From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms | Paper Citation Record

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This paper cites SemDeDup: Data-efficient learning at web-scale through semantic deduplication.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms SemDeDup: Data-efficient learning at web-scale through semantic deduplication

Reference 1

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Observation 2c4296a2-004f-4801-bd74-854b8d2cd7f1 · outbound

This paper cites Cosmos World Foundation Model Platform for Physical AI.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms Cosmos World Foundation Model Platform for Physical AI

Reference 2

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This paper cites A Survey on Data Selection for Language Models.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms A Survey on Data Selection for Language Models

Reference 3

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From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms Qwen2.5-VL Technical Report

Reference 4

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Observation 3a7202c5-ea3b-4b6c-be2a-5323b144c4a8 · outbound

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From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms Impossible Videos

Reference 5

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This paper cites VideoPhy: Evaluating Physical Commonsense for Video Generation.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms VideoPhy: Evaluating Physical Commonsense for Video Generation

Reference 6

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This paper cites Color-filter: Conditional loss reduction filtering for targeted language model pre- training.Advances in Neural Information Processing Systems, 37:97618–97649, 2024.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms Color-filter: Conditional loss reduction filtering for targeted language model pre- training.Advances in Neural Information Processing Systems, 37:97618–97649, 2024

Reference 7

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Observation b1c1f2e6-5895-4fa9-b29a-b2decf3b019f · outbound

This paper cites Video generation models as world simulators.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms Video generation models as world simulators

Reference 8

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Observation d906720c-8b73-4ef0-b7dd-243d7ab7b5ef · outbound

This paper cites DSPO: Direct Semantic Preference Optimization for Real-World Image Super-Resolution.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms DSPO: Direct Semantic Preference Optimization for Real-World Image Super-Resolution

Reference 9

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Observation 51f2b9b5-cdb8-4c01-b8ed-0860becab8c8 · outbound

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

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms SkyReels-V2: Infinite-length Film Generative Model

Reference 10

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Observation 651e0262-16d9-4d84-8118-b80bcf027212 · outbound

This paper cites Beyond Generation: Unlocking Universal Editing via Self-Supervised Fine-Tuning.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms Beyond Generation: Unlocking Universal Editing via Self-Supervised Fine-Tuning

Reference 12

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Observation eca22b97-edd5-4a21-bee3-6e244c09a0cf · outbound

This paper cites Temporal Regularization Makes Your Video Generator Stronger.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms Temporal Regularization Makes Your Video Generator Stronger

Reference 13

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Observation 3f97f983-3978-451d-bd2f-4659026d5263 · outbound

This paper cites AlpaGasus: Training A Better Alpaca with Fewer Data.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms AlpaGasus: Training A Better Alpaca with Fewer Data

Reference 14

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Observation 343d2a48-e967-478b-9f55-9d38b4aae68e · outbound

This paper cites Goku: Flow Based Video Generative Foundation Models.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms Goku: Flow Based Video Generative Foundation Models

Reference 15

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Observation 3b7cf368-c963-439c-a184-fbbe55076843 · outbound

This paper cites Discriminator-Free Direct Preference Optimization for Video Diffusion.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms Discriminator-Free Direct Preference Optimization for Video Diffusion

Reference 16

Resolution: verified exact; local_arxiv, observed 2026-08-05T20:17:55.703370Z

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Observation b91a59fa-dad5-4157-a3dd-c05d57d37096 · outbound

This paper cites Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality.See https://vicuna.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality.See https://vicuna

Reference 17

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This paper cites UltraFeedback: Boosting Language Models with Scaled AI Feedback.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms UltraFeedback: Boosting Language Models with Scaled AI Feedback

Reference 18

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Observation 7dc9f138-2c4c-443c-816b-400c8b7f9376 · outbound

This paper cites One-Minute Video Generation with Test-Time Training.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms One-Minute Video Generation with Test-Time Training

Reference 19

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Observation 9e8b4bce-2dc5-465d-ab43-afc6dc977cb6 · outbound

This paper cites Enhancing Chat Language Models by Scaling High-quality Instructional Conversations.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms Enhancing Chat Language Models by Scaling High-quality Instructional Conversations

Reference 20

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Observation 23fa2e10-e2fa-4aba-abf4-96e4adab8997 · outbound

This paper cites What's In My Big Data?.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms What's In My Big Data?

