic Embedding Size Search for Streaming Recommendation

Yunke Qu, Liang Qu, Tong Chen +3

Recommender systems typically represent users and items by learning their embeddings, which are usually set to uniform dimensions and dominate the model parameters. However, real-w…

cs.CL2026

Align-GRAG: Anchor and Rationale Guided Dual Alignment for Graph Retrieval-Augmented Generation

Derong Xu, Pengyue Jia, Xiaopeng Li +9

Despite the strong abilities, large language models (LLMs) still suffer from hallucinations and reliance on outdated knowledge, raising concerns in knowledge-intensive tasks. Graph…