AGI-Elo: How Far Are We From Mastering A Task? | Paper Citation Record

Observation 219f380e-b095-4d2e-96f0-cda95f2ac0dd · outbound

This paper cites GPT-4 Technical Report.

AGI-Elo: How Far Are We From Mastering A Task? GPT-4 Technical Report

Reference 1

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Observation f0cb1279-665e-4f42-b560-ed5da4c35a39 · outbound

This paper cites Claude 3.7 sonnet and claude code.

AGI-Elo: How Far Are We From Mastering A Task? Claude 3.7 sonnet and claude code

Reference 2

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Observation f6aa4140-1951-4391-bb95-252358ca3b22 · outbound

This paper cites Unsu- pervised label noise modeling and loss correction.

AGI-Elo: How Far Are We From Mastering A Task? Unsu- pervised label noise modeling and loss correction

Reference 3

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Observation e8de3d15-5726-432c-b946-f4a2eb952b4d · outbound

This paper cites Curriculum learning.

AGI-Elo: How Far Are We From Mastering A Task? Curriculum learning

Reference 4

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Observation 66ca1ee0-7b2c-4177-a8dd-9c4056846c94 · outbound

This paper cites Elo uncovered: Robustness and best practices in language model evaluation.

AGI-Elo: How Far Are We From Mastering A Task? Elo uncovered: Robustness and best practices in language model evaluation

Reference 5

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This paper cites Lang, Sourabh V ora, Venice Erin Liong, Qiang Xu, Anush Krishnan, Yu Pan, Giancarlo Baldan, and Oscar Beijbom.

AGI-Elo: How Far Are We From Mastering A Task? Lang, Sourabh V ora, Venice Erin Liong, Qiang Xu, Anush Krishnan, Yu Pan, Giancarlo Baldan, and Oscar Beijbom

Reference 6

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Observation 56bd01c0-b9d4-4903-8635-915019f99200 · outbound

This paper cites Active bias: Training more accurate neural networks by emphasizing high variance samples.

AGI-Elo: How Far Are We From Mastering A Task? Active bias: Training more accurate neural networks by emphasizing high variance samples

Reference 7

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Observation 125dc179-432f-4a64-a352-526aa5c2c413 · outbound

This paper cites MMDetection: Open MMLab Detection Toolbox and Benchmark.

AGI-Elo: How Far Are We From Mastering A Task? MMDetection: Open MMLab Detection Toolbox and Benchmark

Reference 8

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Observation 04f9cbfa-3968-437f-849d-a4275abb6a83 · outbound

This paper cites Chatbot arena: An open platform for evaluating llms by human preference.

AGI-Elo: How Far Are We From Mastering A Task? Chatbot arena: An open platform for evaluating llms by human preference

Reference 9

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Observation ba4f5cfd-4abf-482a-9eb9-c0d9ff076911 · outbound

This paper cites Transfuser: Imitation with transformer-based sensor fusion for autonomous driving.

AGI-Elo: How Far Are We From Mastering A Task? Transfuser: Imitation with transformer-based sensor fusion for autonomous driving

Reference 10

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This paper cites Openscene: The largest up-to-date 3d occupancy prediction bench- mark in autonomous driving, 2023.

AGI-Elo: How Far Are We From Mastering A Task? Openscene: The largest up-to-date 3d occupancy prediction bench- mark in autonomous driving, 2023

Reference 11

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Observation 5e20415d-8a78-46ad-bdf1-6a795eac94d1 · outbound

This paper cites Navsim: Data-driven non-reactive autonomous vehicle simulation and benchmarking.

AGI-Elo: How Far Are We From Mastering A Task? Navsim: Data-driven non-reactive autonomous vehicle simulation and benchmarking

Reference 12

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Observation 5e42ca1d-99c7-43ca-82ee-fb8410b9678a · outbound

This paper cites Imagenet: A large-scale hierarchical image database.

AGI-Elo: How Far Are We From Mastering A Task? Imagenet: A large-scale hierarchical image database

Reference 13

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Observation d61c5ce5-bec3-4899-874e-338ff3b4222a · outbound

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

AGI-Elo: How Far Are We From Mastering A Task? An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 14

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Observation f2704f3f-ee69-4932-935e-c7ee4463b804 · outbound

This paper cites The proposed uscf rating system, its development, theory, and applications.

AGI-Elo: How Far Are We From Mastering A Task? The proposed uscf rating system, its development, theory, and applications

Reference 15

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Observation d571e1da-d60d-49a8-93a5-06fccaff8a4d · outbound

This paper cites Understanding dataset difficulty with v-usable information.

