Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-05-10T00:37:31.858728Z
Paper Citation Record · LEDGER
Building a Precise Video Language with Human-AI Oversight
As of 4 August 2026, this Paper Citation Record lists 100 of 109 outbound references and 1 inbound Pith citation observation for arXiv:2604.21718.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-04T06:34:03.388597+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-05-12T02:10:27.595446Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-05-12T02:11:15.529838Z
Reference resolution
100 of 109 outbound references displayed
- verified exact53
- verified fuzzy37
- unresolved7
- parse uncertain0
- malformed identifier1
- metadata mismatch2
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation e9eedcf7-ea0e-4e25-a36b-53136ad5baff · outbound
This paper cites Critique-out-Loud Reward Models.
Building a Precise Video Language with Human-AI Oversight Critique-out-Loud Reward Models
Reference 1
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T13:46:04.566261Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation a15b36a9-931e-4aae-af9e-b21bc85e7a8c · outbound
This paper cites Cycle consistency as reward: Learning image-text alignment without human preferences.
Building a Precise Video Language with Human-AI Oversight Cycle consistency as reward: Learning image-text alignment without human preferences
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T10:57:53.594783Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 06f4607a-d2a0-41d7-9c47-5a6e580fd043 · outbound
This paper cites Qwen2.5-VL Technical Report.
Building a Precise Video Language with Human-AI Oversight Qwen2.5-VL Technical Report
Reference 3
- Resolution
- verified exact
- local_arxiv, observed 2026-05-11T13:46:04.578883Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation ec221864-2935-4a42-aa07-75563e7a935b · outbound
This paper cites Improving image generation with better captions.https://cdn.openai.
Building a Precise Video Language with Human-AI Oversight Improving image generation with better captions.https://cdn.openai
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T10:57:53.762533Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 50419c15-4d9e-43c2-949d-5d1335d125af · outbound
This paper cites Measuring Progress on Scalable Oversight for Large Language Models.
Building a Precise Video Language with Human-AI Oversight Measuring Progress on Scalable Oversight for Large Language Models
Reference 5
- Resolution
- verified exact
- arxiv_id, observed 2026-05-17T15:01:41.422297Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation c697a69a-b83f-45aa-8222-9158dc93e9e7 · outbound
This paper cites Activation Reward Models for Few-Shot Model Alignment.
Building a Precise Video Language with Human-AI Oversight Activation Reward Models for Few-Shot Model Alignment
Reference 6
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T13:46:04.573192Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 9fdf966d-545e-41f9-a686-acde1a8d4700 · outbound
This paper cites AuroraCap: Efficient, Performant Video Detailed Captioning and a New Benchmark.
Building a Precise Video Language with Human-AI Oversight AuroraCap: Efficient, Performant Video Detailed Captioning and a New Benchmark
Reference 7
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T13:46:04.576239Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 31541708-eb04-487d-9adf-4426ebe3b289 · outbound
This paper cites Agneet Chatterjee, Rahim Entezari, Maksym Zhuravinskyi, Maksim Lapin, Reshinth Adithyan, Amit Raj, Chitta Baral, Yezhou Yang, and Varun Jampani.
Building a Precise Video Language with Human-AI Oversight Agneet Chatterjee, Rahim Entezari, Maksym Zhuravinskyi, Maksim Lapin, Reshinth Adithyan, Amit Raj, Chitta Baral, Yezhou Yang, and Varun Jampani
Reference 8
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-11T13:46:04.581628Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation c00a7c3a-e33c-4d74-beb9-b97b8187c1d4 · outbound
This paper cites How people use chatgpt.
Building a Precise Video Language with Human-AI Oversight How people use chatgpt
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T10:57:53.622035Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation d81cc469-82bb-4da0-ba32-304f0a53c70f · outbound
This paper cites MiniMax-M1: Scaling Test-Time Compute Efficiently with Lightning Attention.
Building a Precise Video Language with Human-AI Oversight MiniMax-M1: Scaling Test-Time Compute Efficiently with Lightning Attention
Reference 10
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T09:28:16.586976Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 1b03c787-31d2-4f1f-ab7c-09ba1e959249 · outbound
This paper cites SkyReels-V2: Infinite-length Film Generative Model.
