Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation | Paper Citation Record

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This paper cites Qwen Technical Report.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation Qwen Technical Report

Reference 1

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This paper cites Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

Reference 2

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Observation a5525f58-491f-4f40-93f7-0b2218537b1b · outbound

This paper cites One Token to Seg Them All: Language Instructed Reasoning Segmentation in Videos.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation One Token to Seg Them All: Language Instructed Reasoning Segmentation in Videos

Reference 3

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This paper cites METEOR: An Au- tomatic Metric for MT Evaluation with Improved Correla- tion with Human Judgments.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation METEOR: An Au- tomatic Metric for MT Evaluation with Improved Correla- tion with Human Judgments

Reference 4

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This paper cites End-to-End Referring Video Object Segmentation with Mul- timodal Transformers.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation End-to-End Referring Video Object Segmentation with Mul- timodal Transformers

Reference 5

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Observation e8e3eb20-6961-4062-a322-8376d74a004c · outbound

This paper cites Auditory Scene Analysis: The Perceptual Organization of Sound.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation Auditory Scene Analysis: The Perceptual Organization of Sound

Reference 6

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This paper cites COCO- Stuff: Thing and Stuff Classes in Context.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation COCO- Stuff: Thing and Stuff Classes in Context

Reference 7

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Observation e53caa16-5819-4119-b0bd-d8051b52809f · outbound

This paper cites TIM: A Time Interval Ma- chine for Audio-Visual Action Recognition.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation TIM: A Time Interval Ma- chine for Audio-Visual Action Recognition

Reference 8

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Observation c505fc3d-73be-4808-9367-b907a3ce0dc7 · outbound

This paper cites GigaSpeech: An Evolving, Multi-domain ASR Corpus with 10,000 Hours of Transcribed Audio.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation GigaSpeech: An Evolving, Multi-domain ASR Corpus with 10,000 Hours of Transcribed Audio

Reference 9

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Observation 1ae1bae4-45c0-424a-8d2f-ee1031106421 · outbound

This paper cites VGGSound: A Large-scale Audio-Visual Dataset.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation VGGSound: A Large-scale Audio-Visual Dataset

Reference 10

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Observation 042946cb-fc4c-4e03-a6e0-73db51bb935a · outbound

This paper cites Detect What You Can: Detecting and Representing Objects using Holistic Models and Body Parts.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation Detect What You Can: Detecting and Representing Objects using Holistic Models and Body Parts

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:16:12.210671Z

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Observation 646c8340-d9cb-4d95-8eeb-802e3e114d5e · outbound

This paper cites Vision Transformer Adapter for Dense Predictions.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation Vision Transformer Adapter for Dense Predictions

Reference 12

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Observation 76f515e9-2c19-402f-a1c4-383e0f99abb1 · outbound

This paper cites How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suites.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suites

Reference 13

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Observation 1e824bbf-bee8-4cc9-9ad0-a5e34c2278c8 · outbound

This paper cites Masked-attention Mask Transformer for Universal Image Segmentation.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation Masked-attention Mask Transformer for Universal Image Segmentation

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:16:12.171004Z

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This paper cites VideoLLaMA 2: Advancing Spatial-Temporal Modeling and Audio Understanding in Video-LLMs.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation VideoLLaMA 2: Advancing Spatial-Temporal Modeling and Audio Understanding in Video-LLMs

Reference 15

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Observation b10fd106-834c-4e6d-8b7b-ad7c8fdc633b · outbound

This paper cites Qwen2-Audio Technical Report.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation Qwen2-Audio Technical Report

Reference 16

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Observation f6258804-80df-43ff-9a14-46e88b13db52 · outbound

This paper cites MeViS: A Large-scale Benchmark for Video Segmentation with Motion Expressions.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation MeViS: A Large-scale Benchmark for Video Segmentation with Motion Expressions

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:16:12.149630Z

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Observation 01f7c39d-536f-4319-b801-04d6ef0370b8 · outbound

This paper cites MOSE: A New Dataset for Video Object Segmentation in Complex Scenes.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation MOSE: A New Dataset for Video Object Segmentation in Complex Scenes

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:16:12.128980Z

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Observation 4f1abf28-9b01-48f0-80fc-2db69cc2c347 · outbound

This paper cites Multimodal referring segmentation: A survey.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation Multimodal referring segmentation: A survey

