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Top signals · Oct 27–28, 2026 · Updated Oct 28, 10:05 UTC
Moonfold: Coding tasks that survive agent usage limits
GEPA-Curator: Curated Learning for Self Improving Agents
Large Language Models (LLMs) are increasingly used in multi-turn agentic workloads that require sustained interaction with complex environments. Existing reflective prompt optimizers such as GEPA learn from failed rol... Context & related coverage →
ETAMem: Decoupling and Aligning Heterogeneous Memory for Long-Term Conversational Agents
Long-term memory enables Large Language Models (LLMs) to maintain coherent and personalized interactions across extended conversations. However, existing memory systems face two key challenges: (1) Information Entangl... Context & related coverage →
EnvSched: Environment-Aware Scheduling for Rollout-Efficient Agent Reinforcement Learning
As executable environments for language agents scale, generating and verifying their rollouts becomes increasingly expensive. Under finite rollout budgets, this raises an important question: can data management at the... Context & related coverage →
From Interaction to Capability: Task Advancement as State and Supervision for GUI Agents
GUI memory should preserve the results of past actions and learn reusable operations. This is difficult in long-horizon workflows, where agents must use information across applications and useful operations are interl... Context & related coverage →
Gym-Anything-RT: Scaling Real-Time Environments for Vision-Language Agents
AI agents have made substantial progress in domains where they have a non-trivial amount of time to deliberate between actions, such as mathematics, software engineering, and performing tasks on desktop applications.... Context & related coverage →
Requesty: AI Gateway and LLM Router for 600 Models in EU Datacenters
Legora is building the agentic operating system for legal work
See how Legora uses OpenAI models, ChatGPT, and Codex to accelerate legal workflows, expand contract analysis, and free lawyers to focus on higher-value work. Context & related coverage →