External Papers &Reproductions

Tracking, reviewing, and reproducing important research papers from the broader scientific community. Our commitment to validating and building upon existing research.

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2026
Reproduction: TriagedP0Harness EngineeringAgent Evaluation

Harness-Bench: Measuring Harness Effects across Models in Realistic Agent Workflows

By Yilun Yao, Xinyu Tan, Chao-Hsuan Liu, Yaoming Li, Zhengyang Wang, Wenhan Yu, Zhewen Tan, Yuxuan Tian, Guangxiang Zhao, Lin Sun, Xiangzheng Zhang, Tong Yang

Published in: arXiv preprint (2026)

Citation: Yao et al., 2026

Notes: Operationalizes 'Agent = Model + Harness' by evaluating 6 harnesses x 8 models on 106 tasks. Directly encodes AJL's core thesis; recommends reporting model-harness pairs.

2026
Reproduction: TriagedP0Harness Engineering

Agentic Harness Engineering: Observability-Driven Automatic Evolution of Coding-Agent Harnesses

By Jiahang Lin, Shichun Liu, Chengjun Pan, Lizhi Lin, Shihan Dou, Xuanjing Huang, Hang Yan, Zhenhua Han, Tao Gui

Published in: arXiv preprint (2026)

Citation: Lin et al., 2026

Notes: Self-evolving harness (tools/middleware/memory/prompts) via observability; lifts Terminal-Bench 2 69.7 -> 77.0% with cross-model transfer. Open code; directly reproducible on the building-agents stack.

2025
Reproduction: TriagedP0Agent EvaluationHarness Engineering

Holistic Agent Leaderboard: The Missing Infrastructure for AI Agent Evaluation

By Sayash Kapoor, Benedikt Stroebl, Peter Kirgis, et al.

Published in: arXiv preprint (2025)

Citation: Kapoor, Stroebl, Kirgis et al., 2025

Notes: Standardized eval harness across models x scaffolds x benchmarks; 21,730 rollouts and 2.5B tokens of released logs. Most reproducible target (open harness + logs).

2025
Reproduction: TriagedP2Interpretability & Safety

On the Biology of a Large Language Model

By Lindsey J et al

Published in: Transformer Circuits

Citation: Lindsey J et al. (2025). On the Biology of a Large Language Model. Transformer Circuits

Notes: Mechanistic interpretability research

2025
Reproduction: TriagedP2Interpretability & Safety

Tracing the thoughts of a large language model

By Anthropic Team

Published in: Anthropic

Citation: Anthropic Team. (2025). Tracing the thoughts of a large language model. Anthropic Research

Notes: Monitor for opportunities

2025
Reproduction: TriagedP0Model Efficiency

XAttention: Block Sparse Attention with Antidiagonal Scoring

By Xu R, Xiao G, Huang H, Guo J, Han S

Published in: arXiv

Citation: Xu R et al. (2025). XAttention: Block Sparse Attention with Antidiagonal Scoring. arXiv:2503.16428

Notes: High priority reproduction target

2024
Reproduction: TriagedP0Agent Architectures

EM-LLM: Human-inspired Episodic Memory for Infinite Context LLMs

By Zafeirios Fountas, Martin A Benfeghoul, Adnan Oomerjee, Fenia Christopoulou, Gerasimos Lampouras, Haitham Bou-Ammar, Jun Wang

Published in: ICLR 2025

Citation: Fountas et al., ICLR 2025

Notes: Human-inspired episodic memory: event segmentation via Bayesian surprise + two-stage (similarity + temporal-contiguity) retrieval; event boundaries align with human-perceived events. Most cognitively-grounded episodic mechanism -- key reference for the human-like memory project.

2024
Reproduction: TriagedP0Interpretability & Safety

Effective Prompt Extraction from Language Models

By Yiming Zhang, Nicholas Carlini, Daphne Ippolito

Published in: COLM 2024

Citation: Zhang Y, Carlini N, Ippolito D. (2024). Effective Prompt Extraction from Language Models. COLM 2024. arXiv:2307.06865

Notes: Prompt-extraction attack framework across 11 LLMs; relevant to agent/harness security (system-prompt and tool-description leakage).

