Memento: Fine-tuning LLM Agents without Fine-tuning LLMs | Paper Citation Record

Observation 13598bb3-f6dc-415c-9d06-979f931f97f3 · inbound

EvolveR: Self-Evolving LLM Agents through an Experience-Driven Lifecycle cites this paper.

EvolveR: Self-Evolving LLM Agents through an Experience-Driven Lifecycle Memento: Fine-tuning LLM Agents without Fine-tuning LLMs

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-18T06:20:58.308884Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation d3ffd9ee-7469-4d5d-b137-8192b6379e1f · inbound

EvolveR: Self-Evolving LLM Agents through an Experience-Driven Lifecycle cites this paper.

EvolveR: Self-Evolving LLM Agents through an Experience-Driven Lifecycle Memento: Fine-tuning LLM Agents without Fine-tuning LLMs

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-21T20:50:36.459439Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation c984f269-d390-4184-980f-0903e7d01dc2 · inbound

Toward Efficient Agents: Memory, Tool learning, and Planning cites this paper.

Toward Efficient Agents: Memory, Tool learning, and Planning Memento: Fine-tuning LLM Agents without Fine-tuning LLMs

Reference 202

Resolution: unresolved; no resolver link, observed 2026-08-03T09:21:51.389116Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5d53bfc4-5122-4e2e-a3ae-d696dee2c696 · inbound

TAME: A Trustworthy Test-Time Evolution of Agent Memory with Systematic Benchmarking cites this paper.

TAME: A Trustworthy Test-Time Evolution of Agent Memory with Systematic Benchmarking Memento: Fine-tuning LLM Agents without Fine-tuning LLMs

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-03T05:10:16.751969Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4587d50b-25b9-4235-8781-ad7e57ab9df2 · inbound

Gecko: A Simulation Environment with Stateful Feedback for Refining Agent Tool Calls cites this paper.

Gecko: A Simulation Environment with Stateful Feedback for Refining Agent Tool Calls Memento: Fine-tuning LLM Agents without Fine-tuning LLMs

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-02T21:46:33.400151Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 293360a0-956d-497e-9a85-edaba2840448 · inbound

Limits of Spatial Imagery Reasoning in Frontier LLM Models cites this paper.

Limits of Spatial Imagery Reasoning in Frontier LLM Models Memento: Fine-tuning LLM Agents without Fine-tuning LLMs

Reference 34

Resolution: unresolved; no resolver link, observed 2026-07-13T19:19:52.557913Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 239dfe04-2cdc-4035-be8b-d53eb765d31c · inbound

Springdrift: An Auditable Persistent Runtime for LLM Agents with Case-Based Memory, Normative Safety, and Ambient Self-Perception cites this paper.

Springdrift: An Auditable Persistent Runtime for LLM Agents with Case-Based Memory, Normative Safety, and Ambient Self-Perception Memento: Fine-tuning LLM Agents without Fine-tuning LLMs

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-10T23:20:53.238659Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 1df4a510-4035-461e-ab50-079d524360bc · inbound

Externalization in LLM Agents: A Unified Review of Memory, Skills, Protocols and Harness Engineering cites this paper.

Externalization in LLM Agents: A Unified Review of Memory, Skills, Protocols and Harness Engineering Memento: Fine-tuning LLM Agents without Fine-tuning LLMs

Reference 199

Resolution: verified exact; arxiv_id, observed 2026-05-11T06:20:59.320197Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 36a9b71c-5281-4620-a6bf-a13f59729ca2 · inbound

MEMENTO: Teaching LLMs to Manage Their Own Context cites this paper.

MEMENTO: Teaching LLMs to Manage Their Own Context Memento: Fine-tuning LLM Agents without Fine-tuning LLMs

Reference 40

Resolution: verified exact; arxiv_id, observed 2026-05-11T07:10:59.421553Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 095ab774-02a5-4a7b-a197-2b85aaa2020e · inbound

StepPO: Step-Aligned Policy Optimization for Agentic Reinforcement Learning cites this paper.

StepPO: Step-Aligned Policy Optimization for Agentic Reinforcement Learning Memento: Fine-tuning LLM Agents without Fine-tuning LLMs

Reference 43

Resolution: verified exact; local_arxiv, observed 2026-07-05T12:30:59.993544Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 6dac5018-cacc-4684-818d-d1b3b5a50b92 · inbound

From Skills to Talent: Organising Heterogeneous Agents as a Real-World Company cites this paper.

