Navigating the Digital World as Humans Do: Universal Visual Grounding for GUI Agents Gou et al.: https://
arxiv.org/abs/2410.05243 #ArtificialIntelligence #DeepLearning #MachineLearning
@montreal_ai
-
Universal Visual Grounding for GUI Agents Navigation
By
–
-
Leanabell-Prover: Posttraining Scaling in Formal Reasoning
By
–
Leanabell-Prover: Posttraining Scaling in Formal Reasoning Zhang et al.: https://
arxiv.org/abs/2504.06122 #ArtificialIntelligence #DeepLearning #MachineLearning -
Learning Reasoning for Long-Form Story Generation
By
–
Learning to Reason for Long-Form Story Generation Alexander Gurung, Mirella Lapata: https://
arxiv.org/abs/2503.22828 #ArtificialIntelligence #DeepLearning #MachineLearning -
Transformers Learn Positional Information Without Explicit Encodings
By
–
Transformer Language Models without Positional Encodings Still Learn Positional Information Haviv et al.: https://
arxiv.org/abs/2203.16634 #ArtificialIntelligence #DeepLearning #MachineLearning -
Scaling Laws of Synthetic Data for Language Models
By
–
Scaling Laws of Synthetic Data for Language Models Qin et al.: https://
arxiv.org/abs/2503.19551
v2
… #ArtificialIntelligence #DeepLearning #MachineLearning -
APIGen-MT: Agentic Pipeline for Multi-Turn Data Generation
By
–
APIGen-MT: Agentic Pipeline for Multi-Turn Data Generation via Simulated Agent-Human Interplay Prabhakar et al.: https://
arxiv.org/abs/2504.03601 #ArtificialIntelligence #DeepLearning #MachineLearning -
Decentralized Collective World Model for Emergent Agent Communication
By
–
Decentralized Collective World Model for Emergent Communication and Coordination Nomura et al.: https://
arxiv.org/abs/2504.03353 #ArtificialIntelligence #DeepLearning #MachineLearning -
Open-Reasoner-Zero: Scaling Reinforcement Learning on Base Models
By
–
Open-Reasoner-Zero: An Open Source Approach to Scaling Up Reinforcement Learning on the Base Model Hu et al.: https://
arxiv.org/abs/2503.24290 #ArtificialIntelligence #DeepLearning #MachineLearning -
NoProp: Training Neural Networks Without Back-propagation
By
–
NoProp: Training Neural Networks without Back-propagation or Forward-propagation Qinyu Li, Yee Whye Teh, Razvan Pascanu: https://
arxiv.org/abs/2503.24322 #ArtificialIntelligence #DeepLearning #MachineLearning -
Foundation Agents: Brain-Inspired, Collaborative, Safe Systems
By
–
Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems Liu et al.: https://
arxiv.org/abs/2504.01990
v1
… #ArtificialIntelligence #DeepLearning #MachineLearning