Reference 19

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Observation 6c58ef9c-39ad-43f1-91f7-91a7b233dcde · outbound

This paper cites MOSEv2: A more challenging dataset for video object segmentation in complex scenes.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation MOSEv2: A more challenging dataset for video object segmentation in complex scenes

Reference 20

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This paper cites VITA: Towards Open-Source Interactive Omni Multimodal LLM.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation VITA: Towards Open-Source Interactive Omni Multimodal LLM

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:16:12.070253Z

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Observation 48a5fa52-7c80-4b18-8b04-ac3a66fa6e90 · outbound

This paper cites A VSegFormer: Audio-Visual Segmentation with Transformer.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation A VSegFormer: Audio-Visual Segmentation with Transformer

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:16:12.052365Z

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Observation 4dd43122-d005-4916-bbd3-36838b48a4d8 · outbound

This paper cites https://github.com/RVC- Boss/ GPT-SoVITS, 2024.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation https://github.com/RVC- Boss/ GPT-SoVITS, 2024

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:16:12.032935Z

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Observation 405c891e-2575-4736-bdea-30422574e22c · outbound

This paper cites Open- V ocabulary Audio-Visual Semantic Segmentation.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation Open- V ocabulary Audio-Visual Semantic Segmentation

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:16:12.016780Z

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This paper cites Multi- modal Instruction Tuned LLMs with Fine-grained Visual Perception.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation Multi- modal Instruction Tuned LLMs with Fine-grained Visual Perception

Reference 25

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This paper cites Decoupling Static and Hierarchical Motion Perception for Referring Video Seg- mentation.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation Decoupling Static and Hierarchical Motion Perception for Referring Video Seg- mentation

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:16:11.977821Z

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Observation f6c70001-9a2d-426c-ad4f-06a8182e72a6 · outbound

This paper cites A Generalized Framework for Video Instance Segmentation.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation A Generalized Framework for Video Instance Segmentation

Reference 27

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Observation cd2dc9d9-8f31-40c9-a458-3c397f3283c0 · outbound

This paper cites Deep clustering: Discriminative embeddings for segmentation and separation.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation Deep clustering: Discriminative embeddings for segmentation and separation

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:16:11.942633Z

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Observation db461c65-20e1-4067-a559-4ffe04388662 · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation LoRA: Low-Rank Adaptation of Large Language Models

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:16:11.922008Z

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Observation d1af3745-296f-45f2-8d5f-9cc30daa77ac · outbound

This paper cites Egocentric Audio-Visual Object Localization.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation Egocentric Audio-Visual Object Localization

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:16:11.905791Z

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Observation 50a7f8a0-b7c0-4f1b-9ca8-a92f7895044c · outbound

This paper cites Video Object Segmentation with Language Referring Expressions.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation Video Object Segmentation with Language Referring Expressions

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:16:11.888913Z

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Observation 672b7acd-ee7b-4197-8a0b-e39f025dd6dd · outbound

This paper cites Segment Anything.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation Segment Anything

Reference 32

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Observation e8dc9a84-77ca-4455-8bb8-8e76388a25f0 · outbound

This paper cites LISA: Reasoning Segmen- tation via Large Language Model.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation LISA: Reasoning Segmen- tation via Large Language Model

Reference 33

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Observation 64d9a684-9cda-4be5-9d2a-d1b0722f00db · outbound

This paper cites TVQA: Localized, Compositional Video Question Answer- ing.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation TVQA: Localized, Compositional Video Question Answer- ing

Reference 34

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Observation f176f74b-fda8-43ac-901b-0ec06487a5e0 · outbound

This paper cites Learning to Answer Questions in Dynamic Audio-Visual Scenarios.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation Learning to Answer Questions in Dynamic Audio-Visual Scenarios

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:16:11.819872Z

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Observation f8a8afd9-e3f0-4389-9471-37c213797fff · outbound

This paper cites Boosting Audio Visual Question Answering via Key Semantic-Aware Cues.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation Boosting Audio Visual Question Answering via Key Semantic-Aware Cues

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:16:11.800716Z

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Observation fcccefce-30db-4420-a1eb-d1a5452bf3e4 · outbound

This paper cites Do Audio-Visual Segmentation Models Truly Segment Sounding Objects? arXiv, 2025.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation Do Audio-Visual Segmentation Models Truly Segment Sounding Objects? arXiv, 2025

