Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation | Paper Citation Record

Observation f9d8f3db-d9de-490a-8223-3f6f2628c43e · outbound

This paper cites LLM-PySC2: Starcraft II learning environment for Large Language Models.

Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation LLM-PySC2: Starcraft II learning environment for Large Language Models

Reference 1

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This paper cites Large Language Models Play StarCraft II: Benchmarks and a Chain of Summarization Approach.

Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation Large Language Models Play StarCraft II: Benchmarks and a Chain of Summarization Approach

Reference 2

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Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation SwarmBrain: Embodied agent for real-time strategy game StarCraft II via large language models

Reference 3

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This paper cites Hierarchical Expert Prompt for Large-Language-Model: An Approach Defeat Elite AI in TextStarCraft II for the First Time.

Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation Hierarchical Expert Prompt for Large-Language-Model: An Approach Defeat Elite AI in TextStarCraft II for the First Time

Reference 4

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This paper cites ChatDev: Communicative Agents for Software Development.

Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation ChatDev: Communicative Agents for Software Development

Reference 5

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This paper cites F., An, B.,et al., Lu, Z.

Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation F., An, B.,et al., Lu, Z

Reference 6

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Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation Unresolved cited work

Reference 7

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Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation Unresolved cited work

Reference 8

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Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation Unresolved cited work

Reference 9

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This paper cites TradingAgents: Multi-Agents LLM Financial Trading Framework.

Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation TradingAgents: Multi-Agents LLM Financial Trading Framework

Reference 10

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This paper cites Ghanem, B.

Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation Ghanem, B

Reference 11

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This paper cites , Anandkumar, A.

Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation , Anandkumar, A

Reference 12

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Observation c46ee15d-e182-44c1-bdbc-88f060d6f59a · outbound

This paper cites Exploring Large Language Models for Communication Games: An Empirical Study on Werewolf.

Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation Exploring Large Language Models for Communication Games: An Empirical Study on Werewolf

Reference 13

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This paper cites Reflection of Episodes: Learning to Play Game from Expert and Self Experiences.

Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation Reflection of Episodes: Learning to Play Game from Expert and Self Experiences

Reference 14

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Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation SMAC-Hard: Enabling Mixed Opponent Strategy Script and Self-play on SMAC

Reference 15

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This paper cites Ghost in the Minecraft: Generally Capable Agents for Open-World Environments via Large Language Models with Text-based Knowledge and Memory.

Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation Ghost in the Minecraft: Generally Capable Agents for Open-World Environments via Large Language Models with Text-based Knowledge and Memory

Reference 16

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This paper cites Zijlstra, M.

Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation Zijlstra, M

Reference 17

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This paper cites LLaMA Rider: Spurring Large Language Models to Explore the Open World.

Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation LLaMA Rider: Spurring Large Language Models to Explore the Open World

Reference 18

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This paper cites Reinforcement Learning Enhanced LLMs: A Survey.

Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation Reinforcement Learning Enhanced LLMs: A Survey

Reference 19

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Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation SMAC-R1: The Emergence of Intelligence in Decision-Making Tasks

Reference 20

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This paper cites Voyager: An Open-Ended Embodied Agent with Large Language Models.

Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation Voyager: An Open-Ended Embodied Agent with Large Language Models

Reference 21

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Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation Playing Atari with Deep Reinforcement Learning

Reference 22

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Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation Value-Decomposition Networks For Cooperative Multi-Agent Learning

Reference 23

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Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation S., Farquhar, G., Foerster,et al.J.,Whiteson, S

Reference 24

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Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation Continuous control with deep reinforcement learning

Reference 25

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Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation Proximal Policy Optimization Algorithms

Reference 26

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This paper cites Grandmaster Level in StarCraft II Using Multi-Agent Reinforcement Learning.

Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation Grandmaster Level in StarCraft II Using Multi-Agent Reinforcement Learning

Reference 27

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Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation DI-star: An Open-source Reinforcement Learning Framework for StarCraft II

Reference 28

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Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation s1: Simple test-time scaling

Reference 29

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Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation Can 1B LLM Surpass 405B LLM? Rethinking Compute-Optimal Test-Time Scaling

Reference 30

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Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation TTRL: Test-Time Reinforcement Learning

Reference 31

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Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation How Much Can RAG Help the Reasoning of LLM?

Reference 32

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Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation Always concentrating all teams' fire at one unit that (1)with highest DPS(most valuable) (2)most vulnerable (3)closest

Reference 33

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Reference 34

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Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation Unresolved cited work

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Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation Unresolved cited work

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Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation Also, you will be provided with 'existing_hypothesis'

Reference 38

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Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation Unresolved cited work

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Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation Unresolved cited work

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Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation Unresolved cited work

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Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation Unresolved cited work

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This paper cites Please carefully and accurately analyse costs and benefits and compare whether the benefits outweigh the losses.

Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation Please carefully and accurately analyse costs and benefits and compare whether the benefits outweigh the losses

Reference 44

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Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation This is a xxxxx (excellent/good/bad/terrible) hypothesis

Reference 45

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This paper cites Always concentrating all teams' fire at one unit that (1)with highest DPS(most valuable) (2)most vulnerable (3)closest.

Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation Always concentrating all teams' fire at one unit that (1)with highest DPS(most valuable) (2)most vulnerable (3)closest

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:32:21.391322Z

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Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation Unresolved cited work

Reference 47

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Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation Unresolved cited work

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Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation Its advantages include xxxx

Reference 49

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Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation Unresolved cited work

Reference 50

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Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation Unresolved cited work

Reference 51

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Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation hypothesis

Reference 52

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Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation Unresolved cited work

Reference 53

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Observation 924745fc-3984-4a77-b9d8-fdf4a3c568cd · outbound

This paper cites This provides a better angle for further attacks and minimizes the risk of being trapped.

Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation This provides a better angle for further attacks and minimizes the risk of being trapped

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:32:21.221796Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 6b4bf407-a8a5-410f-8267-a1552ec97188 · outbound

This paper cites experience-0.

Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation experience-0

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:32:21.208948Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d1e48320-c928-4b32-8821-0f8f0404ad0a · outbound

This paper cites an unresolved cited work.

Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation Unresolved cited work

Reference 56

Resolution: unresolved; raw_fallback, observed 2026-08-16T04:32:21.195863Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 63109b26-378c-4fa6-8ce4-905c9db5b96e · outbound

This paper cites an unresolved cited work.

Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation Unresolved cited work

Reference 57

Resolution: unresolved; raw_fallback, observed 2026-08-16T04:32:21.183115Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d4cab0d6-79a4-4ef2-b4de-c7866052ceab · outbound

This paper cites , "a_t1":.

Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation , "a_t1":

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:32:21.170076Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation ab645780-3a69-44e2-b718-8e7652ee3a3b · outbound

This paper cites The attack on the Zealot (tag: 0x1000c0001) and the move to [16, 15] are both legal actions according to the valid action list.

Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation The attack on the Zealot (tag: 0x1000c0001) and the move to [16, 15] are both legal actions according to the valid action list

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:32:21.156890Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation cc1f7e53-2818-4fef-b614-fcbd433d8b64 · outbound

This paper cites skills/abilities -> attack -> move.

Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation skills/abilities -> attack -> move

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:32:21.143960Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 09128ee1-3ef4-4236-9add-9daab9fc3c85 · outbound

This paper cites The Stalkers are only performing attacks and moves, which is appropriate for the current situation.

Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation The Stalkers are only performing attacks and moves, which is appropriate for the current situation

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:32:21.130474Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b760d2d6-6be7-4d30-b90f-9dace8566f5d · outbound

This paper cites By targeting the weak Zealot, the Stalkers aim to eliminate the lowest-health unit quickly.

Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation By targeting the weak Zealot, the Stalkers aim to eliminate the lowest-health unit quickly

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:32:21.116986Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 1fbc0ed5-7e32-457d-bb63-4d9b91f75174 · outbound

This paper cites , "a_t1":.

Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation , "a_t1":

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:32:21.103579Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 2557f1e1-c4f7-4426-9111-8d419f83a029 · outbound

This paper cites an unresolved cited work.

Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation Unresolved cited work

Reference 64

Resolution: unresolved; raw_fallback, observed 2026-08-16T04:32:21.089890Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 76074455-56f1-44e3-b3e9-476959103044 · outbound

This paper cites Kill as much as enemy units as possible and avoid losing units.

Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation Kill as much as enemy units as possible and avoid losing units

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:32:21.075843Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation ea06ed01-3a4e-4988-8363-80e1b3ae21ad · outbound

This paper cites The <Attack_Unit(tag)> would likely result in the elimination of this Zealot, reducing the enemy threat significantly.

Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation The **<Attack_Unit(tag)>** would likely result in the elimination of this Zealot, reducing the enemy threat significantly

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:32:21.059187Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d9b9bc31-d37c-4bd8-a54a-211c33752909 · outbound

This paper cites hypothesis\.

Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation hypothesis\

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:32:21.045091Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 213b54d5-8f4c-4647-b907-34a948aecaad · outbound

This paper cites Concentrated Fire (Most Vulnerable Unit).

Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation Concentrated Fire (Most Vulnerable Unit)

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:32:21.016692Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 695b01a8-ea3a-4946-a1f4-42d5e53c3901 · outbound

This paper cites an unresolved cited work.

Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation Unresolved cited work

Reference 70

Resolution: unresolved; raw_fallback, observed 2026-08-16T04:32:21.031238Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 4cd715f9-d4bf-4664-ab41-d151f21c26c5 · outbound

This paper cites Concentrated Fire (Most Vulnerable Unit).

Retrieval Augmented Learning: A Retrial-based Large Language Model Self-Supervised Learning and Autonomous Knowledge Generation Concentrated Fire (Most Vulnerable Unit)

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:32:21.002638Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers