Hugging Face Trending Papers
DolphinBench: Mapping the Pareto Frontier of Agent Memory
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arXiv Computation and Language
Sep 22
DolphinBench: Mapping the Pareto Frontier of Agent Memory
arXiv:2609.24971v1 Announce Type: new Abstract: Agents today often take real-world actions that depend on long-term memory and context recall over time. However, most current memory benchmarks are bu...
arXiv Computation and Language
Sep 21
MemoryArena: Benchmarking Agent Memory in Interdependent Multi-Session Agentic Tasks
MemoryArena is a new evaluation gym that benchmarks agent memory in interdependent multi‑session tasks. Unlike prior benchmarks that test memorization or single‑session action in isolation, MemoryArena requires agents to acquire memory while interacting with the environment and then use that memory to guide future decisions across a range of tasks such as web navigation, planning, information search, and formal reasoning. The benchmark reveals that agents excelling on existing long‑context memory tests perform poorly here, highlighting a gap in current memory evaluation methods.
arXiv AI
Jun 11
MemToolAgent: Leveraging Memory for Tool Using Agents Based on Environment and User Feedback
arXiv:2606. 07909v2 Announce Type: replace Abstract: Modern large language model (LLM) agents can use external tools to help users solve complex tasks.
arXiv AI
Jun 9
MemToolAgent overview with a simple restaurant booking scenario where the agent retrieves similar memories, receives feedback on an invalid time format, and generates a reflection to update its memory
arXiv:2606. 07909v1 Announce Type: new Abstract: Modern large language model (LLM) agents can use external tools to help users solve complex tasks.
arXiv AI
Jun 16
EvoMemBench: Benchmarking Agent Memory from a Self-Evolving Perspective
arXiv:2605. 18421v2 Announce Type: replace-cross Abstract: Recent benchmarks for Large Language Model (LLM) agents mainly evaluate reasoning, planning, and execution.
arXiv AI
Aug 7
Benchmarking the Benchmarks: Evaluating Benchmarks for Conversational Agents
arXiv:2608. 06329v1 Announce Type: cross Abstract: Task-oriented conversational agents are evaluated using curated or automatically generated benchmarks, yet benchmark quality is rarely assessed.