Tootfinder

Human-Annotated NER Dataset for the Kyrgyz Language
Timur Turatali, Anton Alekseev, Gulira Jumalieva, Gulnara Kabaeva, Sergey Nikolenko
https://arxiv.org/abs/2509.19109 https://…

HyCoVAD: A Hybrid SSL-LLM Model for Complex Video Anomaly Detection
Mohammad Mahdi Hemmatyar, Mahdi Jafari, Mohammad Amin Yousefi, Mohammad Reza Nemati, Mobin Azadani, Hamid Reza Rastad, Amirmohammad Akbari
https://arxiv.org/abs/2509.22544

HyCoVAD: A Hybrid SSL-LLM Model for Complex Video Anomaly Detection
Video anomaly detection (VAD) is crucial for intelligent surveillance, but a significant challenge lies in identifying complex anomalies, which are events defined by intricate relationships and temporal dependencies among multiple entities rather than by isolated actions. While self-supervised learning (SSL) methods effectively model low-level spatiotemporal patterns, they often struggle to grasp the semantic meaning of these interactions. Conversely, large language models (LLMs) offer powerful…

Mah\={a}n\={a}ma: A Unique Testbed for Literary Entity Discovery and Linking
Sujoy Sarkar, Gourav Sarkar, Manoj Balaji Jagadeeshan, Jivnesh Sandhan, Amrith Krishna, Pawan Goyal
https://arxiv.org/abs/2509.19844

Mahānāma: A Unique Testbed for Literary Entity Discovery and Linking
High lexical variation, ambiguous references, and long-range dependencies make entity resolution in literary texts particularly challenging. We present Mahānāma, the first large-scale dataset for end-to-end Entity Discovery and Linking (EDL) in Sanskrit, a morphologically rich and under-resourced language. Derived from the Mahābhārata, the world's longest epic, the dataset comprises over 109K named entity mentions mapped to 5.5K unique entities, and is aligned with an English knowledge base…