arXiv Machine Learning
Memento No More: Coaching AI Agents to Master Multiple Tasks via Hints Internalization
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AdMem: Advanced Memory for Task-solving Agents
arXiv:2606. 06787v1 Announce Type: new Abstract: Large Language Models (LLMs) show promise as tool-using agents but remain limited in long-horizon tasks that require remembering, organizing, and reusing knowledge.
arXiv AI
Jun 30
Evaluating Memory in LLM Agents via Incremental Multi-Turn Interactions
arXiv:2507. 05257v4 Announce Type: replace-cross Abstract: Recent benchmarks for Large Language Model (LLM) agents primarily focus on evaluating reasoning, planning, and execution capabilities, while another critical component-memory, encompassing how agents memorize, update, and retrieve long-term information-is under-evaluated due to the lack of benchmarks.
arXiv AI
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APEx: Distillation of Agent Procedural Experience for Adaptive Deep Research Question Answering
APEx is a hierarchical framework that organizes a deep research agent’s interaction history into instance-level trajectory memories and category-level procedural skills. It couples these through an Executor, Distiller, and Planner, trained with a three-stage alternating GRPO paradigm to enable reward-guided skill distillation. At test time, distilled skills act as procedural priors for online Planner adaptation via skill-guided reinforcement learning, achieving state‑of‑the‑art results on seven benchmarks, outperforming GPT‑5.4 by 14.7 points and the best memory‑augmented baseline by 3.0 points.
arXiv AI
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Bidirectional Context Self-Distillation for Reinforcement Learning of Skill-Based LLM Agents
arXiv:2608. 09555v1 Announce Type: new Abstract: External natural-language skills provide large language model (LLM) agents with reusable and editable guidance for solving complex tasks.
arXiv AI
Jun 3
MemVerse: Multimodal Memory for Lifelong Learning Agents
arXiv:2512. 03627v2 Announce Type: replace Abstract: Despite rapid progress in large-scale language and vision models, AI agents still suffer from a fundamental limitation: they cannot remember.
Hugging Face Trending Papers
Jul 15
Memory as a Controlled Process: Learned Adaptive Memory Management for LLM Agents
Large Language Model (LLM) agents increasingly rely on external memory systems to accumulate experience across tasks. Yet nearly all existing approaches, from graph-structured memories to reflective insight stores, access memory through fixed, hand-designed heuristics.