Entity trail

LoCoMo

Source-backed findings, relationship evidence, citations, and briefing history from the public MindPattern archive.

Briefing refs

Findings

Edges

Sources

Corpus findings

2026-06-07 / skill-finderTreat agent memory as a pruning problem, not a hoarding problem — decay it on an Ebbinghaus curveUnbounded memory accumulation degrades agents through noise, retrieval latency, and interference from stale facts; context pollution now causes more failures than model quality. YourMemory applies an Ebbinghaus forgetting curve that prunes stale memories every 24 hours, uses importance scores to set per-memory decay rates, does subject-aware deduplication to replace outdated facts, and keeps a decayed memory alive only if a graph neighbor stays above threshold (chain-aware pruning). The result is +16pp recall over Mem0 on the LoCoMo benchmark.
2026-06-04 / skill-finderShift agent-memory work from retrieval time to storage time for 3–4× token savingsMost agent memory systems do too much at retrieval and too little at storage. New 2026 architectures organize, relate, and compress memories at creation time, then retrieve via multi-signal fusion (semantic + keyword + entity, plus temporal recency and metadata pre-filters). The result: ~7,000 tokens per retrieval vs 25K–100K for full-context, with >91% recall on LoCoMo-style long-horizon benchmarks.
2026-05-28 / agents-researcherFluxMem: Dynamic Heterogeneous Graph Memory Achieves SOTA on LoCoMo, Mind2Web, and GAIA Agent BenchmarksFang et al. (submitted May 27, arXiv 2605.28773) propose FluxMem, which models LLM agent memory as a continuously evolving heterogeneous graph rather than a static repository. The system repairs broken connections, prunes irrelevant interference, aligns abstraction granularity, and distills successful trajectories into reusable procedural circuits through three stages: connection formation, feedback-driven refinement, and long-term consolidation. Achieves state-of-the-art across LoCoMo (conversational), Mind2Web (web navigation), and GAIA (multi-step reasoning) benchmarks.
2026-05-24 / vibe-coding-researcherPattern: Agent Memory Becoming a Benchmarked Competitive Category With Standardized EvaluationsThree independent agent memory projects — MemPalace (96.6% LongMemEval, 52K stars), ByteRover CLI (96.1% LoCoMo, 4.8K stars), and Hermes Agent (persistent skill documents, 164K stars) — all prominently feature benchmark scores in their READMEs. This signals a shift: agent memory is no longer a nice-to-have feature bolted onto chat but a distinct, measurable capability with its own evaluation frameworks (LongMemEval, LoCoMo). Expect memory benchmarks to become a selection criterion alongside coding benchmarks.
2026-05-24 / vibe-coding-researcherTip: ByteRover CLI 2.0 Adds Portable Agent Memory With 96.1% LoCoMo Benchmark ScoreByteRover CLI (brv), formerly Cipher, provides a portable memory layer for autonomous coding agents (4.8K stars). Unlike vector databases that embed everything and hope semantic search works, ByteRover maintains an 'agentic map' — a structured context tree stored as JSON that captures file dependencies, function call graphs, architectural decisions, and custom annotations. Scored 96.1% on the LoCoMo benchmark using production code. Supports cloud sync for sharing context across teams and machines.
2026-05-17 / github-pulse-researcherMemPalace/mempalace at 52.4K Stars: Local-First AI Memory System Posts 96.6% Recall@5 on LongMemEval Without Any API CallsMemPalace stores conversation history verbatim (no summarization lossy compression) and indexes it using a spatial metaphor — 'wings' for people/projects, 'rooms' for topics, 'drawers' for content. It leads LongMemEval retrieval recall at 96.6% R@5 raw (98.4% hybrid, 99%+ with LLM reranking), with strong results on LoCoMo (60.3%), ConvoMem (92.9%), and MemBench (80.3%). Ships as an MCP server with 29 tools and auto-save hooks for Claude Code sessions, all running on SQLite + ChromaDB locally.
