Paper Citation Record · LEDGER

MiniCPM4: Ultra-Efficient LLMs on End Devices

As of 7 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 24 inbound Pith citation observations for arXiv:2506.07900.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2506.07900 v2

Coverage vector

measured 44 of 44 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:31:22.729139Z

measured 68 of 68 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 24 of 24 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T23:24:00.992793Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-07-02T19:47:19.779661Z

Reference resolution

44 of 44 outbound references displayed

verified exact0
verified fuzzy1
unresolved43
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4040efea-bba9-40f9-82f9-60fc2ba3ed7f · outbound

This paper cites Phi-4 Technical Report.

MiniCPM4: Ultra-Efficient LLMs on End Devices Phi-4 Technical Report

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T05:31:18.875371Z

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Observation 6a28f7e1-ff55-45c8-98e4-2c82ae95876f · outbound

This paper cites Scaling Optimal LR Across Token Horizons.

MiniCPM4: Ultra-Efficient LLMs on End Devices Scaling Optimal LR Across Token Horizons

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T05:31:19.177588Z

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Observation 2741925e-a400-42f9-9af0-29148327eb32 · outbound

This paper cites On the Opportunities and Risks of Foundation Models.

MiniCPM4: Ultra-Efficient LLMs on End Devices On the Opportunities and Risks of Foundation Models

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T05:31:19.248712Z

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Observation 7abf9a29-f4fc-4523-9c1f-058dacbe44b9 · outbound

This paper cites Accelerating Large Language Model Decoding with Speculative Sampling.

MiniCPM4: Ultra-Efficient LLMs on End Devices Accelerating Large Language Model Decoding with Speculative Sampling

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T05:31:19.312242Z

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Observation 28ffb747-e7b7-44dd-b8da-adfc54dde3dd · outbound

This paper cites PrefixQuant: Eliminating Outliers by Prefixed Tokens for Large Language Models Quantization.

MiniCPM4: Ultra-Efficient LLMs on End Devices PrefixQuant: Eliminating Outliers by Prefixed Tokens for Large Language Models Quantization

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T05:31:19.504337Z

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Observation c7199424-90ad-4a24-adcb-4138d50c8db6 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

MiniCPM4: Ultra-Efficient LLMs on End Devices Training Verifiers to Solve Math Word Problems

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T05:31:19.583221Z

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Observation 5894efcb-26ba-4c7c-9726-709c936a6d30 · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

MiniCPM4: Ultra-Efficient LLMs on End Devices DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T05:31:19.740928Z

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Observation 4023f1a7-3a0a-43a9-adc1-72371e797054 · outbound

This paper cites LongRoPE: Extending LLM Context Window Beyond 2 Million Tokens.

MiniCPM4: Ultra-Efficient LLMs on End Devices LongRoPE: Extending LLM Context Window Beyond 2 Million Tokens

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T05:31:19.832284Z

Source-reported events for the cited work

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Observation af373711-54ae-471f-8020-88eb87640fd6 · outbound

This paper cites LongRoPE: Extending LLM Context Window Beyond 2 Million Tokens.

MiniCPM4: Ultra-Efficient LLMs on End Devices LongRoPE: Extending LLM Context Window Beyond 2 Million Tokens

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T05:31:19.897369Z

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Observation 54a4433f-df02-4a02-a324-a4625949e638 · outbound

This paper cites Scaling Synthetic Data Creation with 1,000,000,000 Personas.

MiniCPM4: Ultra-Efficient LLMs on End Devices Scaling Synthetic Data Creation with 1,000,000,000 Personas

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T05:31:19.962339Z

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Observation 3cafe3a1-3eeb-486b-b71b-d91909d676b8 · outbound

This paper cites ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Tools.

MiniCPM4: Ultra-Efficient LLMs on End Devices ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Tools

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T05:31:20.054521Z

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Observation 300ac078-28c9-4b39-9828-f062674a38d1 · outbound

This paper cites Apple intelligence foundation language models.

MiniCPM4: Ultra-Efficient LLMs on End Devices Apple intelligence foundation language models

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T05:31:20.120366Z

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Observation f46c26c9-89be-4b62-845c-aeb52577a1fe · outbound

This paper cites an unresolved cited work.

MiniCPM4: Ultra-Efficient LLMs on End Devices Unresolved cited work

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T05:31:20.247421Z

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Observation a4846314-5108-45f7-876b-0ff002f42000 · outbound

This paper cites Training Compute-Optimal Large Language Models.

MiniCPM4: Ultra-Efficient LLMs on End Devices Training Compute-Optimal Large Language Models

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T05:31:20.342343Z

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Observation ae5aad4f-303b-4140-8d82-09fbefbe7a82 · outbound

This paper cites Training Compute-Optimal Large Language Models.

MiniCPM4: Ultra-Efficient LLMs on End Devices Training Compute-Optimal Large Language Models

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T05:31:20.437199Z

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Observation 8a8ab57b-3cfd-4e86-b5b9-64c74d1318b8 · outbound

This paper cites MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies.

MiniCPM4: Ultra-Efficient LLMs on End Devices MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T05:31:20.509228Z

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Observation d3baa7e2-407d-4ade-bd7e-31ab609914e9 · outbound

This paper cites MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies.

MiniCPM4: Ultra-Efficient LLMs on End Devices MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T05:31:20.607735Z

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Observation a29c74cb-59e9-4b63-8444-ff4fa44a6b03 · outbound

This paper cites Scaling Laws for Neural Language Models.

MiniCPM4: Ultra-Efficient LLMs on End Devices Scaling Laws for Neural Language Models

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-07T05:31:20.683952Z

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Observation 1165ea7f-1d20-4208-a608-7a64ed3ef045 · outbound

This paper cites DataComp-LM: In search of the next generation of training sets for language models.

MiniCPM4: Ultra-Efficient LLMs on End Devices DataComp-LM: In search of the next generation of training sets for language models

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T05:31:20.740587Z

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Observation 06112a24-3f9e-4f7d-abf7-5a6945c2f4dc · outbound

This paper cites DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model.

MiniCPM4: Ultra-Efficient LLMs on End Devices DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T05:31:20.819152Z

Source-reported events for the cited work

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Observation fd626aa0-ded1-4ca9-98d3-9511ef8d26b7 · outbound

This paper cites FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generation.

MiniCPM4: Ultra-Efficient LLMs on End Devices FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generation

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T05:31:20.935628Z

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Observation 572b4ac6-899e-45a9-ad87-6a54e8cb530f · outbound

This paper cites GPT-4 Technical Report.

MiniCPM4: Ultra-Efficient LLMs on End Devices GPT-4 Technical Report

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-07T05:31:20.998847Z

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Observation d43fbc7e-88cc-4c75-86c3-c03bcc1bcc5b · outbound

This paper cites OpenAI o1 System Card.

MiniCPM4: Ultra-Efficient LLMs on End Devices OpenAI o1 System Card

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T05:31:21.055300Z

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Observation 3f794b23-b4c3-45b6-85d4-85bdb74c32eb · outbound

This paper cites YaRN: Efficient Context Window Extension of Large Language Models.

MiniCPM4: Ultra-Efficient LLMs on End Devices YaRN: Efficient Context Window Extension of Large Language Models

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T05:31:21.131165Z

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Observation b3d2b179-1be3-4f03-bca5-fed19fe14733 · outbound

This paper cites Pre-trained Models for Natural Language Processing: A Survey.

MiniCPM4: Ultra-Efficient LLMs on End Devices Pre-trained Models for Natural Language Processing: A Survey

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T05:31:21.251814Z

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Observation 226e7c60-3884-4c98-b3d7-f4d9861882ad · outbound

This paper cites Gemma 3 Technical Report.