Building a Precise Video Language with Human-AI Oversight SkyReels-V2: Infinite-length Film Generative Model
Reference 11
- Resolution
- verified exact
- arxiv_id, observed 2026-05-14T20:23:04.486750Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 8d6fb856-8573-444f-8a44-1678397164f0 · outbound
This paper cites Sharegpt4video: Improving video understanding and generation with better captions.Advances in Neural Information Processing Systems, 37:19472–19495.
Building a Precise Video Language with Human-AI Oversight Sharegpt4video: Improving video understanding and generation with better captions.Advances in Neural Information Processing Systems, 37:19472–19495
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T10:57:53.606384Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation c5d467a7-3f64-48a8-8920-ed7d4b1e35a8 · outbound
This paper cites Panda-70m: Captioning 70m videos with multiple cross- modality teachers.
Building a Precise Video Language with Human-AI Oversight Panda-70m: Captioning 70m videos with multiple cross- modality teachers
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T10:57:53.742056Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 0e9efa01-f19c-43b2-af33-481834f54bb4 · outbound
This paper cites Dress: Instructing large vision-language models to align and interact with humans via natural lan- guage feedback.
Building a Precise Video Language with Human-AI Oversight Dress: Instructing large vision-language models to align and interact with humans via natural lan- guage feedback
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T10:57:53.746356Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 90b75ce0-2758-4e5f-b709-91725c335095 · outbound
This paper cites PerceptionLM: Open-Access Data and Models for Detailed Visual Understanding.
Building a Precise Video Language with Human-AI Oversight PerceptionLM: Open-Access Data and Models for Detailed Visual Understanding
Reference 15
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T13:46:04.390564Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 401c45f7-e49b-406c-bab4-dd2801b4cc3f · outbound
This paper cites Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities.
Building a Precise Video Language with Human-AI Oversight Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities
Reference 16
- Resolution
- verified exact
- local_arxiv, observed 2026-05-11T13:46:04.491750Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 1d78293f-a1b4-4659-b132-aec9bab34279 · outbound
This paper cites Synpo: Synergizing descriptiveness and preference optimization for video detailed captioning.
Building a Precise Video Language with Human-AI Oversight Synpo: Synergizing descriptiveness and preference optimization for video detailed captioning
Reference 17
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T13:46:04.488544Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation a6a72b4d-aad8-4f9e-a7fb-06cdb0c0d91c · outbound
This paper cites Ties mat- ter: Meta-evaluating modern metrics with pairwise accuracy and tie calibration.
Building a Precise Video Language with Human-AI Oversight Ties mat- ter: Meta-evaluating modern metrics with pairwise accuracy and tie calibration
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T10:57:53.750340Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation ed2839be-4249-4b15-8cd0-bcfac256da9c · outbound
This paper cites Mo- tionsight: Boosting fine-grained motion understanding in multimodal llms.
Building a Precise Video Language with Human-AI Oversight Mo- tionsight: Boosting fine-grained motion understanding in multimodal llms
Reference 19
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T13:46:04.474762Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 1a3dc349-b33e-4776-859b-94bd6403d8a1 · outbound
This paper cites Improving clip training with language rewrites.
Building a Precise Video Language with Human-AI Oversight Improving clip training with language rewrites
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T10:57:53.766452Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 2e6f6cf1-5234-48f3-8b61-d07c1bd0f19d · outbound
This paper cites Unblocking Fine-Grained Evaluation of Detailed Captions: An Explaining AutoRater and Critic-and-Revise Pipeline.
Building a Precise Video Language with Human-AI Oversight Unblocking Fine-Grained Evaluation of Detailed Captions: An Explaining AutoRater and Critic-and-Revise Pipeline
Reference 21
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T13:46:04.497600Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 1e91b538-f976-4b34-a3de-f53d3bdf5476 · outbound
This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.
Building a Precise Video Language with Human-AI Oversight DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
Reference 22
- Resolution
- verified exact
- local_arxiv, observed 2026-05-11T13:46:04.444596Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 4eab8fb4-88dc-4e4d-a727-82e952cacafe · outbound
This paper cites Captioning images taken by people who are blind.
Building a Precise Video Language with Human-AI Oversight Captioning images taken by people who are blind
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T10:57:53.610019Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation d8a87605-6d4d-45aa-8f76-c29c9c799c21 · outbound
This paper cites Miradata: A large-scale video dataset with long durations and structured captions.Advances in Neural Information Processing Systems, 37:48955–48970.
