MemSyco-Bench is a benchmark covering five tasks to evaluate memory-induced sycophancy in LLM agents, testing rejection of invalid memory, scope respect, conflict resolution, update tracking, and valid personalization.
Evaluating long-horizon memory for multi-party collaborative dialogues, 2026
5 Pith papers cite this work. Polarity classification is still indexing.
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2026 5verdicts
UNVERDICTED 5representative citing papers
GateMem benchmark shows no existing memory method for LLM agents achieves strong utility, access control, and reliable forgetting simultaneously in multi-principal shared settings.
H2HMem is a multimodal memory benchmark evaluating LLM agents on recall, reasoning, and application in dyadic and multi-party human-human conversations with phenomena such as anaphora and deixis.
MemConflict provides a benchmark for testing LLM long-term memory systems under dynamic, static, and conditional conflicts involving temporal validity, factual correctness, and contextual applicability.
GroupMemBench is a new benchmark exposing that LLM agent memory systems fail on group conversation properties like speaker-grounded tracking and audience-adapted responses, with top systems at 46% accuracy.
citing papers explorer
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MemSyco-Bench: Benchmarking Sycophancy in Agent Memory
MemSyco-Bench is a benchmark covering five tasks to evaluate memory-induced sycophancy in LLM agents, testing rejection of invalid memory, scope respect, conflict resolution, update tracking, and valid personalization.
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GateMem: Benchmarking Memory Governance in Multi-Principal Shared-Memory Agents
GateMem benchmark shows no existing memory method for LLM agents achieves strong utility, access control, and reliable forgetting simultaneously in multi-principal shared settings.
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H2HMem: A Multimodal Memory Benchmark for Agents in Human-Human Interactions
H2HMem is a multimodal memory benchmark evaluating LLM agents on recall, reasoning, and application in dyadic and multi-party human-human conversations with phenomena such as anaphora and deixis.
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MemConflict: Evaluating Long-Term Memory Systems Under Memory Conflicts
MemConflict provides a benchmark for testing LLM long-term memory systems under dynamic, static, and conditional conflicts involving temporal validity, factual correctness, and contextual applicability.
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GroupMemBench: Benchmarking LLM Agent Memory in Multi-Party Conversations
GroupMemBench is a new benchmark exposing that LLM agent memory systems fail on group conversation properties like speaker-grounded tracking and audience-adapted responses, with top systems at 46% accuracy.