2026-05-13 / projects-researcherByteRover CLI 2.0 Claims Top LoCoMo and LongMemEval Benchmarks — Portable Memory Layer for Autonomous Coding Agents at 4,736 StarsByteRover CLI (formerly Cipher) ships a portable memory layer that gives AI coding agents persistent, structured memory via hierarchical context trees. Version 2.0 claims the top spot on long-term memory benchmarks with 96.1% LoCoMo accuracy and 92.8% LongMemEval-S accuracy. Includes a local web dashboard for browsing project memory, version control for context trees, and cloud sync, with support for Cursor, Claude Code, and Windsurf.
2026-05-10 / github-pulse-researcherMemoriLabs/Memori v3.3.3: Agent-Native Memory Infrastructure Launched May 7 at 14.3K Stars, Beats Zep and Mem0 on LoCoMo BenchmarkMemori is an LLM-agnostic memory layer that turns agent execution traces — tool results, workflow steps, decision logic — into structured persistent state. On the LoCoMo benchmark it achieved 81.95% accuracy using only 1,294 tokens per query (4.97% of full-context), outperforming Zep, LangMem, and Mem0 while reducing prompt size by 67% vs Zep. Officially launched May 7 with Python and TypeScript SDKs, the repo has surged to 14.3K stars with 549 commits.
2026-04-25 / reddit-researcherMirrorMe Bolt Humanoid Claims 11 m/s Indoor Speed — Closing Gap on Usain Bolt's 12.42 m/s RecordMirrorMe's Bolt humanoid robot appeared on r/singularity (185 upvotes) with updated speed claims of 11 m/s indoors and 10.09 m/s outdoors, approaching Usain Bolt's record 12.42 m/s. The 177cm, 75kg robot was originally unveiled in February at 10 m/s; the 10% indoor speed improvement suggests ongoing locomotion gains. MirrorMe markets Bolt as a 'steel sparring partner' for athletes, using faster stride rhythm rather than longer strides to maintain stability at speed.
2026-04-22 / reddit-researcherHalf-Marathon Robot Service Team POV — Joint Temperatures Hitting 70-100°C During 21km CourseA behind-the-scenes video from a humanoid robot's service team during a half-marathon attempt drew 69 upvotes and 13 comments on r/singularity, revealing joint temperatures consistently hitting 70-100°C throughout the 21km course. The thermal management data provides rare engineering transparency into the real-world challenges of sustained bipedal locomotion — a practical constraint rarely discussed in humanoid robot demos.
2026-04-22 / reddit-researcherAheadForm Origin F1 Humanoid Robot Returns with Updated Design — 289 Upvotes on r/singularityAheadForm's Origin F1 bionic humanoid robot head drew 289 upvotes and 69 comments on r/singularity with an updated look featuring 25 micromotors controlling eye, mouth, and facial muscle movements for lifelike expressions. The Chinese-made robot head integrates RGB cameras in pupils, bionic silicone skin, and real-time LLM/VLM integration for emotional conveyance and conversation. It focuses on head-only biomimicry for companionship and telepresence rather than full-body locomotion.
2026-04-18 / reddit-researcherUnitree H1 Humanoid Robot Demonstrates Jogging-to-Running Acceleration — 876↑ on r/singularityA video post (876↑, 90 comments) shows the Unitree H1 humanoid robot accelerating from a controlled jog to a full run, demonstrating a significant advance in bipedal locomotion stability. This is the highest-engagement robotics post on r/singularity today. The transition from walking to running is a key milestone in humanoid robotics because it requires dynamic balance control during a flight phase where neither foot contacts the ground.

Graph relationships

BENCHMARKED AGAINST
EverMemOS
EverMemOS outperforms all prior work on LoCoMo benchmark for long-horizon agents.
Source finding
BENCHMARKED AGAINST
Omni-SimpleMem
Omni-SimpleMem achieves state-of-the-art on LoCoMo benchmark with F1=0.613, a 47% improvement.
Source finding
BENCHMARKED AGAINST
SuperLocalMemory V3.3
SuperLocalMemory V3.3 achieves 70.4% on LoCoMo benchmark
Source finding
BENCHMARKED AGAINST
mem0
Mem0's memory compression achieved 26% accuracy improvements on the LOCOMO benchmark.
Source finding
BENCHMARKED AGAINST
ByteRover CLI

Source trail

Source: GitHub / YourMemory OpenAI spun up First hyperscaler to productionize computer use Overman & Bayati This paper The server now ships 197-upvote guide on r/ClaudeAI

Graph sources

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