AGI-Elo: How Far Are We From Mastering A Task? Understanding dataset difficulty with v-usable information

Reference 16

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Observation 47067c5c-c5b8-4399-9871-213bea386e70 · outbound

This paper cites Large scale interactive motion forecasting for autonomous driving: The waymo open motion dataset.

AGI-Elo: How Far Are We From Mastering A Task? Large scale interactive motion forecasting for autonomous driving: The waymo open motion dataset

Reference 17

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Observation a0f0afe8-bb94-46c1-a329-f2c189ba254f · outbound

This paper cites Are we ready for autonomous driving? the kitti vision benchmark suite.

AGI-Elo: How Far Are We From Mastering A Task? Are we ready for autonomous driving? the kitti vision benchmark suite

Reference 18

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Observation f723a872-bb9e-4367-8ddb-cc07228a2289 · outbound

This paper cites Glickman.

AGI-Elo: How Far Are We From Mastering A Task? Glickman

Reference 19

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Observation fa2aab54-a358-46e5-bf9c-119a21e29afd · outbound

This paper cites Gemini 2.5: Our most intelligent ai model.

AGI-Elo: How Far Are We From Mastering A Task? Gemini 2.5: Our most intelligent ai model

Reference 20

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Observation 8b0c663a-b10e-4e77-be5a-069a5d47e391 · outbound

This paper cites The Llama 3 Herd of Models.

AGI-Elo: How Far Are We From Mastering A Task? The Llama 3 Herd of Models

Reference 21

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Observation 1c145112-8fd4-424e-96d0-f0d3384ba654 · outbound

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

AGI-Elo: How Far Are We From Mastering A Task? DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 22

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Observation 4fc9456d-94b6-4436-9e89-690b483e5c3d · outbound

This paper cites DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence.

AGI-Elo: How Far Are We From Mastering A Task? DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence

Reference 23

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Observation 61d43fa0-22b7-4105-981e-82beb62279bc · outbound

This paper cites an unresolved cited work.

AGI-Elo: How Far Are We From Mastering A Task? Unresolved cited work

Reference 24

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Observation 59399dd2-8b66-4c9f-8e23-2ae8d79a9cdb · outbound

This paper cites Tan et al.

AGI-Elo: How Far Are We From Mastering A Task? Tan et al

Reference 25

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Observation 0ce4cdd9-55c2-4b76-98fd-961af9f2ded1 · outbound

This paper cites Co-teaching: Robust training of deep neural networks with extremely noisy labels.

AGI-Elo: How Far Are We From Mastering A Task? Co-teaching: Robust training of deep neural networks with extremely noisy labels

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:31:23.521908Z

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Observation 404c2fb1-a86c-4a51-884d-242a00de382d · outbound

This paper cites Mask R-CNN.

AGI-Elo: How Far Are We From Mastering A Task? Mask R-CNN

Reference 27

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Observation ff3496f8-2210-43bb-96e4-80b3a30e1561 · outbound

This paper cites Deep residual learning for image recognition.

AGI-Elo: How Far Are We From Mastering A Task? Deep residual learning for image recognition

Reference 28

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Observation 4fc71b59-042d-46b3-9910-ad8ab1abe056 · outbound

This paper cites Measuring Massive Multitask Language Understanding.

AGI-Elo: How Far Are We From Mastering A Task? Measuring Massive Multitask Language Understanding

Reference 29

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Observation 9c35bbdb-3d25-4578-a1c7-54a3a5e16373 · outbound

This paper cites Trueskill ™: a bayesian skill rating system.

AGI-Elo: How Far Are We From Mastering A Task? Trueskill ™: a bayesian skill rating system

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:31:23.502558Z

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Observation 361017f4-313f-4b11-a4d2-87859fec97ae · outbound

This paper cites Learning whodunnit: Classification of event participants in news articles.

AGI-Elo: How Far Are We From Mastering A Task? Learning whodunnit: Classification of event participants in news articles

Reference 31

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Observation 1e567de8-5f99-4de3-952c-1035a708b9d9 · outbound

This paper cites Densely connected convolutional networks.

AGI-Elo: How Far Are We From Mastering A Task? Densely connected convolutional networks

Reference 32

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Observation 650f6075-c6b5-4f33-b43f-2df451d0f807 · outbound

This paper cites Qwen2.5-Coder Technical Report.