Reference 21

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Observation 12d2df78-5f1d-4099-b3bd-77d4de623145 · outbound

This paper cites Wave: Warping ddim inversion features for zero-shot text-to-video editing.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms Wave: Warping ddim inversion features for zero-shot text-to-video editing

Reference 22

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Observation 1b887b31-ddfa-4e6f-aeb3-28e5dc953086 · outbound

This paper cites CHip: Cross-modal hierarchical direct preference optimization for multimodal LLMs.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms CHip: Cross-modal hierarchical direct preference optimization for multimodal LLMs

Reference 23

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Observation c27eed50-92be-4e50-b66e-8eb68de4b65c · outbound

This paper cites Clustering and Ranking: Diversity-preserved Instruction Selection through Expert-aligned Quality Estimation.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms Clustering and Ranking: Diversity-preserved Instruction Selection through Expert-aligned Quality Estimation

Reference 24

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Observation 1907ae4c-5fcf-4834-bc96-4d379bee0586 · outbound

This paper cites Task-adaptive pretrained lan- guage models via clustered-importance sampling.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms Task-adaptive pretrained lan- guage models via clustered-importance sampling

Reference 25

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Observation e18c4541-ce06-4bb9-9a66-fd6182f8911b · outbound

This paper cites A Survey on LLM-as-a-Judge.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms A Survey on LLM-as-a-Judge

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Observation de89ac9a-98af-4c20-8b7d-a536d11cedc4 · outbound

This paper cites Detecting and preventing hallucinations in large vision language models.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms Detecting and preventing hallucinations in large vision language models

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Resolution: unresolved; no resolver link, observed 2026-08-05T20:17:45.850679Z

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Observation 5c5c933a-c49c-4ec7-b88b-ea46b8f5b030 · outbound

This paper cites Long Context Tuning for Video Generation.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms Long Context Tuning for Video Generation

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-05T20:17:45.932208Z

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Observation 708b2311-88eb-4360-afb9-167bd54c7a0b · outbound

This paper cites Denoising diffusion probabilistic models.Advances in neural information processing systems, 33:6840–6851, 2020.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms Denoising diffusion probabilistic models.Advances in neural information processing systems, 33:6840–6851, 2020

Reference 29

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This paper cites Animate anyone: Consistent and controllable image-to-video synthesis for character animation.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms Animate anyone: Consistent and controllable image-to-video synthesis for character animation

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Observation 0fde41f4-4c7a-4303-82c6-f3da424f2f48 · outbound

This paper cites VistaDPO: Video Hierarchical Spatial-Temporal Direct Preference Optimization for Large Video Models.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms VistaDPO: Video Hierarchical Spatial-Temporal Direct Preference Optimization for Large Video Models

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This paper cites A survey on hallucination in large language models: Principles, taxonomy, challenges, and open questions.ACM Transactions on Information Systems, 43(2):1–55, 2025.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms A survey on hallucination in large language models: Principles, taxonomy, challenges, and open questions.ACM Transactions on Information Systems, 43(2):1–55, 2025

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This paper cites ConceptMaster: Multi-Concept Video Customization on Diffusion Transformer Models Without Test-Time Tuning.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms ConceptMaster: Multi-Concept Video Customization on Diffusion Transformer Models Without Test-Time Tuning

Reference 33

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From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms VBench: Comprehensive benchmark suite for video generative models

Reference 34

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This paper cites Camels in a Changing Climate: Enhancing LM Adaptation with Tulu 2.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms Camels in a Changing Climate: Enhancing LM Adaptation with Tulu 2

Reference 35

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Observation bf6dc059-d33d-4059-be70-d8e793db1210 · outbound

This paper cites HuViDPO:Enhancing Video Generation through Direct Preference Optimization for Human-Centric Alignment.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms HuViDPO:Enhancing Video Generation through Direct Preference Optimization for Human-Centric Alignment

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Resolution: verified exact; local_arxiv, observed 2026-08-05T20:17:55.255982Z

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Observation b1d79ba2-b9e6-4236-9e7d-a16373d5577f · 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, 2024.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms Miradata: A large-scale video dataset with long durations and structured captions.Advances in Neural Information Processing Systems, 37:48955–48970, 2024

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Observation f662d494-15a4-4616-a087-c99f3dec94d5 · outbound

This paper cites How Far is Video Generation from World Model: A Physical Law Perspective.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms How Far is Video Generation from World Model: A Physical Law Perspective

Reference 38

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Observation be4a6946-7f71-4f4f-849a-ad213ad449d5 · outbound

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

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms HunyuanVideo: A Systematic Framework For Large Video Generative Models

Reference 39

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This paper cites Differentiable physics simulation of dynamics- augmented neural objects.IEEE Robotics and Automation Letters, 8(5):2780–2787, 2023.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms Differentiable physics simulation of dynamics- augmented neural objects.IEEE Robotics and Automation Letters, 8(5):2780–2787, 2023

Reference 40

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This paper cites PISA Experiments: Exploring Physics Post-Training for Video Diffusion Models by Watching Stuff Drop.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms PISA Experiments: Exploring Physics Post-Training for Video Diffusion Models by Watching Stuff Drop

Reference 41

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Observation e8fcdfc0-7560-45a6-a002-a4381ebaf0ef · outbound

This paper cites WorldModelBench: Judging Video Generation Models As World Models.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms WorldModelBench: Judging Video Generation Models As World Models

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Observation 86cdc098-fe62-4ba9-8aaa-742e796cf2a4 · outbound

This paper cites MagicID: Hybrid Preference Optimization for ID-Consistent and Dynamic-Preserved Video Customization.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms MagicID: Hybrid Preference Optimization for ID-Consistent and Dynamic-Preserved Video Customization

Reference 43

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Observation c3506c99-36cd-4a6d-8906-0a61264f44f2 · outbound

This paper cites Science-t2i: Addressing scientific illusions in image synthesis.arXiv preprint arXiv:2504.13129, 2025.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms Science-t2i: Addressing scientific illusions in image synthesis.arXiv preprint arXiv:2504.13129, 2025

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Observation 0b869c00-2632-44ba-8032-938821e53c52 · outbound

This paper cites From Quantity to Quality: Boosting LLM Performance with Self-Guided Data Selection for Instruction Tuning.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms From Quantity to Quality: Boosting LLM Performance with Self-Guided Data Selection for Instruction Tuning

Reference 45

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Observation ee975cbd-0d2b-4ad3-8d80-03fb9d4da2ea · outbound

This paper cites Selective reflection-tuning: Student-selected data recycling for llm instruction-tuning.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms Selective reflection-tuning: Student-selected data recycling for llm instruction-tuning

Reference 46

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This paper cites Superfiltering: Weak-to-Strong Data Filtering for Fast Instruction-Tuning.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms Superfiltering: Weak-to-Strong Data Filtering for Fast Instruction-Tuning

Reference 47

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From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms Open-Sora Plan: Open-Source Large Video Generation Model

Reference 48

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Observation f00f2c34-dbcf-4841-a583-a921c51bbf66 · outbound

This paper cites Yu, and Meng Cao.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms Yu, and Meng Cao

Reference 49

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Observation 6d76ab5d-7ccc-4927-a6bb-d166e3e5fe02 · outbound

This paper cites AlignGuard: Scalable Safety Alignment for Text-to-Image Generation.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms AlignGuard: Scalable Safety Alignment for Text-to-Image Generation

Reference 50

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This paper cites VideoDPO: Omni-Preference Alignment for Video Diffusion Generation.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms VideoDPO: Omni-Preference Alignment for Video Diffusion Generation

Reference 51

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Observation 80273f93-d82f-40ac-9351-974ebc621e51 · outbound

This paper cites Physgen: Rigid-body physics-grounded image-to-video generation.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms Physgen: Rigid-body physics-grounded image-to-video generation

Reference 52

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Observation 93e26cd5-b055-426a-8100-f745dfbc245e · outbound

This paper cites What makes good data for alignment? a comprehensive study of automatic data selection in instruction tuning.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms What makes good data for alignment? a comprehensive study of automatic data selection in instruction tuning

Reference 53

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Observation f96e0489-fcd5-4d9a-960a-730ce4224b75 · outbound

This paper cites Towards World Simulator: Crafting Physical Commonsense-Based Benchmark for Video Generation.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms Towards World Simulator: Crafting Physical Commonsense-Based Benchmark for Video Generation

Reference 54

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Unavailable: canonical work link unavailable.

Observation 5813ed32-d29d-42fb-83f0-fcf99eedfabb · outbound

This paper cites Motioncraft: Physics-based zero-shot video generation.Advances in Neural Information Processing Systems, 37:123155–123181, 2024.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms Motioncraft: Physics-based zero-shot video generation.Advances in Neural Information Processing Systems, 37:123155–123181, 2024

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-05T20:17:48.456302Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0d5b9814-d809-44d1-8bdc-76d38084b9ad · outbound

This paper cites Do generative video models understand physical principles?.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms Do generative video models understand physical principles?

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-05T20:17:48.539063Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 349d422a-ff0a-4f1c-8634-63631c5f4916 · outbound

This paper cites OpenVid-1M: A Large-Scale High-Quality Dataset for Text-to-video Generation.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms OpenVid-1M: A Large-Scale High-Quality Dataset for Text-to-video Generation

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-05T20:17:48.618160Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f60c4bd0-484a-4d05-bd2d-919f83304430 · outbound

This paper cites Training language models to follow instructions with human feedback.Advances in neural information processing systems, 35:27730–27744, 2022.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms Training language models to follow instructions with human feedback.Advances in neural information processing systems, 35:27730–27744, 2022

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-05T20:17:48.703193Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 30d705c9-330d-4a31-b414-bfa5a7204743 · outbound

This paper cites G-DIG: Towards Gradient-based Diverse and High-quality Instruction Data Selection for Machine Translation.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms G-DIG: Towards Gradient-based Diverse and High-quality Instruction Data Selection for Machine Translation

Reference 59

Resolution: verified exact; local_arxiv, observed 2026-08-05T20:17:54.676371Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 2c9a8fed-01cd-4f95-aadd-a4f6ae5c877c · outbound

This paper cites FreeNoise: Tuning-Free Longer Video Diffusion via Noise Rescheduling.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms FreeNoise: Tuning-Free Longer Video Diffusion via Noise Rescheduling

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-05T20:17:48.936251Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b12dc097-7349-441f-a413-672f07ab1fe8 · outbound

This paper cites Direct preference optimization: Your language model is secretly a reward model.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms Direct preference optimization: Your language model is secretly a reward model

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-05T20:17:49.026865Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 620105b7-d05f-475b-8533-7a69d34d81a2 · outbound

This paper cites High-resolution image synthesis with latent diffusion models.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms High-resolution image synthesis with latent diffusion models

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-05T20:17:49.176682Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cdd15dc3-6f42-452c-8198-0ed458e584f2 · outbound

This paper cites Towards nsfw-free text-to-image generation via safety-constraint direct preference optimization.arXiv preprint arXiv:2504.14290, 2025.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms Towards nsfw-free text-to-image generation via safety-constraint direct preference optimization.arXiv preprint arXiv:2504.14290, 2025

Reference 63

Resolution: verified exact; raw_fallback, observed 2026-08-05T20:17:54.464113Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 8cfe1255-ea62-4d71-9c79-71a691a2bd3f · outbound

This paper cites Seaweed-7B: Cost-Effective Training of Video Generation Foundation Model.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms Seaweed-7B: Cost-Effective Training of Video Generation Foundation Model

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-05T20:17:49.372195Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c05f59d3-75cf-4e78-a1a6-7d003d01c488 · outbound

This paper cites Finephys: Fine-grained human action generation by explicitly incorporating physical laws for effective skeletal guidance.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms Finephys: Fine-grained human action generation by explicitly incorporating physical laws for effective skeletal guidance

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-05T20:17:49.549878Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e9d0113d-629e-4ba2-9694-35640b87643f · outbound

This paper cites Deep unsuper- vised learning using nonequilibrium thermodynamics.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms Deep unsuper- vised learning using nonequilibrium thermodynamics

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-05T20:17:49.645106Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9881760d-010e-4da5-8489-b24af8b90d60 · outbound

This paper cites Conifer: Improving Complex Constrained Instruction-Following Ability of Large Language Models.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms Conifer: Improving Complex Constrained Instruction-Following Ability of Large Language Models

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-05T20:17:49.708519Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dab43196-6139-4898-b7ae-8663814d0afd · outbound

This paper cites Dsv: Exploiting dynamic sparsity to accelerate large-scale video dit training.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms Dsv: Exploiting dynamic sparsity to accelerate large-scale video dit training

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-05T20:17:49.812237Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8effc63e-8341-428e-9ad0-18b24b247692 · outbound

This paper cites Stanford alpaca: An instruction-following llama model, 2023.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms Stanford alpaca: An instruction-following llama model, 2023

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-05T20:17:49.904906Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 82239b99-506f-45bd-a5ed-a08e2decd835 · outbound

This paper cites D4: Improving llm pretraining via document de-duplication and diversification.Advances in Neural Information Processing Systems, 36:53983–53995, 2023.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms D4: Improving llm pretraining via document de-duplication and diversification.Advances in Neural Information Processing Systems, 36:53983–53995, 2023

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:17:57.031220Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 46ee9ada-4f4c-478f-ad59-6c04a9d48856 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms LLaMA: Open and Efficient Foundation Language Models

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-05T20:17:50.169654Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 10c3cce6-9e60-43d7-a8bb-273de30f1dd2 · outbound

This paper cites Diffusion model alignment using direct preference optimization.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms Diffusion model alignment using direct preference optimization

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-05T20:17:50.262878Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8ad70bc7-4a55-4c7d-acd7-641b18240ee6 · outbound

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

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms Wan: Open and Advanced Large-Scale Video Generative Models

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-05T20:17:50.387681Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2e1f0604-b540-4cfd-9f89-63e9f451c43c · outbound

This paper cites A Survey on Data Selection for LLM Instruction Tuning.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms A Survey on Data Selection for LLM Instruction Tuning

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-05T20:17:50.495923Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d502aa60-fa5f-4c05-ab50-0870b8a677e5 · outbound

This paper cites WISA: World Simulator Assistant for Physics-Aware Text-to-Video Generation.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms WISA: World Simulator Assistant for Physics-Aware Text-to-Video Generation

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-05T20:17:50.611919Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f1fe35c4-46c6-4983-9916-c3608a9d0417 · outbound

This paper cites InternVid: A Large-scale Video-Text Dataset for Multimodal Understanding and Generation.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms InternVid: A Large-scale Video-Text Dataset for Multimodal Understanding and Generation

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-05T20:17:50.734115Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dbea077a-10ee-4b46-becd-5e827b802889 · outbound

This paper cites Self-Instruct: Aligning Language Models with Self-Generated Instructions.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms Self-Instruct: Aligning Language Models with Self-Generated Instructions

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-05T20:17:50.859370Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cd0f3bf7-0ba7-490d-b7e5-61dc42391848 · outbound

This paper cites LightGen: Efficient Image Generation through Knowledge Distillation and Direct Preference Optimization.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms LightGen: Efficient Image Generation through Knowledge Distillation and Direct Preference Optimization

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-05T20:17:50.983947Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 917063ba-4949-4e80-8efd-5d46db9f6022 · outbound

This paper cites DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal Understanding.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal Understanding

Reference 79

Resolution: unresolved; no resolver link, observed 2026-08-05T20:17:51.151628Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 890410cd-874c-4095-b0c1-31a1c0b115ce · outbound

This paper cites LESS: Selecting influential data for targeted instruction tuning.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms LESS: Selecting influential data for targeted instruction tuning

Reference 80

Resolution: unresolved; no resolver link, observed 2026-08-05T20:17:51.305027Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 18f09d67-c54e-4cde-8ed1-c1c32bb5d014 · outbound

This paper cites Data selection for language models via importance resampling.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms Data selection for language models via importance resampling

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:17:56.863201Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c8ced76b-9c1b-42fb-ae5b-42296c8c69e7 · outbound

This paper cites Tooncrafter: Generative cartoon interpolation.ACM Transactions on Graphics (TOG), 43(6):1–11, 2024.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms Tooncrafter: Generative cartoon interpolation.ACM Transactions on Graphics (TOG), 43(6):1–11, 2024

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:17:56.748405Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 9dfd53d8-d876-4db8-9fc7-2163ac26bae5 · outbound

This paper cites Make-your-video: Customized video generation using textual and structural guidance.IEEE Transactions on Visualization and Computer Graphics, 2024.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms Make-your-video: Customized video generation using textual and structural guidance.IEEE Transactions on Visualization and Computer Graphics, 2024

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:17:56.627630Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation eedcd5ff-7769-4b7b-ac2b-449ef73ef391 · outbound

This paper cites WizardLM: Empowering large pre-trained language models to follow complex instructions.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms WizardLM: Empowering large pre-trained language models to follow complex instructions

Reference 84

Resolution: unresolved; no resolver link, observed 2026-08-05T20:17:51.699517Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 35ff23cb-f93f-4779-bbd7-4591624ec733 · outbound

This paper cites PhyT2V: LLM-Guided Iterative Self-Refinement for Physics-Grounded Text-to-Video Generation.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms PhyT2V: LLM-Guided Iterative Self-Refinement for Physics-Grounded Text-to-Video Generation

Reference 85

Resolution: verified exact; local_arxiv, observed 2026-08-05T20:17:53.995131Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c53a2ac9-a94f-4f48-808d-5b293594b69f · outbound

This paper cites Qwen2.5 Technical Report.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms Qwen2.5 Technical Report

Reference 86

Resolution: unresolved; no resolver link, observed 2026-08-05T20:17:51.809671Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5bef51d8-dbe6-4c59-81ff-b323adc40ab1 · outbound

This paper cites Rethinking Video Tokenization: A Conditioned Diffusion-based Approach.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms Rethinking Video Tokenization: A Conditioned Diffusion-based Approach

Reference 87

Resolution: unresolved; no resolver link, observed 2026-08-05T20:17:51.896432Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation affe0794-99d4-40b2-8b2c-e2e67a3c2a3b · outbound

This paper cites Vlipp: Towards physically plausible video generation with vision and language informed physical prior.arXiv e-prints, pages arXiv–2503, 2025.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms Vlipp: Towards physically plausible video generation with vision and language informed physical prior.arXiv e-prints, pages arXiv–2503, 2025

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:17:56.505600Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 9d622c6a-a7a3-4cb7-b6ad-5ae69bff8dc8 · outbound

This paper cites Decoding Data Quality via Synthetic Corruptions: Embedding-guided Pruning of Code Data.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms Decoding Data Quality via Synthetic Corruptions: Embedding-guided Pruning of Code Data

Reference 89

Resolution: verified exact; local_arxiv, observed 2026-08-05T20:17:53.787634Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 1d6d6bd8-7ba2-4cff-8e2b-e97c373ca8db · outbound

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

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer

Reference 90

Resolution: unresolved; no resolver link, observed 2026-08-05T20:17:52.141243Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d8bed148-e95a-42ed-8a85-1253f980db17 · outbound

This paper cites LIMO: Less is More for Reasoning.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms LIMO: Less is More for Reasoning

Reference 91

Resolution: unresolved; no resolver link, observed 2026-08-05T20:17:52.215847Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 41f7937a-4249-455d-99b3-b020ae6c1359 · outbound

This paper cites Gamefactory: Creating new games with generative interactive videos.arXiv preprint arXiv:2501.08325, 2025.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms Gamefactory: Creating new games with generative interactive videos.arXiv preprint arXiv:2501.08325, 2025

Reference 92

Resolution: unresolved; no resolver link, observed 2026-08-05T20:17:52.310879Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cf987ee9-698f-44d0-8686-fa84726c50ef · outbound

This paper cites Magictime: Time-lapse video generation models as metamorphic simulators.IEEE Transactions on Pattern Analysis and Machine Intelligence, 2025.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms Magictime: Time-lapse video generation models as metamorphic simulators.IEEE Transactions on Pattern Analysis and Machine Intelligence, 2025

Reference 93

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:17:56.404541Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 93f0668e-d3bc-4cc7-a5a0-777b3b9b1097 · outbound

This paper cites Onlinevpo: Align video diffusion model with online video-centric preference optimization.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms Onlinevpo: Align video diffusion model with online video-centric preference optimization

Reference 94

Resolution: unresolved; no resolver link, observed 2026-08-05T20:17:52.464640Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8bd3350f-fc28-4e41-9798-d40ccac9c88f · outbound

This paper cites TAGCOS: Task-agnostic Gradient Clustered Coreset Selection for Instruction Tuning Data.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms TAGCOS: Task-agnostic Gradient Clustered Coreset Selection for Instruction Tuning Data

Reference 95

Resolution: unresolved; no resolver link, observed 2026-08-05T20:17:52.555346Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 79dd796a-7f00-4d8e-a505-002bb0da77eb · outbound

This paper cites Packing input frame contexts in next-frame prediction models for video generation.arXiv preprint arXiv:2504.12626, 2025.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms Packing input frame contexts in next-frame prediction models for video generation.arXiv preprint arXiv:2504.12626, 2025

Reference 96

Resolution: unresolved; no resolver link, observed 2026-08-05T20:17:52.641103Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dfb00868-04e2-46a7-8787-f80b5d8376a3 · outbound

This paper cites Fast Video Generation with Sliding Tile Attention.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms Fast Video Generation with Sliding Tile Attention

Reference 97

Resolution: unresolved; no resolver link, observed 2026-08-05T20:17:52.715883Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 859bc576-4e8a-4a9a-9a69-8cbd359a2034 · outbound

This paper cites Synthetic Video Enhances Physical Fidelity in Video Synthesis.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms Synthetic Video Enhances Physical Fidelity in Video Synthesis

Reference 98

Resolution: unresolved; no resolver link, observed 2026-08-05T20:17:52.808648Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e95ee606-f44b-4a30-a2b1-6cd4c3301e30 · outbound

This paper cites Open-Sora: Democratizing Efficient Video Production for All.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms Open-Sora: Democratizing Efficient Video Production for All

Reference 99

Resolution: unresolved; no resolver link, observed 2026-08-05T20:17:52.900654Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 221837a9-e0bc-47f2-a343-a1b7931a73da · outbound

This paper cites Deco: Decoupled human-centered diffusion video editing with motion consistency.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms Deco: Decoupled human-centered diffusion video editing with motion consistency

Reference 100

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:17:56.266427Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation dac611b5-14cc-47cd-9551-f96d81d42e00 · outbound

This paper cites Lima: Less is more for alignment.Advances in Neural Information Processing Systems, 36:55006–55021, 2023.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms Lima: Less is more for alignment.Advances in Neural Information Processing Systems, 36:55006–55021, 2023

Reference 101

Resolution: unresolved; no resolver link, observed 2026-08-05T20:17:52.998922Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Outbound references

Pith citing papers