Paper Citation Record · LEDGER

Echo-Infinity: Learning Evolving Memory for Real-Time Infinite Video Generation

As of 11 August 2026, this Paper Citation Record lists 51 of 51 outbound references and 2 inbound Pith citation observations for arXiv:2606.04527.

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

pith.paper-citation-record.v1
2606.04527 v1

Coverage vector

measured 51 of 51 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-28T03:27:02.232039Z

measured 53 of 53 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T03:17:51.809080Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

51 of 51 outbound references displayed

verified exact27
verified fuzzy0
unresolved19
parse uncertain0
malformed identifier1
metadata mismatch4

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d17c79a7-fee9-4df7-9fe4-3789e907c03d · outbound

This paper cites ReCamMaster: Camera-controlled generative rendering from a single video.

Echo-Infinity: Learning Evolving Memory for Real-Time Infinite Video Generation ReCamMaster: Camera-controlled generative rendering from a single video

Reference 1

Resolution: unresolved; no resolver link, observed 2026-06-28T03:27:02.232039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 972b6bdf-ae65-420c-8194-32422060ffce · outbound

This paper cites Video-as-prompt: Uni- fied semantic control for video generation.

Echo-Infinity: Learning Evolving Memory for Real-Time Infinite Video Generation Video-as-prompt: Uni- fied semantic control for video generation

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-07-02T11:36:54.858189Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation d2f3c2a6-8884-4105-a41b-98e7d1c86ccb · outbound

This paper cites MotionCraft: Crafting whole-body motion with plug-and-play multimodal controls.

Echo-Infinity: Learning Evolving Memory for Real-Time Infinite Video Generation MotionCraft: Crafting whole-body motion with plug-and-play multimodal controls

Reference 3

Resolution: unresolved; no resolver link, observed 2026-06-28T03:27:02.232039Z

Source-reported events for the cited work

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Observation afde6122-dd98-4c04-a2a4-6547aff63713 · outbound

This paper cites VideoPainter: Any-length video inpainting and editing with plug-and-play context control.

Echo-Infinity: Learning Evolving Memory for Real-Time Infinite Video Generation VideoPainter: Any-length video inpainting and editing with plug-and-play context control

Reference 4

Resolution: unresolved; no resolver link, observed 2026-06-28T03:27:02.232039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 32997bc6-2444-4f06-86e5-538304db2125 · outbound

This paper cites Medusa: Simple LLM Inference Acceleration Framework with Multiple Decoding Heads.

Echo-Infinity: Learning Evolving Memory for Real-Time Infinite Video Generation Medusa: Simple LLM Inference Acceleration Framework with Multiple Decoding Heads

Reference 5

Resolution: verified exact; local_arxiv, observed 2026-07-02T11:36:54.891634Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation a5c787ec-a0bb-4020-b161-bff3cbb3a53a · outbound

This paper cites Diffusion forcing: Next-token prediction meets full-sequence diffusion.

Echo-Infinity: Learning Evolving Memory for Real-Time Infinite Video Generation Diffusion forcing: Next-token prediction meets full-sequence diffusion

Reference 6

Resolution: unresolved; no resolver link, observed 2026-06-28T03:27:02.232039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6a8ab858-e553-48b8-ad43-79457a973d11 · outbound

This paper cites SkyReels-V2: Infinite-length Film Generative Model.

Echo-Infinity: Learning Evolving Memory for Real-Time Infinite Video Generation SkyReels-V2: Infinite-length Film Generative Model

Reference 7

Resolution: verified exact; local_arxiv, observed 2026-07-02T11:36:54.844827Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation bd01307e-d68f-4854-9b50-0449d8b14007 · outbound

This paper cites Grounded Forcing: Bridging Time-Independent Semantics and Proximal Dynamics in Autoregressive Video Synthesis.

Echo-Infinity: Learning Evolving Memory for Real-Time Infinite Video Generation Grounded Forcing: Bridging Time-Independent Semantics and Proximal Dynamics in Autoregressive Video Synthesis

Reference 8

Resolution: verified exact; local_arxiv, observed 2026-07-02T11:36:54.845749Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation e86c3629-f4e1-4993-bac4-9ff7b7460063 · outbound

This paper cites Context forcing: Consistent autoregressive video generation with long context.

Echo-Infinity: Learning Evolving Memory for Real-Time Infinite Video Generation Context forcing: Consistent autoregressive video generation with long context

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-07-02T11:36:54.886742Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 48a14b3b-f87c-4777-af9f-2bbf270f91bd · outbound

This paper cites Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities.