From Skills to Talent: Organising Heterogeneous Agents as a Real-World Company Memento: Fine-tuning LLM Agents without Fine-tuning LLMs

Reference 45

Resolution: verified exact; arxiv_id, observed 2026-05-11T19:21:09.535981Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 24239de4-d8d8-45f2-829d-4e5bb4e3643d · inbound

Skill1: Unified Evolution of Skill-Augmented Agents via Reinforcement Learning cites this paper.

Skill1: Unified Evolution of Skill-Augmented Agents via Reinforcement Learning Memento: Fine-tuning LLM Agents without Fine-tuning LLMs

Reference 67

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T20:06:08.530363Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation e2494e93-c5ee-4a1f-89bf-86e4d93a6650 · inbound

Skill1: Unified Evolution of Skill-Augmented Agents via Reinforcement Learning cites this paper.

Skill1: Unified Evolution of Skill-Augmented Agents via Reinforcement Learning Memento: Fine-tuning LLM Agents without Fine-tuning LLMs

Reference 67

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T04:00:56.884914Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 1a05a3ba-2655-4846-aeca-c342f1afae09 · inbound

Skill1: Unified Evolution of Skill-Augmented Agents via Reinforcement Learning cites this paper.

Skill1: Unified Evolution of Skill-Augmented Agents via Reinforcement Learning Memento: Fine-tuning LLM Agents without Fine-tuning LLMs

Reference 67

Resolution: metadata mismatch; arxiv_id, observed 2026-05-13T07:17:28.195272Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 256ba3ac-72bf-45fc-9ef1-aaeda55448ff · inbound

CASCADE: Case-Based Continual Adaptation for Large Language Models During Deployment cites this paper.

CASCADE: Case-Based Continual Adaptation for Large Language Models During Deployment Memento: Fine-tuning LLM Agents without Fine-tuning LLMs

Reference 67

Resolution: verified exact; arxiv_id, observed 2026-05-11T04:30:59.611353Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation e5b25611-39bd-4e7b-a3ef-0f73850e5bd7 · inbound

Learning Agent Routing From Early Experience cites this paper.

Learning Agent Routing From Early Experience Memento: Fine-tuning LLM Agents without Fine-tuning LLMs

Reference 22

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T04:35:57.682196Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 2bb55553-b962-4819-8afe-fc7ef746a33b · inbound

Ace-Skill: Bootstrapping Multimodal Agents with Prioritized and Clustered Evolution cites this paper.

Ace-Skill: Bootstrapping Multimodal Agents with Prioritized and Clustered Evolution Memento: Fine-tuning LLM Agents without Fine-tuning LLMs

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-12T08:01:27.358932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 02e819e8-c2df-4240-9a37-8ab215a5399f · inbound

Skill-R1: Agent Skill Evolution via Reinforcement Learning cites this paper.

Skill-R1: Agent Skill Evolution via Reinforcement Learning Memento: Fine-tuning LLM Agents without Fine-tuning LLMs

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-05-12T06:41:44.748653Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 2ecd8f46-952a-46c8-b844-aa91c6c67b0b · inbound

Evolving-RL: End-to-End Optimization of Experience-Driven Self-Evolving Capability within Agents cites this paper.

Evolving-RL: End-to-End Optimization of Experience-Driven Self-Evolving Capability within Agents Memento: Fine-tuning LLM Agents without Fine-tuning LLMs

Reference 41

Resolution: verified exact; arxiv_id, observed 2026-05-12T05:16:22.385504Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation b33c8a81-eece-4978-8dda-b4ec1b0bef32 · inbound

OLIVIA: Online Learning via Inference-time Action Adaptation for Decision Making in LLM ReAct Agents cites this paper.

OLIVIA: Online Learning via Inference-time Action Adaptation for Decision Making in LLM ReAct Agents Memento: Fine-tuning LLM Agents without Fine-tuning LLMs

Reference 37

Resolution: metadata mismatch; arxiv_id, observed 2026-05-13T02:27:07.327624Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation fdb187ff-d68f-4f67-bb1e-c5c5a9065d5f · inbound

PREPING: Building Agent Memory without Tasks cites this paper.

PREPING: Building Agent Memory without Tasks Memento: Fine-tuning LLM Agents without Fine-tuning LLMs

Reference 40

Resolution: verified exact; arxiv_id, observed 2026-05-15T06:15:06.177778Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 8deb4528-1e45-46f2-b913-62929562780e · inbound

Improving Multi-turn Dialogue Consistency with Self-Recall Thinking cites this paper.

