4 accepted papers
The pursuit of general-purpose embodied agents is currently hindered by fragmented evaluation protocols that isolate navigation skills and fixate on specific robot morphologies. This disconnect fails to reflect real-world scenarios where agents must orchestrate diverse behaviors across varying physi…
We propose a novel approach to improve multi-objective evolutionary algorithms by modifying crossover operations. Our approach uses a modifiable cross distribution and virtual point to rebalance the probability distribution of all crossover options. This design reduces runtime for typical pseudo-Boo…
With the proliferation of LLM-integrated applications such as GPT-s, millions are deployed, offering valuable services through proprietary instruction prompts. These systems, however, are prone to prompt extraction attacks through meticulously designed queries. To help mitigate this problem, we intr…
To understand a story with multiple events, it is important to capture the proper relations across these events. However, existing event relation extraction (ERE) framework regards it as a multi-class classification task and do not guarantee any coherence between different relation types, such as an…