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:16:11.782524Z

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Observation 645602e0-6408-4407-97dc-4093b00fe8fb · outbound

This paper cites Robust Referring Video Object Segmentation with Cyclic Structural Consensus.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation Robust Referring Video Object Segmentation with Cyclic Structural Consensus

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:16:11.764123Z

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Observation c8b02ec2-3a3d-4696-8be3-73d21c9be3ea · outbound

This paper cites Baichuan-Omni Technical Report.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation Baichuan-Omni Technical Report

Reference 39

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Observation d5aae2dc-9bb8-440b-9bc7-5ff61ddce81d · outbound

This paper cites Losh: Long-short text joint prediction network for referring video object segmentation.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation Losh: Long-short text joint prediction network for referring video object segmentation

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:16:11.743164Z

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Observation 50923f62-0614-498b-9011-7e18564c6710 · outbound

This paper cites GRES: Generalized Referring Expression Segmentation.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation GRES: Generalized Referring Expression Segmentation

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:16:11.725625Z

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Observation 891931f1-a7d3-4608-bc87-9c6f7b102264 · outbound

This paper cites Primitivenet: decomposing the global constraints for referring segmenta- tion.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation Primitivenet: decomposing the global constraints for referring segmenta- tion

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:16:11.705305Z

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Observation bdfc6c6f-d5ba-4b18-93c0-8dfbcddcee92 · outbound

This paper cites Visual Instruction Tuning.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation Visual Instruction Tuning

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:16:11.688159Z

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Observation 1590031a-698e-41ca-b72f-fa229f64fbbc · outbound

This paper cites Improved Baselines with Visual Instruction Tuning.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation Improved Baselines with Visual Instruction Tuning

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:16:11.672272Z

Source-reported events for the cited work

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Observation 10ab099c-43fb-47a7-a078-5903e288deae · outbound

This paper cites ConvBench: A Multi-Turn Conversation Evaluation Benchmark with Hierarchical Ablation Capability for Large Vision-Language Models.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation ConvBench: A Multi-Turn Conversation Evaluation Benchmark with Hierarchical Ablation Capability for Large Vision-Language Models

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:16:11.654463Z

Source-reported events for the cited work

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Observation 8abb241e-01d6-4491-9e08-383ddf8654f1 · outbound

This paper cites Conv-TasNet: Surpassing Ideal Time-Frequency Magnitude Masking for Speech Sep- aration.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation Conv-TasNet: Surpassing Ideal Time-Frequency Magnitude Masking for Speech Sep- aration

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:16:11.635223Z

Source-reported events for the cited work

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Observation 015e1808-5f00-4085-98c3-22a9a3013810 · outbound

This paper cites Stepping Stones: A Progressive Training Strategy for Audio- Visual Semantic Segmentation.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation Stepping Stones: A Progressive Training Strategy for Audio- Visual Semantic Segmentation

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:16:11.610896Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 9a25fee9-c7ce-46fd-a42f-0e562430d94a · outbound

This paper cites Generation and Comprehension of Unambiguous Object Descriptions.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation Generation and Comprehension of Unambiguous Object Descriptions

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:16:11.588517Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0501c317-ebcf-452a-b993-8c1f8f8b4d2c · outbound

This paper cites V-Net: Fully Convolutional Neural Networks for V olumetric Medical Image Segmentation.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation V-Net: Fully Convolutional Neural Networks for V olumetric Medical Image Segmentation

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:16:11.570411Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6cbd765e-9f01-4245-a1ce-0c1c298c72f3 · outbound

This paper cites https://platform.openai.com/docs/ guides/text-to-speech, 2023.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation https://platform.openai.com/docs/ guides/text-to-speech, 2023

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:16:11.552583Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 82d8109d-93ff-4236-b5d7-e40bc2dcf588 · outbound

This paper cites https://openai.com/index/hello- gpt-4o, 2024.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation https://openai.com/index/hello- gpt-4o, 2024

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:16:11.534588Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6a185d90-b484-4179-baa4-a6d681f6e7b2 · outbound

This paper cites Wnet: Audio-Guided Video Object Segmentation via Wavelet-Based Cross-Modal Denoising Networks.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation Wnet: Audio-Guided Video Object Segmentation via Wavelet-Based Cross-Modal Denoising Networks