Building a Precise Video Language with Human-AI Oversight Miradata: A large-scale video dataset with long durations and structured captions.Advances in Neural Information Processing Systems, 37:48955–48970
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T10:57:53.629694Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 4a43f467-6b72-4538-8332-b8e9ab49a570 · outbound
This paper cites TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos.
Building a Precise Video Language with Human-AI Oversight TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos
Reference 25
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T13:46:04.355382Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation d76ca6e1-d434-4986-8296-1874eb0f27f6 · outbound
This paper cites Dense-captioning events in videos.
Building a Precise Video Language with Human-AI Oversight Dense-captioning events in videos
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T10:57:53.625831Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation ae0e9b7c-b088-4cc8-b11e-3f19f7350c8d · outbound
This paper cites Videopasta: 7k preference pairs that matter for video-llm alignment.
Building a Precise Video Language with Human-AI Oversight Videopasta: 7k preference pairs that matter for video-llm alignment
Reference 27
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T13:46:04.362744Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 116576c4-bd88-43ba-8753-b4f5db295734 · outbound
This paper cites Mmr1: Enhancing multimodal reasoning with variance-aware sampling and open resources.
Building a Precise Video Language with Human-AI Oversight Mmr1: Enhancing multimodal reasoning with variance-aware sampling and open resources
Reference 28
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T13:46:04.449001Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation ac5efaae-6185-4e1b-870f-79d132f06187 · outbound
This paper cites Evaluating and improving compositional text-to-visual generation.
Building a Precise Video Language with Human-AI Oversight Evaluating and improving compositional text-to-visual generation
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T10:57:53.738018Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation bc7a5f59-65ab-48d1-8a02-19a18dca9090 · outbound
This paper cites Naturalbench: Evalu- ating vision-language models on natural adversarial samples.
Building a Precise Video Language with Human-AI Oversight Naturalbench: Evalu- ating vision-language models on natural adversarial samples
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T10:57:53.618555Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation d56732cd-baac-4ee8-89e9-ba0e76b85cfc · outbound
This paper cites Fire: A dataset for feedback integration and refinement evalu- ation of multimodal models.Advances in Neural Information Processing Systems, 37:101618–101640.
Building a Precise Video Language with Human-AI Oversight Fire: A dataset for feedback integration and refinement evalu- ation of multimodal models.Advances in Neural Information Processing Systems, 37:101618–101640
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T10:57:53.659959Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 1da19f52-9a29-4949-acb7-04330ab36821 · outbound
This paper cites Describe Anything: Detailed Localized Image and Video Captioning.
Building a Precise Video Language with Human-AI Oversight Describe Anything: Detailed Localized Image and Video Captioning
Reference 32
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T13:46:04.395869Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation b5f31781-152d-4b68-9fe1-3bff1c292f0c · outbound
This paper cites Multimodality helps unimodality: Cross- modal few-shot learning with multimodal models.
Building a Precise Video Language with Human-AI Oversight Multimodality helps unimodality: Cross- modal few-shot learning with multimodal models
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T10:57:53.614146Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation ed0e9454-7441-4148-89dd-c43c9464f95d · outbound
This paper cites Revisiting the Role of Language Priors in Vision-Language Models.
Building a Precise Video Language with Human-AI Oversight Revisiting the Role of Language Priors in Vision-Language Models
Reference 34
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T13:46:04.507451Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 610a4531-40be-463b-9e7c-4064aefe9996 · outbound
This paper cites Evaluating Text-to-Visual Generation with Image-to-Text Generation.
Building a Precise Video Language with Human-AI Oversight Evaluating Text-to-Visual Generation with Image-to-Text Generation
Reference 35
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T13:46:04.455477Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation d78503c1-5dde-4e15-bf05-6da70b76daa8 · outbound
This paper cites Towards un- derstanding camera motions in any video.
Building a Precise Video Language with Human-AI Oversight Towards un- derstanding camera motions in any video
Reference 36
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T10:57:53.754022Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 02e83265-309d-4208-9ee6-014d57a575ba · outbound
This paper cites Language Models as Black-Box Optimizers for Vision-Language Models.
Building a Precise Video Language with Human-AI Oversight Language Models as Black-Box Optimizers for Vision-Language Models
Reference 37
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T13:46:04.380042Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 920dda8b-60d4-4540-ae58-5e2bcc7c36d2 · outbound
This paper cites Inference-time scaling for generalist reward modeling.