AGI-Elo: How Far Are We From Mastering A Task? Qwen2.5-Coder Technical Report

Reference 33

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This paper cites GPT-4o System Card.

AGI-Elo: How Far Are We From Mastering A Task? GPT-4o System Card

Reference 34

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This paper cites SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size.

AGI-Elo: How Far Are We From Mastering A Task? SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size

Reference 35

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Observation 70d68257-b75b-4670-a1e1-a485c9cff832 · outbound

This paper cites OpenAI o1 System Card.

AGI-Elo: How Far Are We From Mastering A Task? OpenAI o1 System Card

Reference 36

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Observation ed03f8c0-1bc8-4ffe-8523-04ae88fcd32f · outbound

This paper cites LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code.

AGI-Elo: How Far Are We From Mastering A Task? LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code

Reference 37

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Observation f3526b71-a9cb-4eed-a33b-4c4809777da7 · outbound

This paper cites Ultralytics yolov8, 2023.

AGI-Elo: How Far Are We From Mastering A Task? Ultralytics yolov8, 2023

Reference 38

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Observation 43a56c9a-2b70-4fe4-94ad-180f10e1ac6a · outbound

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AGI-Elo: How Far Are We From Mastering A Task? Ultralytics yolo11, 2024

Reference 39

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AGI-Elo: How Far Are We From Mastering A Task? ultralytics/yolov5: v3

Reference 40

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Observation 420e2a26-e92e-47a1-a668-eef6cb65b2ad · outbound

This paper cites Learning multiple layers of features from tiny images.

AGI-Elo: How Far Are We From Mastering A Task? Learning multiple layers of features from tiny images

Reference 41

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This paper cites an unresolved cited work.

AGI-Elo: How Far Are We From Mastering A Task? Unresolved cited work

Reference 42

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

Observation f2494901-9490-4903-b6f5-25c993a917a7 · outbound

This paper cites Datasets: A Community Library for Natural Language Processing.

AGI-Elo: How Far Are We From Mastering A Task? Datasets: A Community Library for Natural Language Processing

Reference 43

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Observation eaef0ae8-5a34-48ee-9dee-f4f025b92555 · outbound

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AGI-Elo: How Far Are We From Mastering A Task? Quanti- fying ai psychology: A psychometrics benchmark for large language models

Reference 44

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Observation 9bdf17d0-e0ae-4b16-b9f0-8cbb3ad62763 · outbound

This paper cites DiffusionDrive: Truncated Diffusion Model for End-to-End Autonomous Driving.

AGI-Elo: How Far Are We From Mastering A Task? DiffusionDrive: Truncated Diffusion Model for End-to-End Autonomous Driving

Reference 45

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This paper cites Eda: Evolving and distinct anchors for multimodal motion prediction.

AGI-Elo: How Far Are We From Mastering A Task? Eda: Evolving and distinct anchors for multimodal motion prediction

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:31:23.433031Z

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Observation e4712c81-0009-4a3e-8a3e-83f3826cc27e · outbound

This paper cites Focal Loss for Dense Object Detection.

AGI-Elo: How Far Are We From Mastering A Task? Focal Loss for Dense Object Detection

Reference 47

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Observation a1ff8ffb-f4af-4e60-a9bd-22021cea5981 · outbound

This paper cites Microsoft coco: Common objects in context.

AGI-Elo: How Far Are We From Mastering A Task? Microsoft coco: Common objects in context

Reference 48

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Observation c5b16333-875f-489a-aabf-74606b52c057 · outbound

This paper cites DeepSeek-V3 Technical Report.

AGI-Elo: How Far Are We From Mastering A Task? DeepSeek-V3 Technical Report

Reference 49

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Observation 4c02db0d-b6c2-402a-96c8-77e597cde9fb · outbound

This paper cites Reasoning multi-agent behavioral topology for interactive autonomous driving.

AGI-Elo: How Far Are We From Mastering A Task? Reasoning multi-agent behavioral topology for interactive autonomous driving

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:31:23.413295Z

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

Observation 35d0009b-9093-42be-8dc6-44b653ace8ff · outbound

This paper cites Ssd: Single shot multibox detector.

AGI-Elo: How Far Are We From Mastering A Task? Ssd: Single shot multibox detector

Reference 51

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Observation 8acf187a-249f-4070-860e-40d0085e9797 · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted windows.