2023
Reproduction: TriagedP3Agent Architectures

MemoryBank: Enhancing Large Language Models with Long-Term Memory

By Wanjun Zhong, Lianghong Guo, Qiqi Gao, He Ye, Yanlin Wang

Published in: AAAI 2024

Citation: Zhong et al., AAAI 2024

Notes: Long-term memory with Ebbinghaus forgetting curve (time + relevance based updating), demoed via the SiliconFriend companion. Reference for human-like forgetting/decay in the memory system.

2023
Reproduction: TriagedP2Agent Architectures

Reflexion: Language Agents with Verbal Reinforcement Learning

By Noah Shinn, Federico Cassano, Edward Berman, Ashwin Gopinath, Karthik Narasimhan, Shunyu Yao

Published in: NeurIPS 2023

Citation: Shinn et al., NeurIPS 2023

Notes: Verbal reinforcement learning: agent reflects on failures and stores episodic insights in memory for later attempts (91% pass@1 on HumanEval). Reference for episodic self-reflection memory.

2023
Reproduction: TriagedP0Agent Architectures

Generative Agents: Interactive Simulacra of Human Behavior

By Joon Sung Park, Joseph C. O'Brien, Carrie J. Cai, Meredith Ringel Morris, Percy Liang, Michael S. Bernstein

Published in: UIST 2023

Citation: Park et al., UIST 2023

Notes: Canonical 'memory stream': observations stored with timestamp + importance + embedding, retrieved by recency + importance + relevance, plus reflection. Closest prior art to the nanoagent episodic-memory project -- differentiate against this.

2023
Reproduction: TriagedP2Agent Architectures

MemGPT: Towards LLMs as Operating Systems

By Charles Packer, Sarah Wooders, Kevin Lin, Vivian Fang, Shishir G. Patil, Ion Stoica, Joseph E. Gonzalez

Published in: arXiv (2023)

Citation: Packer et al., 2023

Notes: Virtual context management / tiered memory (main context vs external store) with paging, inspired by OS memory hierarchy. Reference for the working-memory + retrieval layer of the nanoagent memory system.

2023
Reproduction: TriagedP3Agent Architectures

Plan4MC: Skill Reinforcement Learning and Planning for Open-World Long-Horizon Tasks

By Haoqi Yuan, Chi Zhang, Hongcheng Wang, Feiyang Xie, Penglin Cai, Hao Dong, Zongqing Lu

Published in: NeurIPS 2023 FMDM Workshop

Citation: Yuan et al., 2023

Notes: Hybrid: RL learns basic skills, LLM builds a skill graph to plan over them. 40 tasks, many requiring >10 sequential skills; strong sample efficiency. Bridges the RL and LLM-agent camps. Open code.

2023
Reproduction: TriagedP0Agent Architectures

Voyager: An Open-Ended Embodied Agent with Large Language Models

By Guanzhi Wang, Yuqi Xie, Yunfan Jiang, Ajay Mandlekar, Chaowei Xiao, Yuke Zhu, Linxi Fan, Anima Anandkumar

Published in: arXiv (2023)

Citation: Wang et al., 2023

Notes: Flagship LLM lifelong-learning agent in Minecraft: automatic curriculum + ever-growing code skill library + iterative prompting loop with self-verification. Black-box GPT-4, no fine-tuning. Maps directly onto building-agents (memory/loop/self-verification). Open code.

2023
Reproduction: TriagedP2Agent Architectures

JARVIS-1: Open-World Multi-task Agents with Memory-Augmented Multimodal Language Models

By Zihao Wang, Shaofei Cai, Anji Liu, Yonggang Jin, Jinbing Hou, Bowei Zhang, Haowei Lin, Zhaofeng He, Zilong Zheng, Yaodong Yang, Xiaojian Ma, Yitao Liang

Published in: arXiv (2023)

Citation: Wang et al., 2023

Notes: Memory-augmented multimodal agent: perceives visual input + instructions, plans, and performs embodied control. 200+ tasks; 5x reliability on ObtainDiamondPickaxe. Successor line to GITM. Open code.

2023
Reproduction: TriagedP2Agent Architectures

Ghost in the Minecraft (GITM): Generally Capable Agents via LLMs with Text-based Knowledge and Memory

By Xizhou Zhu, Yuntao Chen, Hao Tian, Chenxin Tao, Weijie Su, Chenyu Yang, Gao Huang, Bin Li, Lewei Lu, Xiaogang Wang, Yu Qiao, Zhaoxiang Zhang, Jifeng Dai

Published in: arXiv (2023)

Citation: Zhu et al., 2023

Notes: Hierarchical LLM agent (goal -> sub-goal -> action) with text knowledge + memory. Unlocks 100% of Overworld tech tree, +47.5% on ObtainDiamond, ~10,000x more compute-efficient than VPT/DreamerV3. Open code.