Building a Precise Video Language with Human-AI Oversight Inference-time scaling for generalist reward modeling
Reference 38
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T13:46:04.366143Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 0ced2900-fdf0-48fe-bf91-46c0cb81480e · outbound
This paper cites Liu, C.-W.
Building a Precise Video Language with Human-AI Oversight Liu, C.-W
Reference 39
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-11T13:46:04.458720Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation aaae4784-7ddb-47e9-b285-17460b58f9c0 · outbound
This paper cites Omni-captioner: Data pipeline, mod- els, and benchmark for omni detailed perception.
Building a Precise Video Language with Human-AI Oversight Omni-captioner: Data pipeline, mod- els, and benchmark for omni detailed perception
Reference 40
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T13:46:04.423071Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 555fbe6a-3994-4b86-8d91-31d91fd74cb3 · outbound
This paper cites Self-refine: It- erative refinement with self-feedback.Advances in Neural Information Processing Systems, 36:46534–46594.
Building a Precise Video Language with Human-AI Oversight Self-refine: It- erative refinement with self-feedback.Advances in Neural Information Processing Systems, 36:46534–46594
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T10:57:53.640879Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation b357e0b2-48e4-4405-bdae-47f7827693cb · outbound
This paper cites Native language pro- motes access to visual consciousness.Psychological Science, 29(11):1757–1772.
Building a Precise Video Language with Human-AI Oversight Native language pro- motes access to visual consciousness.Psychological Science, 29(11):1757–1772
Reference 42
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T10:57:53.584261Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation a5806370-9914-4158-9a1a-0b5fc8847c67 · outbound
This paper cites LLM Critics Help Catch LLM Bugs.
Building a Precise Video Language with Human-AI Oversight LLM Critics Help Catch LLM Bugs
Reference 43
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T13:46:04.557005Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 36e73833-b17f-49e4-9a20-48e792f14e45 · outbound
This paper cites VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking.
Building a Precise Video Language with Human-AI Oversight VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking
Reference 44
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T13:46:04.484250Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 642668d0-5545-4f39-b802-9518ff0dcce8 · outbound
This paper cites Enhancing few- shot vision-language classification with large multimodal model features.
Building a Precise Video Language with Human-AI Oversight Enhancing few- shot vision-language classification with large multimodal model features
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T10:57:53.703165Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation d0ecbb6b-09db-4cb7-b11d-87f97e9d8521 · outbound
This paper cites Language can shape the perception of oriented objects.
Building a Precise Video Language with Human-AI Oversight Language can shape the perception of oriented objects
Reference 46
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T10:57:53.652518Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation c91a6621-de1f-48c0-8eb9-48ac08e1dac3 · outbound
This paper cites Docci: De- scriptions of connected and contrasting images.
Building a Precise Video Language with Human-AI Oversight Docci: De- scriptions of connected and contrasting images
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T10:57:53.730074Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation cce94aa3-61de-4abd-bcf8-78fd22ff39a1 · outbound
This paper cites GPT-4 Technical Report.
Building a Precise Video Language with Human-AI Oversight GPT-4 Technical Report
Reference 48
- Resolution
- verified exact
- local_arxiv, observed 2026-05-11T13:46:04.494657Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation fab64950-2ef3-416f-8252-261540142da0 · outbound
This paper cites Training language models to follow instructions with human feedback.Advances in Neural Information Processing Systems, 35:27730–27744.
Building a Precise Video Language with Human-AI Oversight Training language models to follow instructions with human feedback.Advances in Neural Information Processing Systems, 35:27730–27744
Reference 49
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T10:57:53.722707Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 09d4df88-1d67-471a-bf52-5a46939c7e47 · outbound
This paper cites The Neglected Tails in Vision-Language Models.
Building a Precise Video Language with Human-AI Oversight The Neglected Tails in Vision-Language Models
Reference 50
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T13:46:04.553346Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 6a627dc3-bee6-48ab-98de-cd8fc0408b04 · outbound
This paper cites Direct prefer- ence optimization: Your language model is secretly a reward model.Advances in neural information processing systems, 36:53728–53741.