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:16:11.516684Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1b467605-e0aa-40c9-bc9c-023ef0f3f312 · outbound

This paper cites DetGPT: Detect What You Need via Reasoning.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation DetGPT: Detect What You Need via Reasoning

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:16:11.498976Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation cbcbf9cf-d2f6-449e-bbdc-68cfc1239e0c · outbound

This paper cites Robust Speech Recognition via Large-Scale Weak Supervision.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation Robust Speech Recognition via Large-Scale Weak Supervision

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:16:11.480708Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c563c37b-4b53-45a7-be18-589aece25f6f · outbound

This paper cites PACO: Parts and Attributes of Common Objects.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation PACO: Parts and Attributes of Common Objects

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:16:11.444625Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6e4bfd0c-8c92-4dff-ba5d-033188d7a457 · outbound

This paper cites SAM 2: Segment Anything in Images and Videos.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation SAM 2: Segment Anything in Images and Videos

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-06T11:16:10.292503Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 00c96345-f537-42d2-996d-8d48ef230711 · outbound

This paper cites URVOS: Unified Referring Video Object Segmentation Network with a Large-Scale Benchmark.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation URVOS: Unified Referring Video Object Segmentation Network with a Large-Scale Benchmark

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:16:11.405620Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ec9d5370-ca5d-47a2-a75d-17e77bc45517 · outbound

This paper cites video-SALMONN: Speech-Enhanced Audio-Visual Large Language Models.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation video-SALMONN: Speech-Enhanced Audio-Visual Large Language Models

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:16:11.364909Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 43f66742-91dd-46ec-8af0-56562b948142 · outbound

This paper cites Auto- ACD: A Large-scale Dataset for Audio-Language Represen- tation Learning.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation Auto- ACD: A Large-scale Dataset for Audio-Language Represen- tation Learning

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:16:11.347843Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e9f020c3-53c3-4b7e-9352-6abb95a70ee2 · outbound

This paper cites Unveiling and Mitigating Bias in Audio Visual Segmentation.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation Unveiling and Mitigating Bias in Audio Visual Segmentation

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:16:11.330373Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 10441679-27b3-40d4-ae73-4bb067d5a7d8 · outbound

This paper cites SALMONN: Towards Generic Hearing Abilities for Large Language Models.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation SALMONN: Towards Generic Hearing Abilities for Large Language Models

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:16:11.311783Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d62a2be0-8151-4f94-8b91-b354b07c882c · outbound

This paper cites Audio-Visual Event Localization in Unconstrained Videos.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation Audio-Visual Event Localization in Unconstrained Videos

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:16:11.290558Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2d7d6602-7a14-4756-bee0-279c1d915fb5 · outbound

This paper cites Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-06T11:16:10.336496Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9dc3b0b3-a9e6-4331-bf5a-a7eaa1d6b5cb · outbound

This paper cites Audio-Visual Grounding Referring Ex- pression for Robotic Manipulation.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation Audio-Visual Grounding Referring Ex- pression for Robotic Manipulation

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:16:11.271327Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 244a95f7-f82a-40e5-9e11-73152644fc18 · outbound

This paper cites Prompting Segmentation with Sound Is Generalizable Audio-Visual Source Localizer.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation Prompting Segmentation with Sound Is Generalizable Audio-Visual Source Localizer

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:16:11.253156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 977b99c5-f402-4b6c-a997-dce4e653e001 · outbound

This paper cites Can Textual Semantics Mitigate Sounding Object Segmentation Preference? In Eur.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation Can Textual Semantics Mitigate Sounding Object Segmentation Preference? In Eur

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:16:11.234846Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 631e99e6-604d-4d89-ad36-31efa91f39f7 · outbound

This paper cites Ref-A VS: Refer and Segment Objects in Audio-Visual Scenes.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation Ref-A VS: Refer and Segment Objects in Audio-Visual Scenes

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:16:11.218188Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 04473527-a83e-40a6-811e-0b61852742e8 · outbound

This paper cites Language as Queries for Referring Video Object Segmentation.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation Language as Queries for Referring Video Object Segmentation

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:16:11.198186Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 777ad773-26d4-453f-8f81-38b7847d8705 · outbound

This paper cites VISA: Reasoning Video Object Segmentation via Large Language Models.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation VISA: Reasoning Video Object Segmentation via Large Language Models

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:16:11.174877Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 8116845e-6924-4180-b5be-c901cef114e4 · outbound

