8 papers
GorillaWatch: An Automated System for In-the-Wild Gorilla Re-Identification and Population Monitoring
Maximilian Schall, Felix Leonard Knöfel, Noah Elias König +11
Monitoring critically endangered western lowland gorillas is currently hampered by the immense manual effort required to re-identify individuals from vast archives of camera trap f…
On the Challenges and Opportunities in Generative AI
Laura Manduchi, Clara Meister, Kushagra Pandey +23
The field of deep generative modeling has grown rapidly in the last few years. With the availability of massive amounts of training data coupled with advances in scalable unsupervi…
Hierarchical Divide-and-Conquer for Fine-Grained Alignment in LLM-Based Medical Evaluation
Shunfan Zheng, Xiechi Zhang, Gerard de Melo +2
In the rapidly evolving landscape of large language models (LLMs) for medical applications, ensuring the reliability and accuracy of these models in clinical settings is paramount.…
NLSR: Neuron-Level Safety Realignment of Large Language Models Against Harmful Fine-Tuning
Xin Yi, Shunfan Zheng, Linlin Wang +3
The emergence of finetuning-as-a-service has revealed a new vulnerability in large language models (LLMs). A mere handful of malicious data uploaded by users can subtly manipulate…
ACE-: Automatic Capability Evaluator for Multimodal Medical Models
Xiechi Zhang, Shunfan Zheng, Linlin Wang +4
As multimodal large language models (MLLMs) gain prominence in the medical field, the need for precise evaluation methods to assess their effectiveness has become critical. While b…
I Don't Know: Explicit Modeling of Uncertainty with an [IDK] Token
Roi Cohen, Konstantin Dobler, Eden Biran +1
Large Language Models are known to capture real-world knowledge, allowing them to excel in many downstream tasks. Despite recent advances, these models are still prone to what are…