Improving Multi-turn Dialogue Consistency with Self-Recall Thinking Memento: Fine-tuning LLM Agents without Fine-tuning LLMs

Reference 43

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T20:25:02.584817Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 27397d33-092c-4fd1-8145-49e46611e1b3 · inbound

Is One Score Enough? Rethinking the Evaluation of Sequentially Evolving LLM Memory cites this paper.

Is One Score Enough? Rethinking the Evaluation of Sequentially Evolving LLM Memory Memento: Fine-tuning LLM Agents without Fine-tuning LLMs

Reference 47

Resolution: malformed identifier; arxiv_id, observed 2026-05-19T16:47:40.473513Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 2cacef47-1d67-437e-951b-f69017f6f6be · inbound

SkillsVote: Lifecycle Governance of Agent Skills from Collection, Recommendation to Evolution cites this paper.

SkillsVote: Lifecycle Governance of Agent Skills from Collection, Recommendation to Evolution Memento: Fine-tuning LLM Agents without Fine-tuning LLMs

Reference 79

Resolution: verified exact; arxiv_id, observed 2026-05-20T11:43:15.013021Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 0fa07cc2-6de9-4eb0-bd44-6f4ef6ea89f6 · inbound

EvoMemBench: Benchmarking Agent Memory from a Self-Evolving Perspective cites this paper.

EvoMemBench: Benchmarking Agent Memory from a Self-Evolving Perspective Memento: Fine-tuning LLM Agents without Fine-tuning LLMs

Reference 45

Resolution: verified exact; arxiv_id, observed 2026-05-20T11:38:14.578006Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation bf4446b8-555e-4ac1-9580-1522dcbdd949 · inbound

Memory-Augmented Reinforcement Learning Agent for CAD Generation cites this paper.

Memory-Augmented Reinforcement Learning Agent for CAD Generation Memento: Fine-tuning LLM Agents without Fine-tuning LLMs

Reference 85

Resolution: verified exact; arxiv_id, observed 2026-05-20T05:18:03.007489Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 0c38fdad-c413-45f9-ac78-d2b42d9e1f04 · inbound

SOLAR: A Self-Optimizing Open-Ended Autonomous Agent for Lifelong Learning and Continual Adaptation cites this paper.

SOLAR: A Self-Optimizing Open-Ended Autonomous Agent for Lifelong Learning and Continual Adaptation Memento: Fine-tuning LLM Agents without Fine-tuning LLMs

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-05-21T11:24:08.648403Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation a998856b-e58e-45f7-b74c-b801195e126e · inbound

Mem-$\pi$: Adaptive Memory through Learning When and What to Generate cites this paper.

Mem-$\pi$: Adaptive Memory through Learning When and What to Generate Memento: Fine-tuning LLM Agents without Fine-tuning LLMs

Reference 61

Resolution: verified exact; arxiv_id, observed 2026-05-21T04:29:34.531512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 201fa67b-7c31-4f3e-8238-eb99600ac06a · inbound

Dynamic Mixture of Latent Memories for Self-Evolving Agents cites this paper.

Dynamic Mixture of Latent Memories for Self-Evolving Agents Memento: Fine-tuning LLM Agents without Fine-tuning LLMs

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-22T07:41:14.514791Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 71fea5f3-9fc4-47ed-8a2a-dd60f0d9d4fc · inbound

Rethinking Memory as Continuously Evolving Connectivity cites this paper.

Rethinking Memory as Continuously Evolving Connectivity Memento: Fine-tuning LLM Agents without Fine-tuning LLMs

Reference 68

Resolution: verified exact; arxiv_id, observed 2026-06-29T12:33:24.771585Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 8f429dec-497c-4e28-8436-6d43df1c493a · inbound

Traj-Evolve: A Self-Evolving Multi-Agent System for Patient Trajectory Modeling in Lung Cancer Early Detection cites this paper.

Traj-Evolve: A Self-Evolving Multi-Agent System for Patient Trajectory Modeling in Lung Cancer Early Detection Memento: Fine-tuning LLM Agents without Fine-tuning LLMs

Reference 44

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T23:26:22.857531Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 9972521f-5436-4174-a1cb-ec1304e1f703 · inbound

Autonomous heterogeneous catalyst discovery with a self-evolving multi-agent digital twin cites this paper.

Autonomous heterogeneous catalyst discovery with a self-evolving multi-agent digital twin Memento: Fine-tuning LLM Agents without Fine-tuning LLMs

Reference 47

Resolution: verified exact; arxiv_id, observed 2026-07-02T10:16:52.246115Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation b42d344f-1d45-4050-82c5-57606c0550f8 · inbound

Autonomous heterogeneous catalyst discovery with a self-evolving multi-agent digital twin cites this paper.

