3 papers
cs.AI2026
DAEDALUS: Bootstrapping Agent Memory from Self-Generated Tasks
Antoine Edy, Max Conti, Victor Xing +3
LLM agents often lack the operational knowledge to act reliably in new environments, as they must discover specific tool behaviors or environment conventions on their own. Without…
cs.LG2026
Experiential Reflective Learning for Self-Improving LLM Agents
Marc-Antoine Allard, Arnaud Teinturier, Victor Xing +1
Recent advances in large language models (LLMs) have enabled the development of autonomous agents capable of complex reasoning and multi-step problem solving. However, these agents…
cs.AI2026
ViDoRe V3: A Comprehensive Evaluation of Retrieval Augmented Generation in Complex Real-World Scenarios
António Loison, Quentin Macé, Antoine Edy +7
Retrieval-Augmented Generation (RAG) pipelines must address challenges beyond simple single-document retrieval, such as interpreting visual elements (tables, charts, images), synth…