Building a Precise Video Language with Human-AI Oversight Direct prefer- ence optimization: Your language model is secretly a reward model.Advances in neural information processing systems, 36:53728–53741
Reference 51
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T10:57:53.637352Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 43039de7-bff4-4315-9231-b565572fde46 · outbound
This paper cites Moodio: Making anyone a professional video studio.
Building a Precise Video Language with Human-AI Oversight Moodio: Making anyone a professional video studio
Reference 52
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T10:57:53.633332Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation abe315a5-7067-4893-ad38-89e05322cd72 · outbound
This paper cites Self-critiquing models for assisting human evaluators.
Building a Precise Video Language with Human-AI Oversight Self-critiquing models for assisting human evaluators
Reference 53
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T20:25:41.981797Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation f404c9b1-1fe6-4cf1-abb8-991087306050 · outbound
This paper cites Proximal Policy Optimization Algorithms.
Building a Precise Video Language with Human-AI Oversight Proximal Policy Optimization Algorithms
Reference 54
- Resolution
- verified exact
- local_arxiv, observed 2026-05-11T13:46:04.374998Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 3638098c-5729-459b-afa4-0a1fd9a4fc43 · outbound
This paper cites Transnet v2: An effective deep network architecture for fast shot transition detection.
Building a Precise Video Language with Human-AI Oversight Transnet v2: An effective deep network architecture for fast shot transition detection
Reference 55
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T10:57:53.784433Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 3f1654f2-972b-4eba-9820-27121f0a7708 · outbound
This paper cites Univ of California Press.
Building a Precise Video Language with Human-AI Oversight Univ of California Press
Reference 56
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T10:57:53.719004Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 1fdf3072-c114-448c-b7b4-a0eaf1dd41b5 · outbound
This paper cites Going beyond one-size- fits-all image descriptions to satisfy the information wants of people who are blind or have low vision.
Building a Precise Video Language with Human-AI Oversight Going beyond one-size- fits-all image descriptions to satisfy the information wants of people who are blind or have low vision
Reference 57
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T10:57:53.663455Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation a1876222-65cd-496b-a2f7-0b2893d96e6d · outbound
This paper cites video-SALMONN 2: Caption-enhanced audio-visual large language models.
Building a Precise Video Language with Human-AI Oversight video-SALMONN 2: Caption-enhanced audio-visual large language models
Reference 58
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T13:46:04.532001Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 7c73f769-4a9d-49d2-aae9-80d07f013e11 · outbound
This paper cites Granite Vision: a lightweight, open-source multimodal model for enterprise Intelligence.
Building a Precise Video Language with Human-AI Oversight Granite Vision: a lightweight, open-source multimodal model for enterprise Intelligence
Reference 59
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T13:46:04.406418Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation e991aa20-8fa8-414d-8276-9af26d05fb64 · outbound
This paper cites Wan: Open and Advanced Large-Scale Video Generative Models.
Building a Precise Video Language with Human-AI Oversight Wan: Open and Advanced Large-Scale Video Generative Models
Reference 60
- Resolution
- verified exact
- local_arxiv, observed 2026-05-11T13:46:04.437267Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 3b876ced-1ea4-4dad-ac02-ba66176a193c · outbound
This paper cites Tarsier: Recipes for Training and Evaluating Large Video Description Models.
Building a Precise Video Language with Human-AI Oversight Tarsier: Recipes for Training and Evaluating Large Video Description Models
Reference 61
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T13:46:04.401243Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 7c85acd8-b1ef-479b-8583-72beb5f4d15a · outbound
This paper cites Spatialvid: A large-scale video dataset with spatial annotations.arXiv preprint arXiv:2509.09676, 2025a.
Building a Precise Video Language with Human-AI Oversight Spatialvid: A large-scale video dataset with spatial annotations.arXiv preprint arXiv:2509.09676, 2025a
Reference 62
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T13:46:04.527564Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 2ac2a1e3-f852-4bfd-a894-90c20f47c1a1 · outbound
This paper cites InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency.
Building a Precise Video Language with Human-AI Oversight InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency
Reference 63
- Resolution
- verified exact
- local_arxiv, observed 2026-05-11T13:46:04.471178Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 17f1de07-8b54-4c5f-8b14-063ac5ec519a · outbound
This paper cites Self-Consistency Improves Chain of Thought Reasoning in Language Models.
Building a Precise Video Language with Human-AI Oversight Self-Consistency Improves Chain of Thought Reasoning in Language Models
Reference 64
- Resolution
- verified exact
- local_arxiv, observed 2026-05-11T13:46:04.500300Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 06990ab1-b734-4eab-9a9e-73a7c6db852f · outbound
This paper cites SoTA with Less: MCTS-Guided Sample Selection for Data-Efficient Visual Reasoning Self-Improvement.
Building a Precise Video Language with Human-AI Oversight SoTA with Less: MCTS-Guided Sample Selection for Data-Efficient Visual Reasoning Self-Improvement
Reference 65
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T13:46:04.410651Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation d92826e6-801a-40ec-8eb5-c169f641af7b · outbound
This paper cites Critique Fine-Tuning: Learning to Critique is More Effective than Learning to Imitate.
Building a Precise Video Language with Human-AI Oversight Critique Fine-Tuning: Learning to Critique is More Effective than Learning to Imitate
Reference 66
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T13:46:04.441298Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 67b79438-5040-4fcf-bf0e-f45dcbcbc217 · outbound
This paper cites Perception in Reflection.
Building a Precise Video Language with Human-AI Oversight Perception in Reflection
Reference 67
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T13:46:04.452323Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 5b274cdf-a283-410d-8051-6404ee0f3811 · outbound
This paper cites Russian blues reveal effects of language on color discrimination.Proceedings of the national academy of sciences, 104(19):7780–7785.
Building a Precise Video Language with Human-AI Oversight Russian blues reveal effects of language on color discrimination.Proceedings of the national academy of sciences, 104(19):7780–7785
Reference 68
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T10:57:53.649141Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 6f3619df-454b-4890-9bdd-b361fc6f3df6 · outbound
This paper cites Tractatus logico-philosophicus.
Building a Precise Video Language with Human-AI Oversight Tractatus logico-philosophicus
Reference 69
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T10:57:53.726613Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation f4b0ca41-deb5-4562-8a85-b082ccdc5040 · outbound
This paper cites UGC-VideoCaptioner : An omni ugc video detail caption model and new benchmarks.
Building a Precise Video Language with Human-AI Oversight UGC-VideoCaptioner : An omni ugc video detail caption model and new benchmarks
Reference 70
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T13:46:04.428524Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 3cc8b25a-e96a-4bff-9df5-1e7b0918f531 · outbound
This paper cites Visco: Benchmarking 12 fine-grained critique and correction towards self-improvement in visual reasoning.
Building a Precise Video Language with Human-AI Oversight Visco: Benchmarking 12 fine-grained critique and correction towards self-improvement in visual reasoning
Reference 71
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T10:57:53.715516Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 986a1ed0-7cae-4c83-9a50-51d8501ef1e2 · outbound
This paper cites Msr-vtt: A large video description dataset for bridging video and language.
Building a Precise Video Language with Human-AI Oversight Msr-vtt: A large video description dataset for bridging video and language
Reference 72
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T10:57:53.644783Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation aae24a09-cf0d-4e5a-b627-1f12c7a66bfe · outbound
This paper cites UltraVideo: High-Quality UHD Video Dataset with Comprehensive Captions.
Building a Precise Video Language with Human-AI Oversight UltraVideo: High-Quality UHD Video Dataset with Comprehensive Captions
Reference 73
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T13:46:04.545079Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation b6976d6d-24d1-4bf3-8451-2e2fd8e87daf · outbound
This paper cites Videochat-r1.
Building a Precise Video Language with Human-AI Oversight Videochat-r1
Reference 74
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T13:46:04.515301Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation cdc0f7b5-e307-49ef-99c0-3247e225d0e2 · outbound
This paper cites Qwen3 Technical Report.
Building a Precise Video Language with Human-AI Oversight Qwen3 Technical Report
Reference 75
- Resolution
- verified exact
- local_arxiv, observed 2026-05-11T13:46:04.385125Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 41e5262b-1c59-46c4-a7c8-f586ef0ccd47 · outbound
This paper cites Kwai Keye-VL 1.5 Technical Report.
Building a Precise Video Language with Human-AI Oversight Kwai Keye-VL 1.5 Technical Report
Reference 76
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T13:46:04.503586Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation c70b1334-2a5e-4107-8010-c0a8cfe02d17 · outbound
This paper cites Vript: A video is worth thousands of words.Advances in Neural Information Processing Systems, 37:57240–57261.
Building a Precise Video Language with Human-AI Oversight Vript: A video is worth thousands of words.Advances in Neural Information Processing Systems, 37:57240–57261
Reference 77
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T10:57:53.675429Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 0301289b-53ba-42bb-a78a-9253bb63f7ef · outbound
This paper cites Multimodal RewardBench: Holistic Evaluation of Reward Models for Vision Language Models.
Building a Precise Video Language with Human-AI Oversight Multimodal RewardBench: Holistic Evaluation of Reward Models for Vision Language Models
Reference 78
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T13:46:04.512494Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 446f8eea-975c-4e69-9a51-32bf8ecbe9a6 · outbound
This paper cites Omnivinci: Enhancing architecture and data for omni-modal understanding llm.
Building a Precise Video Language with Human-AI Oversight Omnivinci: Enhancing architecture and data for omni-modal understanding llm
Reference 79
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T13:46:04.541934Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation a0d3fcfe-5e05-4f60-a8bf-6992b3793198 · outbound
This paper cites DAPO: An Open-Source LLM Reinforcement Learning System at Scale.
Building a Precise Video Language with Human-AI Oversight DAPO: An Open-Source LLM Reinforcement Learning System at Scale
Reference 80
- Resolution
- verified exact
- local_arxiv, observed 2026-05-11T13:46:04.550286Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation b9131628-ea5e-4c0b-a9be-d8164d89402e · outbound
This paper cites Rlhf-v: Towards trustworthy mllms via behavior alignment from fine-grained correctional human feedback.
Building a Precise Video Language with Human-AI Oversight Rlhf-v: Towards trustworthy mllms via behavior alignment from fine-grained correctional human feedback
Reference 81
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T10:57:53.671283Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 470b0ebe-bbbc-4c34-b282-3575218a909c · outbound
This paper cites Diverse ai feedback for large language model alignment.Transactions of the Association for Computational Linguistics, 13:392–407.
Building a Precise Video Language with Human-AI Oversight Diverse ai feedback for large language model alignment.Transactions of the Association for Computational Linguistics, 13:392–407
Reference 82
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T10:57:53.707689Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 58c58590-3bd8-48e6-b25b-a0b1448d2c79 · outbound
This paper cites Self-Generated Critiques Boost Reward Modeling for Language Models.
Building a Precise Video Language with Human-AI Oversight Self-Generated Critiques Boost Reward Modeling for Language Models
Reference 83
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T13:46:04.461763Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 64567a72-0e1e-4f4b-9842-6764df4e8f78 · outbound
This paper cites Socratic Models: Composing Zero-Shot Multimodal Reasoning with Language.
Building a Precise Video Language with Human-AI Oversight Socratic Models: Composing Zero-Shot Multimodal Reasoning with Language
Reference 84
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T09:50:01.041344Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 1240c1d5-88f3-4bf3-b071-43b958528b03 · outbound
This paper cites Critic-v: Vlm critics help catch vlm errors in multimodal reasoning.
Building a Precise Video Language with Human-AI Oversight Critic-v: Vlm critics help catch vlm errors in multimodal reasoning
Reference 85
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T10:57:53.679253Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation c4bf2f72-1de4-411c-b375-54d1efc47545 · outbound
This paper cites Direct Preference Optimization of Video Large Multimodal Models from Language Model Reward.
Building a Precise Video Language with Human-AI Oversight Direct Preference Optimization of Video Large Multimodal Models from Language Model Reward
Reference 86
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T13:46:04.359535Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 567f4ded-f209-43b9-981a-2df0fcec0af6 · outbound
This paper cites VCapsBench: A Large-scale Fine-grained Benchmark for Video Caption Quality Evaluation.
Building a Precise Video Language with Human-AI Oversight VCapsBench: A Large-scale Fine-grained Benchmark for Video Caption Quality Evaluation
Reference 87
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T13:46:04.547812Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation dd93ae88-6690-4b52-b09e-642ad95b154e · outbound
This paper cites MM-RLHF: The Next Step Forward in Multimodal LLM Alignment.
Building a Precise Video Language with Human-AI Oversight MM-RLHF: The Next Step Forward in Multimodal LLM Alignment
Reference 88
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T13:46:04.467982Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 59e1817f-572d-48ce-b27c-881f952ef19c · outbound
This paper cites OmniAlign-V: Towards Enhanced Alignment of MLLMs with Human Preference.
Building a Precise Video Language with Human-AI Oversight OmniAlign-V: Towards Enhanced Alignment of MLLMs with Human Preference
Reference 89
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T13:46:04.414865Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 642faeba-3ec0-4052-a2a4-953c14d80d2d · outbound
This paper cites OwlCap: Harmonizing Motion-Detail for Video Captioning via HMD-270K and Caption Set Equivalence Reward.
Building a Precise Video Language with Human-AI Oversight OwlCap: Harmonizing Motion-Detail for Video Captioning via HMD-270K and Caption Set Equivalence Reward
Reference 90
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T13:46:04.477814Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation ba0644b0-a956-4225-9c19-6a4fc48eabad · outbound
This paper cites bird’s-eye view.
Building a Precise Video Language with Human-AI Oversight bird’s-eye view
Reference 91
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T10:57:53.682997Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation fe87bb66-a9f6-41aa-aae5-bf6fb200a33f · outbound
This paper cites Roughly one sentence may need addition, modification, or deletion.
Building a Precise Video Language with Human-AI Oversight Roughly one sentence may need addition, modification, or deletion
Reference 92
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T10:57:53.691451Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 77b4effc-78f4-44a0-8048-dcce58e74724 · outbound
This paper cites an unresolved cited work.
Building a Precise Video Language with Human-AI Oversight Unresolved cited work
Reference 93
- Resolution
- unresolved
- raw_fallback, observed 2026-05-23T10:57:53.777110Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation f1bef335-57cd-4d22-b89d-6447275cb736 · outbound
This paper cites an unresolved cited work.
Building a Precise Video Language with Human-AI Oversight Unresolved cited work
Reference 94
- Resolution
- unresolved
- raw_fallback, observed 2026-05-23T10:57:53.780646Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 94537efb-c622-4f5c-82cc-d70971f8815c · outbound
This paper cites conveying changes in actions, behaviors, environments, states and attributes of objects, and camera movements between adjacent frames.
Building a Precise Video Language with Human-AI Oversight conveying changes in actions, behaviors, environments, states and attributes of objects, and camera movements between adjacent frames
Reference 95
- Resolution
- malformed identifier
- raw_fallback, observed 2026-05-23T10:57:53.687474Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 48330530-902c-4040-b965-af0d8c596305 · outbound
This paper cites an unresolved cited work.
Building a Precise Video Language with Human-AI Oversight Unresolved cited work
Reference 96
- Resolution
- unresolved
- raw_fallback, observed 2026-05-23T10:57:53.602156Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 8f109f96-40cd-453e-be17-b4d4c78d26c5 · outbound
This paper cites an unresolved cited work.
Building a Precise Video Language with Human-AI Oversight Unresolved cited work
Reference 97
- Resolution
- unresolved
- raw_fallback, observed 2026-05-23T10:57:53.711652Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 57f7b7a2-bcb2-414d-8bb9-bdb056cc7933 · outbound
This paper cites an unresolved cited work.
Building a Precise Video Language with Human-AI Oversight Unresolved cited work
Reference 98
- Resolution
- unresolved
- raw_fallback, observed 2026-05-23T10:57:53.656327Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 5611d61e-26f7-413a-9b26-6e87c13383c8 · outbound
This paper cites an unresolved cited work.
Building a Precise Video Language with Human-AI Oversight Unresolved cited work
Reference 99
- Resolution
- unresolved
- raw_fallback, observed 2026-05-23T10:57:53.733996Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 0b17e300-459f-46b3-8ac2-73fb3146fc98 · outbound
This paper cites an unresolved cited work.
Building a Precise Video Language with Human-AI Oversight Unresolved cited work
Reference 100
- Resolution
- unresolved
- raw_fallback, observed 2026-05-23T10:57:53.787950Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Pith citing papers
Observation 0deed888-ebdf-4f65-b6a6-ab5d3db5e0b2 · inbound
Offline Preference Optimization for Rectified Flow with Noise-Tracked Pairs cites this paper.
Offline Preference Optimization for Rectified Flow with Noise-Tracked Pairs Building a Precise Video Language with Human-AI Oversight
Reference 25
- Resolution
- verified exact
- local_arxiv, observed 2026-05-12T02:11:15.531611Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.