Echo-Infinity: Learning Evolving Memory for Real-Time Infinite Video Generation Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities

Reference 10

Resolution: verified exact; local_arxiv, observed 2026-07-02T11:36:54.888570Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 11c16ed4-7c81-4bc1-a00a-8b9df73c4d23 · outbound

This paper cites Self-Forcing++: Towards Minute-Scale High-Quality Video Generation.

Echo-Infinity: Learning Evolving Memory for Real-Time Infinite Video Generation Self-Forcing++: Towards Minute-Scale High-Quality Video Generation

Reference 11

Resolution: verified exact; local_arxiv, observed 2026-07-02T11:36:54.885655Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 4a955319-5665-4808-9d7b-2ea813439bed · outbound

This paper cites Autoregressive Video Generation without Vector Quantization.

Echo-Infinity: Learning Evolving Memory for Real-Time Infinite Video Generation Autoregressive Video Generation without Vector Quantization

Reference 12

Resolution: verified exact; local_arxiv, observed 2026-07-02T11:36:54.891991Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation dba47373-d05c-4d16-97b5-c77f15994d76 · outbound

This paper cites Cognitive neuroscience of human memory.Annual review of psychology, 49(1):87–115, 1998.

Echo-Infinity: Learning Evolving Memory for Real-Time Infinite Video Generation Cognitive neuroscience of human memory.Annual review of psychology, 49(1):87–115, 1998

Reference 13

Resolution: unresolved; no resolver link, observed 2026-06-28T03:27:02.232039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1a27d215-70e9-4a2f-a6d3-b77b87cfc273 · outbound

This paper cites LTX-Video: Realtime Video Latent Diffusion.

Echo-Infinity: Learning Evolving Memory for Real-Time Infinite Video Generation LTX-Video: Realtime Video Latent Diffusion

Reference 14

Resolution: verified exact; local_arxiv, observed 2026-07-02T11:36:54.915069Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 010b581a-f64a-40e0-9129-6498e436a55c · outbound

This paper cites LTX-2: Efficient Joint Audio-Visual Foundation Model.

Echo-Infinity: Learning Evolving Memory for Real-Time Infinite Video Generation LTX-2: Efficient Joint Audio-Visual Foundation Model

Reference 15

Resolution: verified exact; local_arxiv, observed 2026-07-02T11:36:54.909995Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 13574aba-bd33-44e3-90a3-394247e6ab70 · outbound

This paper cites CLIPScore: A reference-free evaluation metric for image captioning.

Echo-Infinity: Learning Evolving Memory for Real-Time Infinite Video Generation CLIPScore: A reference-free evaluation metric for image captioning

Reference 16

Resolution: unresolved; no resolver link, observed 2026-06-28T03:27:02.232039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 44363b92-7c61-434f-8481-26e596a772c2 · outbound

This paper cites Denoising diffusion probabilistic models.

Echo-Infinity: Learning Evolving Memory for Real-Time Infinite Video Generation Denoising diffusion probabilistic models

Reference 17

Resolution: unresolved; no resolver link, observed 2026-06-28T03:27:02.232039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b537775f-25ab-42a8-9b03-fb06ba53979b · outbound

This paper cites Self forcing: Bridging the train-test gap in autoregressive video diffusion.

Echo-Infinity: Learning Evolving Memory for Real-Time Infinite Video Generation Self forcing: Bridging the train-test gap in autoregressive video diffusion

Reference 18

Resolution: unresolved; no resolver link, observed 2026-06-28T03:27:02.232039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f2071e85-4eea-4dc1-a4f9-96aa7aaa2e4f · outbound

This paper cites VBench: Comprehensive benchmark suite for video generative models.

Echo-Infinity: Learning Evolving Memory for Real-Time Infinite Video Generation VBench: Comprehensive benchmark suite for video generative models

Reference 19

Resolution: unresolved; no resolver link, observed 2026-06-28T03:27:02.232039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6702902f-45ad-4903-9446-a70ac26a0b56 · outbound

This paper cites VBench++: Comprehensive and versatile benchmark suite for video generative models.

Echo-Infinity: Learning Evolving Memory for Real-Time Infinite Video Generation VBench++: Comprehensive and versatile benchmark suite for video generative models

Reference 20

Resolution: unresolved; no resolver link, observed 2026-06-28T03:27:02.232039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 836a4b93-4fe1-497c-a4f3-6a5e8f703741 · outbound

This paper cites Memflow: Flowing adaptive memory for consistent and efficient long video narratives.

Echo-Infinity: Learning Evolving Memory for Real-Time Infinite Video Generation Memflow: Flowing adaptive memory for consistent and efficient long video narratives

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-07-02T11:36:54.919982Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 292b576f-c86f-4d63-973f-845e5ad3adf6 · outbound

This paper cites LoViC: Efficient Long Video Generation with Context Compression.

Echo-Infinity: Learning Evolving Memory for Real-Time Infinite Video Generation LoViC: Efficient Long Video Generation with Context Compression

Reference 22

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T11:36:54.922789Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation acaaccce-21c0-4c48-a0a5-834ad361a03d · outbound

This paper cites Pyramidal flow matching for efficient video generative modeling.arXiv preprint arXiv:2410.05954.

Echo-Infinity: Learning Evolving Memory for Real-Time Infinite Video Generation Pyramidal flow matching for efficient video generative modeling.arXiv preprint arXiv:2410.05954

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-07-02T11:36:54.869647Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 5872419b-057c-4d25-8abc-03e7bb7ea7da · outbound

This paper cites Elucidating the design space of diffusion-based generative models.

Echo-Infinity: Learning Evolving Memory for Real-Time Infinite Video Generation Elucidating the design space of diffusion-based generative models

Reference 24

Resolution: unresolved; no resolver link, observed 2026-06-28T03:27:02.232039Z

Source-reported events for the cited work

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Observation 16522fc7-15d1-4f75-9f18-847f095ee4c3 · outbound

This paper cites Memrope: Training-free infinite video generation via evolving memory tokens.

Echo-Infinity: Learning Evolving Memory for Real-Time Infinite Video Generation Memrope: Training-free infinite video generation via evolving memory tokens

Reference 25

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T11:36:54.877285Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 6c29ca4f-450a-4439-8347-2b16c6bf9d15 · outbound

This paper cites HunyuanVideo: A Systematic Framework For Large Video Generative Models.

Echo-Infinity: Learning Evolving Memory for Real-Time Infinite Video Generation HunyuanVideo: A Systematic Framework For Large Video Generative Models

Reference 26

Resolution: verified exact; local_arxiv, observed 2026-07-02T11:36:54.872089Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation f4d07788-73e5-4592-8aef-d4aa22592247 · outbound

This paper cites Rolling forcing: Autoregressive long video diffusion in real time.

Echo-Infinity: Learning Evolving Memory for Real-Time Infinite Video Generation Rolling forcing: Autoregressive long video diffusion in real time

Reference 27

Resolution: unresolved; no resolver link, observed 2026-06-28T03:27:02.232039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation af78705c-fc88-468b-b30c-bc6399a182b1 · outbound

This paper cites PackForcing: Short video training suffices for long video sampling and long context inference.

Echo-Infinity: Learning Evolving Memory for Real-Time Infinite Video Generation PackForcing: Short video training suffices for long video sampling and long context inference

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-07-02T11:36:54.905422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 5979b444-9607-4a83-b891-e4303e4aa3ac · outbound

This paper cites Scalable diffusion models with transformers.

Echo-Infinity: Learning Evolving Memory for Real-Time Infinite Video Generation Scalable diffusion models with transformers

Reference 29

Resolution: unresolved; no resolver link, observed 2026-06-28T03:27:02.232039Z

Source-reported events for the cited work

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Observation c277c601-7350-44fc-a618-ea721fa55d6f · outbound

This paper cites Movie Gen: A Cast of Media Foundation Models.

Echo-Infinity: Learning Evolving Memory for Real-Time Infinite Video Generation Movie Gen: A Cast of Media Foundation Models

Reference 30

Resolution: verified exact; local_arxiv, observed 2026-07-02T11:36:54.866052Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation d652d2c1-98f4-4195-ad99-9b6e6b38eeea · outbound

This paper cites RoFormer: Enhanced transformer with rotary position embedding.Neurocomputing, 568:127063, 2024.

Echo-Infinity: Learning Evolving Memory for Real-Time Infinite Video Generation RoFormer: Enhanced transformer with rotary position embedding.Neurocomputing, 568:127063, 2024

Reference 31

Resolution: unresolved; no resolver link, observed 2026-06-28T03:27:02.232039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 378ba482-23de-4a42-b033-2db4354acbeb · outbound

This paper cites MAGI-1: Autoregressive Video Generation at Scale.

Echo-Infinity: Learning Evolving Memory for Real-Time Infinite Video Generation MAGI-1: Autoregressive Video Generation at Scale

Reference 32

Resolution: verified exact; local_arxiv, observed 2026-07-02T11:36:54.906133Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 8e28be7d-85f4-4278-9985-979ecd7e19a3 · outbound

This paper cites Wan: Open and Advanced Large-Scale Video Generative Models.

Echo-Infinity: Learning Evolving Memory for Real-Time Infinite Video Generation Wan: Open and Advanced Large-Scale Video Generative Models

Reference 33

Resolution: verified exact; local_arxiv, observed 2026-07-02T11:36:54.867088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 4a316850-9baa-4979-8a93-ffc1157ae9a0 · outbound

This paper cites VidProM: A million-scale real prompt-gallery dataset for text-to-video diffusion models.

Echo-Infinity: Learning Evolving Memory for Real-Time Infinite Video Generation VidProM: A million-scale real prompt-gallery dataset for text-to-video diffusion models

Reference 34

Resolution: unresolved; no resolver link, observed 2026-06-28T03:27:02.232039Z

Source-reported events for the cited work

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Observation 7245e1b2-e3d5-4ed6-9b8e-01d3067c5b8d · outbound

This paper cites Efficient Streaming Language Models with Attention Sinks.

Echo-Infinity: Learning Evolving Memory for Real-Time Infinite Video Generation Efficient Streaming Language Models with Attention Sinks

Reference 35

Resolution: verified exact; local_arxiv, observed 2026-07-02T11:36:54.899937Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation fbcf92e3-ce8d-4e96-91e3-f8b2f2a53a55 · outbound

This paper cites Qwen3 Technical Report.

Echo-Infinity: Learning Evolving Memory for Real-Time Infinite Video Generation Qwen3 Technical Report

Reference 36

Resolution: verified exact; local_arxiv, observed 2026-07-02T11:36:54.850839Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 5ec49b60-4884-4fde-83a4-6d53ea3c04c5 · outbound

This paper cites LongLive: Real-time interactive long video generation.

Echo-Infinity: Learning Evolving Memory for Real-Time Infinite Video Generation LongLive: Real-time interactive long video generation

Reference 37

Resolution: unresolved; no resolver link, observed 2026-06-28T03:27:02.232039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1653cb8b-f780-427f-8d4a-ef23430e0318 · outbound

This paper cites Anchor forcing: Anchor memory and tri-region rope for interactive streaming video diffusion.

Echo-Infinity: Learning Evolving Memory for Real-Time Infinite Video Generation Anchor forcing: Anchor memory and tri-region rope for interactive streaming video diffusion

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-07-02T11:36:54.903785Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation ce1c3b57-8f94-4a02-8063-ca9495a6b731 · outbound

This paper cites CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer.

Echo-Infinity: Learning Evolving Memory for Real-Time Infinite Video Generation CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer

Reference 39

Resolution: verified exact; local_arxiv, observed 2026-07-02T11:36:54.864605Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 8cb5b454-b2a9-4d6d-a7d1-640adc07596c · outbound

This paper cites Infinity-RoPE: Action-controllable infinite video generation emerges from autoregressive self- rollout.

Echo-Infinity: Learning Evolving Memory for Real-Time Infinite Video Generation Infinity-RoPE: Action-controllable infinite video generation emerges from autoregressive self- rollout

Reference 40

Resolution: verified exact; arxiv_id, observed 2026-07-02T11:36:54.847378Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 885850a3-cee7-4277-8a91-d4370f98bb34 · outbound

This paper cites H., Nam, J., Yoon, H., and Kim, S.

Echo-Infinity: Learning Evolving Memory for Real-Time Infinite Video Generation H., Nam, J., Yoon, H., and Kim, S

Reference 41

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T11:36:54.920283Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 703c2dd1-1b45-4a9e-8acb-cf22b48c5741 · outbound

This paper cites Improved distribution matching distillation for fast image synthesis.Advancesin neural information processing systems, 37:47455–47487, 2024.

Echo-Infinity: Learning Evolving Memory for Real-Time Infinite Video Generation Improved distribution matching distillation for fast image synthesis.Advancesin neural information processing systems, 37:47455–47487, 2024

Reference 42

Resolution: unresolved; no resolver link, observed 2026-06-28T03:27:02.232039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4f0b76b2-1e1f-4d6e-97eb-2796bfbd97f2 · outbound

This paper cites One-step diffusion with distribution matching distillation.

Echo-Infinity: Learning Evolving Memory for Real-Time Infinite Video Generation One-step diffusion with distribution matching distillation

Reference 43

Resolution: unresolved; no resolver link, observed 2026-06-28T03:27:02.232039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3e666fe7-f4d6-4d6d-b176-15a32b363fc7 · outbound

This paper cites From slow bidirectional to fast autoregressive video diffusion models.

Echo-Infinity: Learning Evolving Memory for Real-Time Infinite Video Generation From slow bidirectional to fast autoregressive video diffusion models

Reference 44

Resolution: unresolved; no resolver link, observed 2026-06-28T03:27:02.232039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 26cc9643-cfe5-4d1c-b26f-071288004b1e · outbound

This paper cites Context as memory: Scene-consistent interactive long video generation with memory retrieval.

Echo-Infinity: Learning Evolving Memory for Real-Time Infinite Video Generation Context as memory: Scene-consistent interactive long video generation with memory retrieval

Reference 45

Resolution: verified exact; arxiv_id, observed 2026-07-02T11:36:54.925049Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation d007d82f-23d4-4c44-8642-70c68ab6c700 · outbound

This paper cites Lvmin Zhang, Shengqu Cai, Muyang Li, Chong Zeng, Beijia Lu, Anyi Rao, Song Han, Gordon Wetzstein, and Maneesh Agrawala.

Echo-Infinity: Learning Evolving Memory for Real-Time Infinite Video Generation Lvmin Zhang, Shengqu Cai, Muyang Li, Chong Zeng, Beijia Lu, Anyi Rao, Song Han, Gordon Wetzstein, and Maneesh Agrawala

Reference 46

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T11:36:54.914943Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 43d18ce6-e4a1-4ac7-93c1-2777db18e6f7 · outbound

This paper cites TinyHistory: Lightweight Video History Embeddings via Two-Stage Context Learning.

Echo-Infinity: Learning Evolving Memory for Real-Time Infinite Video Generation TinyHistory: Lightweight Video History Embeddings via Two-Stage Context Learning

Reference 47

Resolution: verified exact; local_arxiv, observed 2026-07-02T11:36:54.917323Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation ddda9d86-ebf1-4c6d-a796-c97e627fd7c3 · outbound

This paper cites Relax forcing: Relaxed kv-memory for consistent long video generation.

Echo-Infinity: Learning Evolving Memory for Real-Time Infinite Video Generation Relax forcing: Relaxed kv-memory for consistent long video generation

Reference 48

Resolution: verified exact; arxiv_id, observed 2026-07-02T11:36:54.909607Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation de71d412-7938-449a-8926-ed49498bfff1 · outbound

This paper cites VBench-2.0: Advancing Video Generation Benchmark Suite for Intrinsic Faithfulness.

Echo-Infinity: Learning Evolving Memory for Real-Time Infinite Video Generation VBench-2.0: Advancing Video Generation Benchmark Suite for Intrinsic Faithfulness

Reference 49

Resolution: verified exact; local_arxiv, observed 2026-07-02T11:36:54.897618Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation ba95ed35-faf6-4b84-abc9-58667ecd18e0 · outbound

This paper cites Causal Forcing: Autoregressive Diffusion Distillation Done Right for High-Quality Real-Time Interactive Video Generation.

Echo-Infinity: Learning Evolving Memory for Real-Time Infinite Video Generation Causal Forcing: Autoregressive Diffusion Distillation Done Right for High-Quality Real-Time Interactive Video Generation

Reference 50

Resolution: verified exact; local_arxiv, observed 2026-07-02T11:36:54.922356Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation c1f82816-838e-4dcc-a757-c5a5296b8b99 · outbound

This paper cites Memorize-and-generate: Towards long-term consistency in real-time video generation.arXiv preprint arXiv:2512.18741, 2025.

Echo-Infinity: Learning Evolving Memory for Real-Time Infinite Video Generation Memorize-and-generate: Towards long-term consistency in real-time video generation.arXiv preprint arXiv:2512.18741, 2025

Reference 51

Resolution: malformed identifier; arxiv_id, observed 2026-07-02T11:36:54.917770Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Pith citing papers

Observation c8b3cb79-70e1-4887-aca0-2c8dc3a06e64 · inbound

Visko Orbis 1.0: A Live Model for Real-Time Interactive Long Video Generation cites this paper.

Visko Orbis 1.0: A Live Model for Real-Time Interactive Long Video Generation Echo-Infinity: Learning Evolving Memory for Real-Time Infinite Video Generation

Reference 23

Resolution: unresolved; no resolver link, observed 2026-07-30T23:47:57.746362Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c544ed62-b5a9-4c6b-be9d-40e04beb7e2a · inbound

FlexComposer: Unified Video Compositing from Images to Dynamic Footage with Flexible Trajectory Control cites this paper.

FlexComposer: Unified Video Compositing from Images to Dynamic Footage with Flexible Trajectory Control Echo-Infinity: Learning Evolving Memory for Real-Time Infinite Video Generation

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-03T03:17:51.809080Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.