MiniCPM4: Ultra-Efficient LLMs on End Devices Gemma 3 Technical Report

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-07T05:31:21.459435Z

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Observation edd32e32-ab94-458e-8851-249b94bef12e · outbound

This paper cites CCI3.0-HQ: a large-scale Chinese dataset of high quality designed for pre-training large language models.

MiniCPM4: Ultra-Efficient LLMs on End Devices CCI3.0-HQ: a large-scale Chinese dataset of high quality designed for pre-training large language models

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-07T05:31:21.709208Z

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Observation 4b6d2b2d-3ebe-498e-aff6-a592566f440d · outbound

This paper cites MiMo: Unlocking the Reasoning Potential of Language Model -- From Pretraining to Posttraining.

MiniCPM4: Ultra-Efficient LLMs on End Devices MiMo: Unlocking the Reasoning Potential of Language Model -- From Pretraining to Posttraining

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-07T05:31:21.843081Z

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Observation 9db46184-a4d4-4d3b-b225-9c60b5f86560 · outbound

This paper cites Densing Law of LLMs.

MiniCPM4: Ultra-Efficient LLMs on End Devices Densing Law of LLMs

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-07T05:31:21.920986Z

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Observation 48f39df3-a01a-476c-b7ea-8e6b7087f981 · outbound

This paper cites XAttention: Block Sparse Attention with Antidiagonal Scoring.

MiniCPM4: Ultra-Efficient LLMs on End Devices XAttention: Block Sparse Attention with Antidiagonal Scoring

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-07T05:31:22.029658Z

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Observation be46e805-0613-44d6-a6cc-3e26a1c5d35f · outbound

This paper cites Qwen3 Technical Report.

MiniCPM4: Ultra-Efficient LLMs on End Devices Qwen3 Technical Report

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-07T05:31:22.117240Z

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Observation 40a7be92-1fac-4728-bf5c-e254c7922771 · outbound

This paper cites Tensor Programs V: Tuning Large Neural Networks via Zero-Shot Hyperparameter Transfer.

MiniCPM4: Ultra-Efficient LLMs on End Devices Tensor Programs V: Tuning Large Neural Networks via Zero-Shot Hyperparameter Transfer

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-07T05:31:22.209465Z

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Observation 658ddb29-6ca7-4afd-a9b1-2ca7f585d146 · outbound

This paper cites MiniCPM-V: A GPT-4V Level MLLM on Your Phone.

MiniCPM4: Ultra-Efficient LLMs on End Devices MiniCPM-V: A GPT-4V Level MLLM on Your Phone

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-07T05:31:22.338736Z

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Observation 0505c5db-18fa-4fd8-bd05-48cf231bc2a9 · outbound

This paper cites DAPO: An Open-Source LLM Reinforcement Learning System at Scale.

MiniCPM4: Ultra-Efficient LLMs on End Devices DAPO: An Open-Source LLM Reinforcement Learning System at Scale

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-07T05:31:22.420798Z

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Observation bbdcb812-5d03-49c4-9731-a04b55e55884 · outbound

This paper cites Spargeattn: Accurate sparse attention accelerating any model inference.

MiniCPM4: Ultra-Efficient LLMs on End Devices Spargeattn: Accurate sparse attention accelerating any model inference

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-07T05:31:22.540224Z

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Observation 78d59c46-a7da-4a31-b944-61ec05423ec6 · outbound

This paper cites FR-Spec: Accelerating Large-Vocabulary Language Models via Frequency-Ranked Speculative Sampling.

MiniCPM4: Ultra-Efficient LLMs on End Devices FR-Spec: Accelerating Large-Vocabulary Language Models via Frequency-Ranked Speculative Sampling

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-07T05:31:22.607755Z

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Observation 353c05fe-6a01-47f1-939b-d544b070a447 · outbound

This paper cites OpenCodeInterpreter: Integrating Code Generation with Execution and Refinement.

MiniCPM4: Ultra-Efficient LLMs on End Devices OpenCodeInterpreter: Integrating Code Generation with Execution and Refinement

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-07T05:31:22.729139Z

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Observation b3b0c243-0bbb-408e-9f43-da719fad6c0c · outbound

This paper cites BitNet: Scaling 1-bit Transformers for Large Language Models.

MiniCPM4: Ultra-Efficient LLMs on End Devices BitNet: Scaling 1-bit Transformers for Large Language Models

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-07T05:31:21.594653Z

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Observation 1e33e265-a74b-4137-ac30-ae59d1d5a11b · outbound

This paper cites Assisting in Writing Wikipedia-like Articles From Scratch with Large Language Models.

MiniCPM4: Ultra-Efficient LLMs on End Devices Assisting in Writing Wikipedia-like Articles From Scratch with Large Language Models

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-07T05:31:21.341625Z

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Observation 819c634a-5d4f-4012-adc8-e9b00a951542 · outbound

This paper cites LongAlign: A recipe for long context alignment of large language models.

MiniCPM4: Ultra-Efficient LLMs on End Devices LongAlign: A recipe for long context alignment of large language models

Reference 2021

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:31:23.553958Z

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation d2b7c941-d788-42d1-84f8-3af3700fd17f · outbound

This paper cites DeepSeek-V3 Technical Report.

MiniCPM4: Ultra-Efficient LLMs on End Devices DeepSeek-V3 Technical Report

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-07T05:31:19.647000Z

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Observation 9e76ad3f-fb4b-4c98-8b2f-5dfebf2fce12 · outbound

This paper cites Evaluating Large Language Models Trained on Code.

MiniCPM4: Ultra-Efficient LLMs on End Devices Evaluating Large Language Models Trained on Code

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-07T05:31:19.401639Z

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Observation 3b69b5e1-438c-4caf-a265-18caef954291 · outbound

This paper cites Program Synthesis with Large Language Models.

MiniCPM4: Ultra-Efficient LLMs on End Devices Program Synthesis with Large Language Models

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-07T05:31:18.957206Z

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Observation 7d34dc5c-336d-4bd7-a94e-4299a4482785 · outbound

This paper cites The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits.

MiniCPM4: Ultra-Efficient LLMs on End Devices The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-07T05:31:20.875138Z

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Pith citing papers

Observation ccb5f421-5942-4eeb-825f-3faa5fba3ba1 · inbound

The Ratchet Effect in Silico: How Interaction Drives Cumulative Intelligence in Large Language Models cites this paper.

The Ratchet Effect in Silico: How Interaction Drives Cumulative Intelligence in Large Language Models MiniCPM4: Ultra-Efficient LLMs on End Devices

Reference 43

Resolution: verified exact; arxiv_id, observed 2026-05-19T02:41:59.963326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 0f6ef702-e5f0-46a6-ab2c-e20bcfae6475 · inbound

iFairy: the First 2-bit Complex LLM with All Parameters in $\{\pm1, \pm i\}$ cites this paper.

iFairy: the First 2-bit Complex LLM with All Parameters in $\{\pm1, \pm i\}$ MiniCPM4: Ultra-Efficient LLMs on End Devices

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-05T23:24:00.992793Z

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Observation f3945627-6699-4f27-bd4c-056b30d131c4 · inbound

Psyche-R1: Towards Reliable Psychological LLMs through Unified Empathy, Expertise, and Reasoning cites this paper.

Psyche-R1: Towards Reliable Psychological LLMs through Unified Empathy, Expertise, and Reasoning MiniCPM4: Ultra-Efficient LLMs on End Devices

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-05T20:18:44.494542Z

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Observation 04169612-8244-4ffe-a3de-011172babba4 · inbound

Kimi Linear: An Expressive, Efficient Attention Architecture cites this paper.

Kimi Linear: An Expressive, Efficient Attention Architecture MiniCPM4: Ultra-Efficient LLMs on End Devices

Reference 99

Resolution: verified exact; arxiv_id, observed 2026-05-13T23:49:10.845126Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 5de5ce09-d461-4f75-950b-715e05a0634d · inbound

Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework cites this paper.

Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework MiniCPM4: Ultra-Efficient LLMs on End Devices

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-03T11:28:10.091739Z

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Observation d296e113-1cab-4c55-a305-ec7e89177e4c · inbound

Stem: Rethinking Causal Information Flow in Sparse Attention cites this paper.

Stem: Rethinking Causal Information Flow in Sparse Attention MiniCPM4: Ultra-Efficient LLMs on End Devices

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-03T02:39:29.867104Z

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Observation 1951c0dd-a718-4ab9-9611-d085030f0e29 · inbound

CodePercept: Code-Grounded Visual STEM Perception for MLLMs cites this paper.

CodePercept: Code-Grounded Visual STEM Perception for MLLMs MiniCPM4: Ultra-Efficient LLMs on End Devices

Reference 43

Resolution: unresolved; no resolver link, observed 2026-07-14T23:22:13.847876Z

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Observation 6d3277bd-8b42-4b8f-921f-5ad96110886f · inbound

TSHA: A Benchmark for Visual Language Models in Trustworthy Safety Hazard Assessment Scenarios cites this paper.

TSHA: A Benchmark for Visual Language Models in Trustworthy Safety Hazard Assessment Scenarios MiniCPM4: Ultra-Efficient LLMs on End Devices

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-02T17:05:14.387747Z

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Observation 4cbf2385-dbf6-4e96-a56e-189d90d64de7 · inbound

Too Nice to Tell the Truth: Quantifying Agreeableness-Driven Sycophancy in Role-Playing Language Models cites this paper.

Too Nice to Tell the Truth: Quantifying Agreeableness-Driven Sycophancy in Role-Playing Language Models MiniCPM4: Ultra-Efficient LLMs on End Devices

Reference 46

Resolution: verified exact; arxiv_id, observed 2026-05-11T09:21:00.956236Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 09359c09-4f30-4b56-809f-eea5b947814a · inbound

LongAct: Harnessing Intrinsic Activation Patterns for Long-Context Reinforcement Learning cites this paper.

LongAct: Harnessing Intrinsic Activation Patterns for Long-Context Reinforcement Learning MiniCPM4: Ultra-Efficient LLMs on End Devices

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-05-10T11:20:10.528750Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 652dda42-44c6-4334-a8f2-4e992830c7d0 · inbound

MiniCPM-o 4.5: Towards Real-Time Full-Duplex Omni-Modal Interaction cites this paper.

MiniCPM-o 4.5: Towards Real-Time Full-Duplex Omni-Modal Interaction MiniCPM4: Ultra-Efficient LLMs on End Devices

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-05-12T09:46:26.470172Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 75b75a62-cd32-43d0-b218-ff70c95f5214 · inbound

JaiTTS: A Thai Voice Cloning Model cites this paper.

JaiTTS: A Thai Voice Cloning Model MiniCPM4: Ultra-Efficient LLMs on End Devices

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-12T10:21:28.812132Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation de1f61a3-5a88-45e6-a8d0-b398b8627147 · inbound

JaiTTS: A Thai Voice Cloning Model cites this paper.

JaiTTS: A Thai Voice Cloning Model MiniCPM4: Ultra-Efficient LLMs on End Devices

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-11T22:16:26.324947Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 758d74a0-a83a-4139-8020-d652c55ebbf7 · inbound

TIDE-Bench: Task-Aware and Diagnostic Evaluation of Tool-Integrated Reasoning cites this paper.

TIDE-Bench: Task-Aware and Diagnostic Evaluation of Tool-Integrated Reasoning MiniCPM4: Ultra-Efficient LLMs on End Devices

Reference 35

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T02:51:18.060399Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation a219ed25-0cbd-4564-a9bb-26d52baf25a1 · inbound

DashAttention: Differentiable and Adaptive Sparse Hierarchical Attention cites this paper.