This paper cites Referred by Multi-Modality: A Unified Temporal Transformer for Video Object Segmentation.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation Referred by Multi-Modality: A Unified Temporal Transformer for Video Object Segmentation

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:16:11.146807Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 46080188-6cf1-486a-8db9-15479764098e · outbound

This paper cites A VQA: A Dataset for Audio-Visual Question Answering on Videos.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation A VQA: A Dataset for Audio-Visual Question Answering on Videos

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:16:11.121804Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d1978e52-dd29-4c52-b280-80f4a309769b · outbound

This paper cites LA VT: Language-Aware Vision Transformer for Referring Image Segmentation.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation LA VT: Language-Aware Vision Transformer for Referring Image Segmentation

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:16:11.095686Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 95031c31-a3e3-417d-93f3-0937d2a67d77 · outbound

This paper cites Isda: Position-aware instance segmentation with deformable attention.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation Isda: Position-aware instance segmentation with deformable attention

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:16:11.064986Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 585b8fae-a251-4094-b1d6-05e743ac25d6 · outbound

This paper cites CTVIS: Consistent Training for Online Video Instance Segmentation.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation CTVIS: Consistent Training for Online Video Instance Segmentation

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:16:11.044795Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4478e543-28aa-49f9-8f7f-66ef2796a7c2 · outbound

This paper cites MMT-Bench: A Comprehensive Multimodal Benchmark for Evaluating Large Vision-Language Models Towards Multitask AGI.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation MMT-Bench: A Comprehensive Multimodal Benchmark for Evaluating Large Vision-Language Models Towards Multitask AGI

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:16:11.017438Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4abbf53c-1812-4652-8e2e-20332cfcfee0 · outbound

This paper cites MOVE: Motion-guided few-shot video object segmentation.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation MOVE: Motion-guided few-shot video object segmentation

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:16:10.995052Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e239833f-6bb0-4853-bbd8-114595adcdeb · outbound

This paper cites Modeling Context in Referring Expressions.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation Modeling Context in Referring Expressions

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:16:10.964609Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3f0d94cf-bbe8-4685-8d81-ca5875f7e677 · outbound

This paper cites MOTR: End-to-End Multiple-Object Tracking with Transformer.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation MOTR: End-to-End Multiple-Object Tracking with Transformer

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:16:10.945246Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ae1f22c0-d178-4c3b-ad7c-2f9fcd04f24e · outbound

This paper cites Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:16:10.921392Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 60db074e-da48-4dee-ac7e-11891f91c7ef · outbound

This paper cites LLaMA-Adapter: Efficient Fine-tuning of Large Language Models with Zero- initialized Attention.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation LLaMA-Adapter: Efficient Fine-tuning of Large Language Models with Zero- initialized Attention

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:16:10.902176Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a24455e6-9922-4a95-9d94-7a0c5ac81fa1 · outbound

This paper cites GPT4RoI: Instruction Tuning Large Language Model on Region-of-Interest.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation GPT4RoI: Instruction Tuning Large Language Model on Region-of-Interest

Reference 82

Resolution: unresolved; no resolver link, observed 2026-08-06T11:16:10.449340Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3dd6e515-9ec8-43cd-987f-fa1c1d08a13f · outbound

This paper cites DVIS: Decoupled Video Instance Segmentation Framework.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation DVIS: Decoupled Video Instance Segmentation Framework

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:16:10.885373Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f35ef5b4-7b2b-4406-9312-0d74b021a834 · outbound

This paper cites ViLLa: Video Reasoning Segmentation with Large Language Model.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation ViLLa: Video Reasoning Segmentation with Large Language Model

Reference 84

Resolution: unresolved; no resolver link, observed 2026-08-06T11:16:10.460552Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 77a47579-e561-4dec-99a8-67aeadf588f5 · outbound

This paper cites Scene Parsing through ADE20K Dataset.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation Scene Parsing through ADE20K Dataset

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:16:10.868533Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b4440455-5ce6-4e3d-bcb1-fdbf7fc961df · outbound

This paper cites Audio-Visual Segmentation.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation Audio-Visual Segmentation

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:16:10.852538Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 68aa03c1-fccc-480d-9709-0703fb587fc1 · outbound

This paper cites Tracking with Human-Intent Reasoning.

Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation Tracking with Human-Intent Reasoning

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:16:10.832815Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers