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Paper Citation Record · LEDGER

RoboEgo System Card: An Omnimodal Model with Native Full Duplexity

As of 15 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 1 inbound Pith citation observation for arXiv:2506.01934.

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

pith.paper-citation-record.v1
2506.01934 v1

Coverage vector

measured 43 of 43 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:37:29.595125Z

measured 44 of 44 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-13T20:56:19.815569Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-13T20:58:15.857687Z

Reference resolution

43 of 43 outbound references displayed

  • verified exact0
  • verified fuzzy6
  • unresolved36
  • parse uncertain1
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 50e9a5e4-7940-48e1-b94c-5d6e7d18970a · outbound

This paper cites Pixtral 12B.

RoboEgo System Card: An Omnimodal Model with Native Full Duplexity Pixtral 12B

Reference 1

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:37:29.357915Z digest=sha256:05c36bfc5ec1392215acfae7347ee751c22a179ffe3d02440191801f02da01ec

Observation bd8141c1-7133-4193-a7d0-aac7c6faba2a · outbound

This paper cites Seed-TTS: A Family of High-Quality Versatile Speech Generation Models.

RoboEgo System Card: An Omnimodal Model with Native Full Duplexity Seed-TTS: A Family of High-Quality Versatile Speech Generation Models

Reference 2

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source=pdf_text observed=2026-08-07T11:37:29.364137Z digest=sha256:bc61a398946bc6e70eb1563409f13f5a17c5c489164948428a7fa6e0f5efbb07

Observation 968f1d6c-5107-4af5-a99b-a857502ce664 · outbound

This paper cites Qwen2.5-VL Technical Report.

RoboEgo System Card: An Omnimodal Model with Native Full Duplexity Qwen2.5-VL Technical Report

Reference 3

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source=pdf_text observed=2026-08-07T11:37:29.369919Z digest=sha256:d809b3954b6f38235dd49be1936004622a7ab49f0dd390a6d10bb53fd7297763

Observation ca96cf19-8ecb-4f21-bc28-8662016bbdbb · outbound

This paper cites Audiolm: a language modeling approach to audio generation.

RoboEgo System Card: An Omnimodal Model with Native Full Duplexity Audiolm: a language modeling approach to audio generation

Reference 4

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:37:29.375474Z digest=sha256:12f6bb6b7e8182658712e96a206a427dd3a6b8ee56c08a97be2c9c24b6882de8

Observation db38e9aa-e405-42f6-8626-822994ef0f0f · outbound

This paper cites RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control.

RoboEgo System Card: An Omnimodal Model with Native Full Duplexity RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control

Reference 5

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source=pdf_text observed=2026-08-07T11:37:29.381125Z digest=sha256:10514479cbeddc8612639ea8963820e706c61ff3d52dbe6ab024d31cce682a3a

Observation 52535a31-8dc6-4b82-9de6-c4ab3c330995 · outbound

This paper cites Sparks of Artificial General Intelligence: Early experiments with GPT-4.

RoboEgo System Card: An Omnimodal Model with Native Full Duplexity Sparks of Artificial General Intelligence: Early experiments with GPT-4

Reference 6

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source=pdf_text observed=2026-08-07T11:37:29.387948Z digest=sha256:c718052f498dd529a8de8ccbb95b3cbd88663ee2ae8f14f7243312a2c9bb5ab7

Observation 9a44d9e3-7d53-4063-97cf-0cb0c20ac3a0 · outbound

This paper cites Are We on the Right Way for Evaluating Large Vision-Language Models?.

RoboEgo System Card: An Omnimodal Model with Native Full Duplexity Are We on the Right Way for Evaluating Large Vision-Language Models?

Reference 7

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source=pdf_text observed=2026-08-07T11:37:29.394082Z digest=sha256:4b7df8352e2039430fbf1fb6aa4b0705beb031abf5556ee05c34d90f2aec1885

Observation b35f5ec1-0f86-42ca-a4e5-1425f62ae257 · outbound

This paper cites MinMo: A Multimodal Large Language Model for Seamless Voice Interaction.

RoboEgo System Card: An Omnimodal Model with Native Full Duplexity MinMo: A Multimodal Large Language Model for Seamless Voice Interaction

Reference 8

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source=pdf_text observed=2026-08-07T11:37:29.400192Z digest=sha256:617a1978ccad65250e71b4ecd67f307e08c0aaa254768c6e6287c61875e70a2c

Observation 35b9b5af-8439-4a37-ac22-a55620a8a29c · outbound

This paper cites Qwen-Audio: Advancing Universal Audio Understanding via Unified Large-Scale Audio-Language Models.

RoboEgo System Card: An Omnimodal Model with Native Full Duplexity Qwen-Audio: Advancing Universal Audio Understanding via Unified Large-Scale Audio-Language Models

Reference 9

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:37:29.405699Z digest=sha256:842b52c2925fdce53b347a787819924a4fdd86e8bd21f9b70c5fec36ce38663c

Observation 7ee4bfd6-b237-46f0-82fe-4747c7b343b2 · outbound

This paper cites FLEURS: Few-shot Learning Evaluation of Universal Representations of Speech.

RoboEgo System Card: An Omnimodal Model with Native Full Duplexity FLEURS: Few-shot Learning Evaluation of Universal Representations of Speech

Reference 10

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source=pdf_text observed=2026-08-07T11:37:29.411137Z digest=sha256:3ffc522287cecd47e3c416fd24c8497942beb4827babbff6dd829d99aab50c1c

Observation 3d8b9c4e-c2d0-474e-931d-6168a4fc581d · outbound

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

RoboEgo System Card: An Omnimodal Model with Native Full Duplexity DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 11

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source=pdf_text observed=2026-08-07T11:37:29.416871Z digest=sha256:c34a0c9ce29146e2b912cd47488d94b2024e63f802672f7639bef9989652e52f

Observation 205bebd4-f948-4f6b-a46b-29ab5bb3ec73 · outbound

This paper cites Moshi: a speech-text foundation model for real-time dialogue.

RoboEgo System Card: An Omnimodal Model with Native Full Duplexity Moshi: a speech-text foundation model for real-time dialogue

Reference 12

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source=pdf_text observed=2026-08-07T11:37:29.422356Z digest=sha256:e1c94444fff0b41ee57f3ccb3fd19fcef32fbb71a2d13c4a48f251350a08aec3

Observation a718f664-0e4f-4f66-8744-7b1f5e0cab0b · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

RoboEgo System Card: An Omnimodal Model with Native Full Duplexity An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 13

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source=pdf_text observed=2026-08-07T11:37:29.428310Z digest=sha256:9bac762ae2a1e78b0eefdc24468ee43e0f055e4a7d4f6103ea538364c32e8fa2

Observation 364c6383-86cc-4d77-8d5f-e928fafe088c · outbound

This paper cites How Far Are We From AGI: Are LLMs All We Need?.

RoboEgo System Card: An Omnimodal Model with Native Full Duplexity How Far Are We From AGI: Are LLMs All We Need?

Reference 14

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source=pdf_text observed=2026-08-07T11:37:29.434061Z digest=sha256:813e03505d04db5d19e5db223bfdf600dbab880099b0d87bb00eb46f2a324609

Observation 8ec743e0-64da-49fc-9483-588b2c0c3703 · outbound

This paper cites OCRBench v2: An Improved Benchmark for Evaluating Large Multimodal Models on Visual Text Localization and Reasoning.

RoboEgo System Card: An Omnimodal Model with Native Full Duplexity OCRBench v2: An Improved Benchmark for Evaluating Large Multimodal Models on Visual Text Localization and Reasoning

Reference 15

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source=pdf_text observed=2026-08-07T11:37:29.440109Z digest=sha256:62dafc07b21fd6c9cac89cf0e28c359e4f35eb589224efe3d02a834ef398b701

Observation aa6cc821-136c-4830-bd9b-73701edc8adc · outbound

This paper cites Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context.

RoboEgo System Card: An Omnimodal Model with Native Full Duplexity Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

Reference 16

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source=pdf_text observed=2026-08-07T11:37:29.446207Z digest=sha256:0326614f1c92e513b49b4ce9a31c6386befa978bddbede6799e2302c7d1b853f

Observation 2a22f8f6-a9f4-4289-aa66-e239d873b158 · outbound

This paper cites Rae, and Laurent Sifre.

RoboEgo System Card: An Omnimodal Model with Native Full Duplexity Rae, and Laurent Sifre

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:37:30.474400Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T11:37:29.452090Z digest=sha256:555f1ec9ca13e39407d3cc007862bdf0b23e11b02999ae190ff25a0fc45dc1fd

Observation 78788d98-ae0c-4229-862e-5c5f67551f8c · outbound

This paper cites GPT-4o System Card.

RoboEgo System Card: An Omnimodal Model with Native Full Duplexity GPT-4o System Card

Reference 18

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source=pdf_text observed=2026-08-07T11:37:29.457403Z digest=sha256:f446ba398184f522003ffa0da59807733ec03ae65f7ad8aa91f8295b2d33c701

Observation 85d532d8-5615-47e3-99ff-c3e152556736 · outbound

This paper cites OpenAI o1 System Card.

RoboEgo System Card: An Omnimodal Model with Native Full Duplexity OpenAI o1 System Card

Reference 19

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source=pdf_text observed=2026-08-07T11:37:29.463050Z digest=sha256:c4306731c03b312cb8b8075a693d73cfa96e6151c786c606fa747758926c1a64

Observation 0c5a5767-4ff6-4f06-898d-3982d124a165 · outbound

This paper cites Sanketi, Quan Vuong, Thomas Kollar, Benjamin Burchfiel, Russ Tedrake, Dorsa Sadigh, Sergey Levine, Percy Liang, and Chelsea Finn.

RoboEgo System Card: An Omnimodal Model with Native Full Duplexity Sanketi, Quan Vuong, Thomas Kollar, Benjamin Burchfiel, Russ Tedrake, Dorsa Sadigh, Sergey Levine, Percy Liang, and Chelsea Finn

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T11:37:29.468653Z digest=sha256:a6d6e2f9bc638290ea6e274d580e10c4266a1736fcb92aed1185bffa65530690

Observation ff315ce8-c3b8-4a2f-92e9-141879c86774 · outbound

This paper cites Hashimoto.

RoboEgo System Card: An Omnimodal Model with Native Full Duplexity Hashimoto

Reference 21

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source=pdf_text observed=2026-08-07T11:37:29.474644Z digest=sha256:7fe2945725abc2924ee29f43c521c6b77b24c46729dbeac1ead1527f2cfdf7d2

Observation cabe497e-c6ff-4387-b2b0-3e4a29c6591e · outbound

This paper cites DeepSeek-V3 Technical Report.

RoboEgo System Card: An Omnimodal Model with Native Full Duplexity DeepSeek-V3 Technical Report

Reference 22

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source=pdf_text observed=2026-08-07T11:37:29.479700Z digest=sha256:2aa31febcd48300be9f23bb5b30faf6e7a88c982a868902194cce2572123484f

Observation 2bb8a380-5e3c-43e2-87b1-7bb621fae84b · outbound

This paper cites Visual instruction tuning.

RoboEgo System Card: An Omnimodal Model with Native Full Duplexity Visual instruction tuning

Reference 23

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T11:37:29.484656Z digest=sha256:485a6f1c6b48c4e41f450c36ab52dd8e8bc5818831e85356f66a82356ad700af

Observation bc1d0369-1056-47e4-aeea-0cb04b77de71 · outbound

This paper cites Aligning Cyber Space with Physical World: A Comprehensive Survey on Embodied AI.

RoboEgo System Card: An Omnimodal Model with Native Full Duplexity Aligning Cyber Space with Physical World: A Comprehensive Survey on Embodied AI

Reference 24

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source=pdf_text observed=2026-08-07T11:37:29.489626Z digest=sha256:c52f5b7fec76118286bc517f7a50f61e0841af5f77a93f5b6883eb99e151cbd6

Observation f3d92625-db85-4e81-b8cb-5f32161f443c · outbound

This paper cites Introducing meta llama 3: The most capable openly available llm to date.

RoboEgo System Card: An Omnimodal Model with Native Full Duplexity Introducing meta llama 3: The most capable openly available llm to date

Reference 25

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source=pdf_text observed=2026-08-07T11:37:29.495560Z digest=sha256:4eae96416b7f5e6cd8a1b6b370574a8f8aacc35d9a68a451a5f8533f87c683b2

Observation a82b8b51-06c7-4edb-8cc2-9f5c41cb3203 · outbound

This paper cites Spoken Question Answering and Speech Continuation Using Spectrogram-Powered LLM.

RoboEgo System Card: An Omnimodal Model with Native Full Duplexity Spoken Question Answering and Speech Continuation Using Spectrogram-Powered LLM

Reference 26

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:37:29.500611Z digest=sha256:8324d26968d4b69e150c7c9f6c417475590c3cba4ec26a9e2e7915466fd0bf06

Observation bad060aa-ea46-4570-95f6-d04403a5d19c · outbound

This paper cites GPT-4 Technical Report.

RoboEgo System Card: An Omnimodal Model with Native Full Duplexity GPT-4 Technical Report

Reference 27

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source=pdf_text observed=2026-08-07T11:37:29.505954Z digest=sha256:e9a885d0bff0ce16a3976fbb4fc7680692185efd1f99c4b3dedd463a8909fec6

Observation d02f64a9-f68b-4216-9716-c1ad985ecbd4 · outbound

This paper cites Librispeech: an asr corpus based on public domain audio books.

RoboEgo System Card: An Omnimodal Model with Native Full Duplexity Librispeech: an asr corpus based on public domain audio books

Reference 28

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verified fuzzy
raw_fallback, observed 2026-08-07T11:37:30.391532Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T11:37:29.511494Z digest=sha256:78c7b834afbeddb754c12621f6daa9ad9c5fcd1a9d70f29035c22605b76f61b1

Observation dd42e150-6283-4597-943b-55f0b29e69d5 · outbound

This paper cites Robust speech recognition via large-scale weak supervision.

RoboEgo System Card: An Omnimodal Model with Native Full Duplexity Robust speech recognition via large-scale weak supervision

Reference 29

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no resolver link, observed 2026-08-07T11:37:29.516219Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:37:29.516219Z digest=sha256:b6812d5e760730b42dd8de2fb8abf9e2ebfefe7e31286b06b921faed30d0d594

Observation 700daae0-b968-4cde-a896-0c462a505c51 · outbound

This paper cites Cambrian-1: A fully open, vision-centric exploration of multimodal llms.

RoboEgo System Card: An Omnimodal Model with Native Full Duplexity Cambrian-1: A fully open, vision-centric exploration of multimodal llms

Reference 30

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source=pdf_text observed=2026-08-07T11:37:29.520942Z digest=sha256:5a3d54f165ce58676e6a277380f6b5131a7f9b99e82e7a7573ab34e3acd42785

Observation 0ef88fd6-a900-4fa0-9932-4189ab38e674 · outbound

This paper cites Attention is all you need.

RoboEgo System Card: An Omnimodal Model with Native Full Duplexity Attention is all you need

Reference 31

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source=pdf_text observed=2026-08-07T11:37:29.525946Z digest=sha256:aa3d53ed1dc8250494e4632c6aec8035ba3319edef81f449d75ae95cf9f59fd6

Observation 77089db2-4afc-4d26-adc4-7de818332873 · outbound

This paper cites A Full-duplex Speech Dialogue Scheme Based On Large Language Models.

RoboEgo System Card: An Omnimodal Model with Native Full Duplexity A Full-duplex Speech Dialogue Scheme Based On Large Language Models

Reference 32

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source=pdf_text observed=2026-08-07T11:37:29.532711Z digest=sha256:8021c99025531da2483b5596b25af6759e64bdf6048179f8abe070c54e8864cc

Observation f9f5c89c-e45a-466c-8a39-ce634b0e827a · outbound

This paper cites Toward Embodied AGI: A Review of Embodied AI and the Road Ahead.

RoboEgo System Card: An Omnimodal Model with Native Full Duplexity Toward Embodied AGI: A Review of Embodied AI and the Road Ahead

Reference 33

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source=pdf_text observed=2026-08-07T11:37:29.538961Z digest=sha256:c89577c737112d670f7b646ed6d6d6fb6d8a7d9659927f3db5357c9b87c58803

Observation 1497ecc2-ba79-45d4-beed-495bb4be1ccb · outbound

This paper cites Realworldqa, 2024.

RoboEgo System Card: An Omnimodal Model with Native Full Duplexity Realworldqa, 2024

Reference 34

Resolution
parse uncertain
raw_fallback, observed 2026-08-07T11:37:30.339146Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T11:37:29.544455Z digest=sha256:2de298e0be11bad06cc1e27682c02f576c40ac1bcf4eea48af4b91b4ea2a1fec

Observation 3f01608d-d34d-4441-ae77-948c9a6e6f7c · outbound

This paper cites Mini-Omni: Language Models Can Hear, Talk While Thinking in Streaming.

RoboEgo System Card: An Omnimodal Model with Native Full Duplexity Mini-Omni: Language Models Can Hear, Talk While Thinking in Streaming

Reference 35

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source=pdf_text observed=2026-08-07T11:37:29.549793Z digest=sha256:3800b91e5fed643611b61fc48e21ecae2fbb995c1a0e53485b7c9c6991761013

Observation 43ecb25e-55e9-4531-9a7a-c1b9d7121b3a · outbound

This paper cites Qwen2.5-Omni Technical Report.

RoboEgo System Card: An Omnimodal Model with Native Full Duplexity Qwen2.5-Omni Technical Report

Reference 36

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:37:29.555975Z digest=sha256:7ce1d155c4d3dacc73061e4b92cf363e712174ee9268dafa4bfcb73f1a1c3183

Observation 1ce45bce-61fd-40c5-87a5-094ce26829c4 · outbound

This paper cites Qwen3 Technical Report.

RoboEgo System Card: An Omnimodal Model with Native Full Duplexity Qwen3 Technical Report

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-07T11:37:29.561570Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:37:29.561570Z digest=sha256:7181905b3437c50fc51d79c501db7bd34b85a944a7bb6defd32d792b74dc5e66

Observation 8672deed-b502-4933-8609-e00e170f9591 · outbound

This paper cites nanoLM: an Affordable LLM Pre-training Benchmark via Accurate Loss Prediction across Scales.

RoboEgo System Card: An Omnimodal Model with Native Full Duplexity nanoLM: an Affordable LLM Pre-training Benchmark via Accurate Loss Prediction across Scales

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-07T11:37:29.567091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:37:29.567091Z digest=sha256:4b2ebbbe27031b1c6c97230e9b95efcf37cc6635d7a08b583e4323337aa53723

Observation 3b4f3436-19cd-489e-916d-b31c41bebdc1 · outbound

This paper cites Minicpm-o 2.6: A gpt-4o level mllm for vision, speech, and multimodal live streaming on your phone, 2025.

RoboEgo System Card: An Omnimodal Model with Native Full Duplexity Minicpm-o 2.6: A gpt-4o level mllm for vision, speech, and multimodal live streaming on your phone, 2025

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:37:30.322555Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T11:37:29.573571Z digest=sha256:6926a8bb269367ff570c8f3379a0d14d77270aa9fd3431c43e25f8a504b2bada

Observation 15c2a814-dcf7-46ae-8d30-826439d4d860 · outbound

This paper cites Scaling Speech-Text Pre-training with Synthetic Interleaved Data.

RoboEgo System Card: An Omnimodal Model with Native Full Duplexity Scaling Speech-Text Pre-training with Synthetic Interleaved Data

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-07T11:37:29.578574Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:37:29.578574Z digest=sha256:92a8e7947250870a2137570806dedfc1fea0e5bae6a223d22853ac468ae6b104

Observation b9d5610c-f5b1-48bc-b077-e47adcf00a40 · outbound

This paper cites Wenetspeech: A 10000+ hours multi-domain mandarin corpus for speech recognition.

RoboEgo System Card: An Omnimodal Model with Native Full Duplexity Wenetspeech: A 10000+ hours multi-domain mandarin corpus for speech recognition

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:37:30.303980Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T11:37:29.583577Z digest=sha256:f5b65a96b3ee34204955df0cb80554d8b39a0470c3224f408dec2a0ed25fbf8c

Observation be8c39de-ae70-4e0d-8c33-8fc5ed74d9d9 · outbound

This paper cites OmniFlatten: An End-to-end GPT Model for Seamless Voice Conversation.

RoboEgo System Card: An Omnimodal Model with Native Full Duplexity OmniFlatten: An End-to-end GPT Model for Seamless Voice Conversation

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-07T11:37:29.589186Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:37:29.589186Z digest=sha256:1b789b574a59fb82dbcee13a8d207ac79de459a8f1ad4b4898645cdaf1ad64e2

Observation 3f76f1c3-893c-4f7f-8ca5-7082a4e55d05 · outbound

This paper cites Beyond the turn-based game: Enabling real-time conversations with duplex models.

RoboEgo System Card: An Omnimodal Model with Native Full Duplexity Beyond the turn-based game: Enabling real-time conversations with duplex models

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-07T11:37:29.595125Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:37:29.595125Z digest=sha256:773cf8686e1f22b71492045626a28cd9376c26f838a15d70dc544c5224cabdaa

Pith citing papers

Observation 1a1e656d-e8ba-4e08-9c87-914b48a15b8f · inbound

Do Audio-Visual Large Language Models Really See and Hear? cites this paper.

Do Audio-Visual Large Language Models Really See and Hear? RoboEgo System Card: An Omnimodal Model with Native Full Duplexity

Reference 60

Resolution
verified exact
arxiv_id, observed 2026-05-13T20:58:15.859076Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-13T20:56:19.815569Z digest=sha256:6576d63ff58d1af895faddc271934d8cd92666fa8822485c999f362ff2b5b08a