Beyond math and coding: New RL framework helps train LLM agents for complex, real-world tasks

The Agent-R1 framework provides a path to building more autonomous agents that can reason and use tools in unpredictable, real-world environments.
IGN

Inverse Functions

This mission walkthrough for Anthem's Inverse Functions is based on the version presented in the demo. Thanks to some improper usage of the Manifold -- you know, like slamming it on a hard surface -- ...

Nous Research just released Nomos 1, an open-source AI that ranks second on the notoriously brutal Putnam math exam

Nous Research's open-source Nomos 1 AI model scored 87/120 on the notoriously difficult Putnam math competition, ranking ...
IEEE

Automatic Loss Function Search for Adversarial Unsupervised Domain Adaptation

Abstract: Unsupervised domain adaption (UDA) aims to reduce the domain gap between labeled source and unlabeled target domains. Many prior works exploit adversarial learning that leverages ...
IEEE

Generalized Characteristic Function Loss for Crowd Analysis in the Frequency Domain

Abstract: Typical approaches that learn crowd density maps are limited to extracting the supervisory information from the loosely organized spatial information in the crowd dot/density maps. This ...
GitHub

Mutual Annotation-Based Prediction of Protein Domain Functions with Domain2GO

Identifying the functions of known proteins is an important task in understanding their critical roles in biological processes. Although high throughput sequencing tools seem to make this task easier, ...