DashAttention: Differentiable and Adaptive Sparse Hierarchical Attention MiniCPM4: Ultra-Efficient LLMs on End Devices

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-20T10:53:13.541414Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation fb1e67fa-e45e-4fff-a9db-5a4576d4bbb3 · inbound

SparDA: Sparse Decoupled Attention for Efficient Long-Context LLM Inference cites this paper.

SparDA: Sparse Decoupled Attention for Efficient Long-Context LLM Inference MiniCPM4: Ultra-Efficient LLMs on End Devices

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-07-02T07:56:47.849374Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation a256a5ad-8de6-4833-8469-d62c9ea95599 · inbound

ReverseEOL: Improving Training-free Text Embeddings via Text Reversal in Decoder-only LLMs cites this paper.

ReverseEOL: Improving Training-free Text Embeddings via Text Reversal in Decoder-only LLMs MiniCPM4: Ultra-Efficient LLMs on End Devices

Reference 35

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T12:56:57.155569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 03272e28-1165-466c-b3a7-413a108afd97 · inbound

VoxCPM2 Technical Report cites this paper.

VoxCPM2 Technical Report MiniCPM4: Ultra-Efficient LLMs on End Devices

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-07-02T19:47:19.781597Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 34e4f3d1-0497-4001-9472-eb44270d0f39 · inbound

FreyaTTS: A Compact Tokenizer-Free Flow-Matching Transformer for Turkish-First Speech Synthesis cites this paper.

FreyaTTS: A Compact Tokenizer-Free Flow-Matching Transformer for Turkish-First Speech Synthesis MiniCPM4: Ultra-Efficient LLMs on End Devices

Reference 8

Resolution: unresolved; no resolver link, observed 2026-07-13T02:22:47.820537Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b04f33d3-fe87-4968-8929-4951f9998c8b · inbound

FreyaTTS: A Compact Tokenizer-Free Flow-Matching Transformer for Turkish-First Speech Synthesis cites this paper.

FreyaTTS: A Compact Tokenizer-Free Flow-Matching Transformer for Turkish-First Speech Synthesis MiniCPM4: Ultra-Efficient LLMs on End Devices

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-02T07:39:23.532135Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cf04b8b5-2777-4aac-bf33-7f6689985846 · inbound

Athena-Brain Technical Report: An Efficient Robot Brain for General Intelligence and Embodied Interaction cites this paper.

Athena-Brain Technical Report: An Efficient Robot Brain for General Intelligence and Embodied Interaction MiniCPM4: Ultra-Efficient LLMs on End Devices

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-01T13:53:45.274396Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1ce58eaf-ac3a-466a-b5f7-694ebba9ac76 · inbound

CoSA: Accelerating Long-Context Inference via Proxy-Kernel Co-Designed Sparse Attention cites this paper.

CoSA: Accelerating Long-Context Inference via Proxy-Kernel Co-Designed Sparse Attention MiniCPM4: Ultra-Efficient LLMs on End Devices

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-01T02:55:49.147989Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4dd1bdf4-d1db-4729-827d-6cbcdcd68a65 · inbound

$\Sigma$-Mem: An Online Reliability Memory for LLM-based Multi-Agent Systems cites this paper.

$\Sigma$-Mem: An Online Reliability Memory for LLM-based Multi-Agent Systems MiniCPM4: Ultra-Efficient LLMs on End Devices

Reference 30

Resolution: unresolved; no resolver link, observed 2026-07-31T22:14:36.638353Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fb09b244-1f74-4478-98f3-0d7e36c6118d · inbound

AgenticASR: Refining Speech Recognition in Real-World Scenarios via an Agentic Approach cites this paper.

AgenticASR: Refining Speech Recognition in Real-World Scenarios via an Agentic Approach MiniCPM4: Ultra-Efficient LLMs on End Devices

Reference 11

Resolution: unresolved; no resolver link, observed 2026-07-31T15:38:32.889220Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.