AGI-Elo: How Far Are We From Mastering A Task? Swin transformer: Hierarchical vision transformer using shifted windows

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-15T20:31:22.385561Z

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Observation 510a553f-6f21-49cc-bde8-b9281a9c09d8 · outbound

This paper cites A convnet for the 2020s.

AGI-Elo: How Far Are We From Mastering A Task? A convnet for the 2020s

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-15T20:31:22.389997Z

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Observation b7a25970-5d26-4207-aee6-6fd28ea94224 · outbound

This paper cites Statistical theories of mental test scores.

AGI-Elo: How Far Are We From Mastering A Task? Statistical theories of mental test scores

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-15T20:31:22.393765Z

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Observation 4b3f3438-4f4e-4fbb-8926-3b923986b840 · outbound

This paper cites StarCoder 2 and The Stack v2: The Next Generation.

AGI-Elo: How Far Are We From Mastering A Task? StarCoder 2 and The Stack v2: The Next Generation

Reference 55

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Observation 185c010e-59c9-49cb-a765-e0518d1e2eed · outbound

This paper cites DETRs Beat YOLOs on Real-time Object Detection.

AGI-Elo: How Far Are We From Mastering A Task? DETRs Beat YOLOs on Real-time Object Detection

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-15T20:31:22.403072Z

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Observation 68e80e4e-0ec4-4ab3-8cc7-52569bb61e77 · outbound

This paper cites Shufflenet v2: Practical guidelines for efficient cnn architecture design.

AGI-Elo: How Far Are We From Mastering A Task? Shufflenet v2: Practical guidelines for efficient cnn architecture design

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-15T20:31:22.407122Z

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Observation 10a60841-6f92-4884-80aa-13ef85b807fd · outbound

This paper cites Item response theory in ai: Analysing machine learning classifiers at the instance level.

AGI-Elo: How Far Are We From Mastering A Task? Item response theory in ai: Analysing machine learning classifiers at the instance level

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:31:23.363441Z

Source-reported events for the cited work

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

Observation 05e2123d-1811-44d4-9e53-2303c1a65651 · outbound

This paper cites The llama 4 herd: The beginning of a new era of natively multimodal ai innova- tion.

AGI-Elo: How Far Are We From Mastering A Task? The llama 4 herd: The beginning of a new era of natively multimodal ai innova- tion

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:31:23.351138Z

Source-reported events for the cited work

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

Observation 1b362fe1-dcb0-418b-96d7-daf94e7b2605 · outbound

This paper cites Hardness of Samples Need to be Quantified for a Reliable Evaluation System: Exploring Potential Opportunities with a New Task.

AGI-Elo: How Far Are We From Mastering A Task? Hardness of Samples Need to be Quantified for a Reliable Evaluation System: Exploring Potential Opportunities with a New Task

Reference 60

Resolution: verified exact; local_arxiv, observed 2026-08-15T20:31:22.853255Z

Source-reported events for the cited work

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

Observation 85bbdc71-6c89-41ba-9a33-52f666049856 · outbound

This paper cites Crosslingual Generalization through Multitask Finetuning.

AGI-Elo: How Far Are We From Mastering A Task? Crosslingual Generalization through Multitask Finetuning

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-15T20:31:22.432267Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0992e84b-b4ed-42b8-9368-50b528df9858 · outbound

This paper cites Nanogpt api.

AGI-Elo: How Far Are We From Mastering A Task? Nanogpt api

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:31:23.340236Z

Source-reported events for the cited work

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

Observation 26f54e31-f9da-4119-be76-27941d0c54cd · outbound

This paper cites Openai api.

AGI-Elo: How Far Are We From Mastering A Task? Openai api

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:31:23.328564Z

Source-reported events for the cited work

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

Observation 7b3dc407-6e4c-4b88-aecf-633bdd0efb3c · outbound

This paper cites PyTorch: An Imperative Style, High-Performance Deep Learning Library.

AGI-Elo: How Far Are We From Mastering A Task? PyTorch: An Imperative Style, High-Performance Deep Learning Library

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-15T20:31:22.445327Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e40f5585-7b66-406c-8cfb-a7f40f44210e · outbound

This paper cites Qwq: Reflect deeply on the boundaries of the unknown.

AGI-Elo: How Far Are We From Mastering A Task? Qwq: Reflect deeply on the boundaries of the unknown

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:31:23.317677Z

Source-reported events for the cited work

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

Observation 9b6ab5d8-4cfe-4e3d-b336-667d7bbff9e5 · outbound

This paper cites Design- ing network design spaces.