Autonomous heterogeneous catalyst discovery with a self-evolving multi-agent digital twin Memento: Fine-tuning LLM Agents without Fine-tuning LLMs

Reference 47

Resolution: unresolved; no resolver link, observed 2026-07-12T15:08:52.399613Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ebea1725-4017-4418-8ccf-d907c8d30f2b · inbound

Towards Persistent Case-Based Memory for Autonomous Data Science: A CBR-Augmented R&D-Agent with a Locally Deployable Small Language Model cites this paper.

Towards Persistent Case-Based Memory for Autonomous Data Science: A CBR-Augmented R&D-Agent with a Locally Deployable Small Language Model Memento: Fine-tuning LLM Agents without Fine-tuning LLMs

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-07-02T10:06:51.721800Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 953caccc-749b-4579-812a-281b32bea8fe · inbound

Rosetta Memory: Adaptive Memory for Cross-LLM Agents cites this paper.

Rosetta Memory: Adaptive Memory for Cross-LLM Agents Memento: Fine-tuning LLM Agents without Fine-tuning LLMs

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-07-02T16:27:09.167392Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 6d86e0ee-e354-4dae-992d-157fb554d353 · inbound

From Player to Master: Enhancing Test-Time Learning of LLM Agents via Reinforcement Learning over Memory cites this paper.

From Player to Master: Enhancing Test-Time Learning of LLM Agents via Reinforcement Learning over Memory Memento: Fine-tuning LLM Agents without Fine-tuning LLMs

Reference 21

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T22:37:25.570346Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation cc670e79-6e3e-4094-a0c4-a1ebd6290b17 · inbound

Co-Evolving Skill Generation and Policy Optimization cites this paper.

Co-Evolving Skill Generation and Policy Optimization Memento: Fine-tuning LLM Agents without Fine-tuning LLMs

Reference 52

Resolution: verified exact; arxiv_id, observed 2026-07-02T22:57:25.867397Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 20012c67-21d6-4ee8-87e3-fbf02d1b707b · inbound

Experience Makes Skillful: Enabling Generalizable Medical Agent Reasoning via Self-Evolving Skill Memory cites this paper.

Experience Makes Skillful: Enabling Generalizable Medical Agent Reasoning via Self-Evolving Skill Memory Memento: Fine-tuning LLM Agents without Fine-tuning LLMs

Reference 93

Resolution: verified exact; arxiv_id, observed 2026-07-03T01:07:30.901726Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation d15a8cee-714e-45ab-88e6-f26b15fc9c46 · inbound

Organize then Retrieve: Hierarchical Memory Navigation for Efficient Agents cites this paper.

Organize then Retrieve: Hierarchical Memory Navigation for Efficient Agents Memento: Fine-tuning LLM Agents without Fine-tuning LLMs

Reference 64

Resolution: verified exact; arxiv_id, observed 2026-07-03T10:17:57.786546Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 17791f13-60a2-465e-99f9-2bed9748312a · inbound

HarnessX: A Composable, Adaptive, and Evolvable Agent Harness Foundry cites this paper.

HarnessX: A Composable, Adaptive, and Evolvable Agent Harness Foundry Memento: Fine-tuning LLM Agents without Fine-tuning LLMs

Reference 50

Resolution: verified exact; arxiv_id, observed 2026-07-03T23:49:01.950818Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation a0bc0eda-3d0a-4ece-b4ab-b37a65addb61 · inbound

HarnessX: A Composable, Adaptive, and Evolvable Agent Harness Foundry cites this paper.

HarnessX: A Composable, Adaptive, and Evolvable Agent Harness Foundry Memento: Fine-tuning LLM Agents without Fine-tuning LLMs

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-02T11:34:38.419445Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b310bbe9-b8cc-4849-b08a-1b9738e830f0 · inbound

Metis: Bridging Text and Code Memory for Self-Evolving Agents cites this paper.

Metis: Bridging Text and Code Memory for Self-Evolving Agents Memento: Fine-tuning LLM Agents without Fine-tuning LLMs

Reference 15

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T16:29:56.686562Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation f7800b70-145f-4056-b4ad-493a2e04a069 · inbound

Metadata, Structure, or Strategy? A Decomposition of RAG Context Enrichment cites this paper.

Metadata, Structure, or Strategy? A Decomposition of RAG Context Enrichment Memento: Fine-tuning LLM Agents without Fine-tuning LLMs

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-06-30T08:04:28.987880Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 2572ebf9-2e73-468d-8129-a793dfc3c15b · inbound

The Past Is Prologue: A Plug-in Controller for Selective Updates in Sequentially Evolving LLM Memory cites this paper.

