Reactive Machines

Recommender systems in multi-stakeholder environments often need to optimize multiple objectives at the same time to meet the needs of…

Apple brings new work in powerful ways to the annual natural language conference (EMNLP), which takes place in person from…

Deliberation has become the central paradigm of large-scale linguistic models (LLMS), increasing the accuracy of progress across various benchmarks. However,…

We suggest that reinforcement learning (RL) from partial expert representation is not only a training material, but a promising framework…

This post was written with NVIDIA and the authors would like to thank Adi Margolin, Eliuth Triana, and Maryam Motamedi…

Linguistic models are developed with the user's description or are used to predict the user's preferences and opinions. However, the…

Knowledge graphs (KGS) are the basis for many AI applications, but maintaining their freshness and completeness is always expensive. Introducing…

(el) business has traditionally relied on large descriptive datasets and good comprehensive modeling. While several shooting methods prevent large-scale linguistic…

As the adoption of language models improves, so does the need to better represent specific users in the model. Are…

Recent advances in multimodal models have demonstrated text-based image editing capabilities, with programs such as GPT-4O and Nano-Banana setting new…