AGI-Elo: How Far Are We From Mastering A Task? Design- ing network design spaces

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:31:23.305833Z

Source-reported events for the cited work

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

Observation 2f210178-ccef-44ca-8340-f303cec45f4c · outbound

This paper cites YOLOv3: An Incremental Improvement.

AGI-Elo: How Far Are We From Mastering A Task? YOLOv3: An Incremental Improvement

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-15T20:31:22.456631Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e2ca54af-e899-4166-af10-b8ccde374ef4 · outbound

This paper cites Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks.

AGI-Elo: How Far Are We From Mastering A Task? Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-15T20:31:22.460344Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 54776c28-cf65-4250-be54-976fed31942a · outbound

This paper cites Mobilenetv2: Inverted residuals and linear bottlenecks.

AGI-Elo: How Far Are We From Mastering A Task? Mobilenetv2: Inverted residuals and linear bottlenecks

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:31:23.293931Z

Source-reported events for the cited work

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

Observation e7c2f2f9-7442-4571-a82a-efcff6b1ab1c · outbound

This paper cites Learning with bad training data via iterative trimmed loss minimization.

AGI-Elo: How Far Are We From Mastering A Task? Learning with bad training data via iterative trimmed loss minimization

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:31:23.283072Z

Source-reported events for the cited work

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

Observation 91fbf034-0e90-4475-aa42-61b9fd695415 · outbound

This paper cites Motion transformer with global inten- tion localization and local movement refinement.

AGI-Elo: How Far Are We From Mastering A Task? Motion transformer with global inten- tion localization and local movement refinement

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:31:23.271441Z

Source-reported events for the cited work

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

Observation bc92e98e-a57d-4e6a-b12b-73ddde9f7540 · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

AGI-Elo: How Far Are We From Mastering A Task? Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-15T20:31:22.474764Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 506146ab-f514-41a3-b210-d5d84c1df3f9 · outbound

This paper cites less is more.

AGI-Elo: How Far Are We From Mastering A Task? less is more

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:31:23.259329Z

Source-reported events for the cited work

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

Observation 5fd0d61e-4888-4420-b9ac-0eb51d2c84cc · outbound

This paper cites RMP-YOLO: A Robust Motion Predictor for Partially Observable Scenarios even if You Only Look Once.

AGI-Elo: How Far Are We From Mastering A Task? RMP-YOLO: A Robust Motion Predictor for Partially Observable Scenarios even if You Only Look Once

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-15T20:31:22.483130Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8c02adce-d84f-43e4-ab1c-0647989310d4 · outbound

This paper cites an unresolved cited work.

AGI-Elo: How Far Are We From Mastering A Task? Unresolved cited work

Reference 75

Resolution: unresolved; raw_fallback, observed 2026-08-15T20:31:23.248667Z

Source-reported events for the cited work

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

Observation dda650c5-7fd0-4906-968f-674aa80e9aa6 · outbound

This paper cites Impact: Behavioral intention-aware multimodal trajectory prediction with adaptive context trimming.

AGI-Elo: How Far Are We From Mastering A Task? Impact: Behavioral intention-aware multimodal trajectory prediction with adaptive context trimming

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-15T20:31:22.492111Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c5b9316b-d121-47cf-99b8-75d8f565caee · outbound

This paper cites Dataset Cartography: Mapping and Diagnosing Datasets with Training Dynamics.

AGI-Elo: How Far Are We From Mastering A Task? Dataset Cartography: Mapping and Diagnosing Datasets with Training Dynamics

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-15T20:31:22.496189Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9c0dd58f-1697-4986-aff4-64eac69a3e2d · outbound

This paper cites Re- thinking the inception architecture for computer vision.

AGI-Elo: How Far Are We From Mastering A Task? Re- thinking the inception architecture for computer vision

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-15T20:31:22.500647Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 98c256f7-5129-422a-aa0f-03e218d0099a · outbound

This paper cites an unresolved cited work.

AGI-Elo: How Far Are We From Mastering A Task? Unresolved cited work

Reference 79

Resolution: unresolved; raw_fallback, observed 2026-08-15T20:31:23.227724Z

Source-reported events for the cited work

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

Observation d4f37b32-f7e3-4d9d-b8bb-4a5a61140d9f · outbound

This paper cites Gemma 3 Technical Report.

AGI-Elo: How Far Are We From Mastering A Task? Gemma 3 Technical Report

Reference 80

Resolution: unresolved; no resolver link, observed 2026-08-15T20:31:22.507932Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0483093f-ced2-46a5-ad57-0a177742c4a7 · outbound

This paper cites Fcos: Fully convolutional one-stage object detection.

AGI-Elo: How Far Are We From Mastering A Task? Fcos: Fully convolutional one-stage object detection

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:31:23.216108Z

Source-reported events for the cited work

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

Observation faaf98d3-64da-4c8c-8bb7-824307017272 · outbound

This paper cites An empirical study of example forgetting during deep neural network learning.

AGI-Elo: How Far Are We From Mastering A Task? An empirical study of example forgetting during deep neural network learning

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:31:23.203085Z

Source-reported events for the cited work

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

Observation 0f794319-ac0f-45ca-b123-77726357382b · outbound

This paper cites ILDAE: Instance-Level Difficulty Analysis of Evaluation Data.

AGI-Elo: How Far Are We From Mastering A Task? ILDAE: Instance-Level Difficulty Analysis of Evaluation Data

Reference 83

Resolution: verified exact; local_arxiv, observed 2026-08-15T20:31:22.668717Z

Source-reported events for the cited work

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

Observation 49841600-3125-489a-9c68-f203c541e15e · outbound

This paper cites Grandmaster level in starcraft ii using multi-agent reinforcement learning.

AGI-Elo: How Far Are We From Mastering A Task? Grandmaster level in starcraft ii using multi-agent reinforcement learning

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:31:23.190854Z

Source-reported events for the cited work

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

Observation d0573762-30bc-4ec0-b29e-d64d9c4ed5de · outbound

This paper cites State and Parameter Estimation for Natural Gas Pipeline Networks using Transient State Data.

AGI-Elo: How Far Are We From Mastering A Task? State and Parameter Estimation for Natural Gas Pipeline Networks using Transient State Data

Reference 85

Resolution: metadata mismatch; local_arxiv, observed 2026-08-15T20:31:22.651547Z

Source-reported events for the cited work

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

Observation 449890c5-2e70-45ad-941f-28968f1b746d · outbound

This paper cites Towards heterogeneous long-tailed learning: Benchmarking, metrics, and toolbox.

AGI-Elo: How Far Are We From Mastering A Task? Towards heterogeneous long-tailed learning: Benchmarking, metrics, and toolbox

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:31:23.178805Z

Source-reported events for the cited work

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

Observation 963a6481-e052-40c4-872d-0e3bfe12deac · outbound

This paper cites Aggregated residual transformations for deep neural networks.

AGI-Elo: How Far Are We From Mastering A Task? Aggregated residual transformations for deep neural networks

Reference 87

Resolution: unresolved; no resolver link, observed 2026-08-15T20:31:22.534529Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e75d02a0-a59c-4fcf-8e11-1db13ef7e842 · outbound

This paper cites Qwen2.5 Technical Report.

AGI-Elo: How Far Are We From Mastering A Task? Qwen2.5 Technical Report

Reference 88

Resolution: unresolved; no resolver link, observed 2026-08-15T20:31:22.538031Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d59e38ff-aa35-4cc6-81c0-ea11dd86dc0c · outbound

This paper cites DRAMA: An Efficient End-to-end Motion Planner for Autonomous Driving with Mamba.

AGI-Elo: How Far Are We From Mastering A Task? DRAMA: An Efficient End-to-end Motion Planner for Autonomous Driving with Mamba

Reference 89

Resolution: unresolved; no resolver link, observed 2026-08-15T20:31:22.541425Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 971d3587-19dd-419c-8691-f399095e92c6 · outbound

This paper cites ResNeSt: Split-Attention Networks.

AGI-Elo: How Far Are We From Mastering A Task? ResNeSt: Split-Attention Networks

Reference 90

Resolution: unresolved; no resolver link, observed 2026-08-15T20:31:22.547377Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 59a37317-f864-4d40-ad32-ac04204e8745 · outbound

This paper cites DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection.

AGI-Elo: How Far Are We From Mastering A Task? DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection

Reference 91

Resolution: unresolved; no resolver link, observed 2026-08-15T20:31:22.551267Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 26c8dae4-9a57-402b-8180-eff2ccf79aab · outbound

This paper cites Position: AI Evaluation Should Learn from How We Test Humans.

AGI-Elo: How Far Are We From Mastering A Task? Position: AI Evaluation Should Learn from How We Test Humans

Reference 92

Resolution: unresolved; no resolver link, observed 2026-08-15T20:31:22.554944Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Coverage vector

Reference resolution

Outbound references

Pith citing papers