The Past Is Prologue: A Plug-in Controller for Selective Updates in Sequentially Evolving LLM Memory Memento: Fine-tuning LLM Agents without Fine-tuning LLMs

Reference 14

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T09:55:41.327443Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation acaae7d4-6702-4255-a879-3460198171d9 · inbound

Procedural Memory Distillation: Online Reflection for Self-Improving Language Models cites this paper.

Procedural Memory Distillation: Online Reflection for Self-Improving Language Models Memento: Fine-tuning LLM Agents without Fine-tuning LLMs

Reference 55

Resolution: malformed identifier; arxiv_id, observed 2026-07-03T20:18:56.014458Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 4fd3c584-d20e-43a3-99de-237289701b2e · inbound

MILES: Modular Instruction Memory with Learnable Selection for Self-Improving LLM Reasoning cites this paper.

MILES: Modular Instruction Memory with Learnable Selection for Self-Improving LLM Reasoning Memento: Fine-tuning LLM Agents without Fine-tuning LLMs

Reference 56

Resolution: verified exact; local_arxiv, observed 2026-07-09T00:45:49.095352Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 67337803-f765-4c3c-a6a0-049126c52381 · inbound

PaperRouter-Agent: A Content-Grounded LLM Agent for Personalized Hierarchical Paper Routing cites this paper.

PaperRouter-Agent: A Content-Grounded LLM Agent for Personalized Hierarchical Paper Routing Memento: Fine-tuning LLM Agents without Fine-tuning LLMs

Reference 38

Resolution: malformed identifier; no resolver link, observed 2026-07-14T04:44:31.914813Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f69e9f30-401d-43be-a7ac-0be8716c55f7 · inbound

From Memory to Skills: Evidence-Grounded Co-Evolution Governance for Long-Horizon LLM Agents cites this paper.

From Memory to Skills: Evidence-Grounded Co-Evolution Governance for Long-Horizon LLM Agents Memento: Fine-tuning LLM Agents without Fine-tuning LLMs

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-01T20:27:35.178457Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c3990bea-4520-4ba9-9063-416411a535bd · inbound

From Blind Search to Memory-Aware Evolution: Efficient DBMS Tuning via Collaborative Diagnosis and Utility-Aware Retrieval cites this paper.

From Blind Search to Memory-Aware Evolution: Efficient DBMS Tuning via Collaborative Diagnosis and Utility-Aware Retrieval Memento: Fine-tuning LLM Agents without Fine-tuning LLMs

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-01T16:55:09.255144Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 88d8fbbb-bced-43e1-a504-641f056d9d48 · inbound

Mi-Memory: A Lifecycle Memory Framework for Personal AI cites this paper.

Mi-Memory: A Lifecycle Memory Framework for Personal AI Memento: Fine-tuning LLM Agents without Fine-tuning LLMs

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-01T13:52:28.713121Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7f9669d1-5304-4fc8-8c2a-5eb5622d9976 · inbound

SkillSmith: Learning to Compose Parametric Skills and Textual Knowledge cites this paper.

SkillSmith: Learning to Compose Parametric Skills and Textual Knowledge Memento: Fine-tuning LLM Agents without Fine-tuning LLMs

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-01T06:52:15.811630Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c6482c7a-73cc-4eeb-9a3c-c0f6c7fe5637 · inbound

Training Skills Like Parameters via Self-Supervised Semantic Diffusion cites this paper.

Training Skills Like Parameters via Self-Supervised Semantic Diffusion Memento: Fine-tuning LLM Agents without Fine-tuning LLMs

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-01T05:47:43.309709Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c4397712-8c74-4ea3-bb83-971794c097e9 · inbound

ARES: Adaptive Reasoning-Effort Steering for PPA- and Cost-Aware RTL Optimization with LLM Agents cites this paper.

ARES: Adaptive Reasoning-Effort Steering for PPA- and Cost-Aware RTL Optimization with LLM Agents Memento: Fine-tuning LLM Agents without Fine-tuning LLMs

Reference 42

Resolution: unresolved; no resolver link, observed 2026-07-31T23:48:06.605320Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3eae2184-c78d-4153-b98b-ae7922e7dc3b · inbound

Memory Reward Inflation in Self-Improving LLM Agents cites this paper.

Memory Reward Inflation in Self-Improving LLM Agents Memento: Fine-tuning LLM Agents without Fine-tuning LLMs

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-04T02:16:41.032797Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Reference resolution

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