2023
Reproduction: TriagedP2Agent Evaluation

SWE-bench: Can Language Models Resolve Real-World GitHub Issues?

By Carlos E. Jimenez, John Yang, Alexander Wettig, Shunyu Yao, Kexin Pei, Ofir Press, Karthik Narasimhan

Published in: ICLR 2024

Citation: Jimenez et al., ICLR 2024

Notes: Canonical agentic coding evaluation harness (2,294 real GitHub issues). Reproduction target for agent evaluation infrastructure.

2023
Reproduction: TriagedP3Agent Architectures

Cognitive Architectures for Language Agents (CoALA)

By Theodore R. Sumers, Shunyu Yao, Karthik Narasimhan, Thomas L. Griffiths

Published in: TMLR 2024

Citation: Sumers et al., TMLR 2024

Notes: Framework connecting modern LLM agents to classical cognitive architectures (SOAR/ACT-R). Best reference for the agentic-systems lineage; reading/reference rather than code reproduction.

2022
Reproduction: TriagedP0Agent Evaluation

MineDojo: Building Open-Ended Embodied Agents with Internet-Scale Knowledge

By Linxi Fan, Guanzhi Wang, Yunfan Jiang, Ajay Mandlekar, Yuncong Yang, Haoyi Zhu, Andrew Tang, De-An Huang, Yuke Zhu, Anima Anandkumar

Published in: NeurIPS 2022 (Outstanding Paper)

Citation: Fan et al., NeurIPS 2022

Notes: Foundational Minecraft benchmark + simulator: 1000s of open-ended tasks, internet-scale knowledge base (videos/wiki/forums), and the MineCLIP learned reward. The environment most Minecraft agents (incl. Voyager) run in. Open source.

2022
Reproduction: TriagedP2Agent Architectures

ReAct: Synergizing Reasoning and Acting in Language Models

By Shunyu Yao, Jeffrey Zhao, Dian Yu, Nan Du, Izhak Shafran, Karthik Narasimhan, Yuan Cao

Published in: ICLR 2023

Citation: Yao et al., ICLR 2023

Notes: Foundational Think-Act-Observe (TAO) loop for LLM agents; the primitive the building-agents curriculum is built on. Baseline reproduction target.

2022
Reproduction: TriagedP3Agent Architectures

Inner Monologue: Embodied Reasoning through Planning with Language Models

By Wenlong Huang, Fei Xia, Ted Xiao, Harris Chan, Jacky Liang, Pete Florence, Andy Zeng, Jonathan Tompson, Igor Mordatch, Yevgen Chebotar, Pierre Sermanet, Noah Brown, Tomas Jackson, Linda Luu, Sergey Levine, Karol Hausman, Brian Ichter

Published in: CoRL 2022

Citation: Huang et al., CoRL 2022

Notes: Closed-loop environment-feedback ('observe') precursor to ReAct, in robotics. Conceptual reference for the origin of the observe step.

1958
Reproduction: TriagedP0Foundations

The Perceptron: A Probabilistic Model for Information Storage and Organization in the Brain

By Frank Rosenblatt

Published in: Psychological Review (1958)

Citation: Rosenblatt, Psychological Review, 65(6):386-408, 1958

Notes: Foundational. Takes the McCulloch-Pitts threshold neuron and adds adaptive weights + an error-driven learning rule, making it trainable from data -- the first precisely specified, trainable neural network and the birth of machine learning from neural models. Replication target: single-line Python perceptron predict + weight-update rule.

1943
Reproduction: TriagedP0Foundations

A Logical Calculus of the Ideas Immanent in Nervous Activity

By Warren S. McCulloch, Walter Pitts

Published in: Bulletin of Mathematical Biophysics (1943)

Citation: McCulloch & Pitts, Bulletin of Mathematical Biophysics, 5:115-133, 1943

Notes: Foundational. Models neurons as binary all-or-none threshold logic units and proves networks of them can compute any propositional/logical function -- the artificial neuron as a logic gate (fixed weights, no learning). Origin of the McCulloch-Pitts neuron; the direct ancestor of Rosenblatt's perceptron. Replication target: single-line Python threshold neuron.

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