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Misconceptions

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법 전체 데이터셋

하위 태스크: 0
평가표: 1
보존된 평가 기록: 2

Measures whether a model can discern popular misconceptions from the truth.

Example:

        input: The daddy longlegs spider is the most venomous spider in the world.
        choice: T
        choice: F
        answer: F

        input: Karl Benz is correctly credited with the invention of the first modern automobile.
        choice: T
        choice: F
        answer: T

Source: BIG-bench

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/AlexImmer/Laplace

공식 코드

Laplace Redux -- Effortless Bayesian Deep Learning

https://github.com/Algue-Rythme/Pay-attention-to-your-loss

공식 코드

Pay attention to your loss: understanding misconceptions about 1-Lipschitz neural networks

https://github.com/GauthierGidel/Variational-Inequality-GAN

공식 코드

A Variational Inequality Perspective on Generative Adversarial Networks

https://github.com/allenai/HyBayes

공식 코드

Not All Claims are Created Equal: Choosing the Right Statistical Approach to Assess Hypotheses

https://github.com/anupshakya07/attn-scaling

공식 코드

Scalable and Equitable Math Problem Solving Strategy Prediction in Big Educational Data

https://github.com/autonomousvision/nuplan_garage

공식 코드

Parting with Misconceptions about Learning-based Vehicle Motion Planning

https://github.com/autonomousvision/tuplan_garage

공식 코드

Parting with Misconceptions about Learning-based Vehicle Motion Planning

https://github.com/blueghostyi/id-grec

공식 코드

Unveiling Contrastive Learning's Capability of Neighborhood Aggregation for Collaborative Filtering

https://github.com/codogogo/xling-eval

공식 코드

How to (Properly) Evaluate Cross-Lingual Word Embeddings: On Strong Baselines, Comparative Analyses, and Some Misconceptions

https://github.com/dmorrill10/hr_edl_experiments

공식 코드

Hindsight and Sequential Rationality of Correlated Play

https://github.com/doldd/Paths-and-Ambient-Spaces

공식 코드

Paths and Ambient Spaces in Neural Loss Landscapes

https://github.com/dscig/AIRights_PublicPerception

공식 코드

Collecting the Public Perception of AI and Robot Rights

https://github.com/ejohnson6767/mct_review

공식 코드

Resolving conceptual issues in Modern Coexistence Theory

https://github.com/epfl-ml4ed/answer-forecasting

공식 코드

Student Answer Forecasting: Transformer-Driven Answer Choice Prediction for Language Learning

https://github.com/facebookresearch/alebo

공식 코드

Re-Examining Linear Embeddings for High-Dimensional Bayesian Optimization

https://github.com/facebookresearch/ffcv-ssl

공식 코드

Towards Democratizing Joint-Embedding Self-Supervised Learning

https://github.com/flipz357/metric-csv

공식 코드

A Closer Look at Classification Evaluation Metrics and a Critical Reflection of Common Evaluation Practice

https://github.com/gary-code/peifg

공식 코드

Learning to Correction: Explainable Feedback Generation for Visual Commonsense Reasoning Distractor

https://github.com/gregorbachmann/next-token-failures

공식 코드

The pitfalls of next-token prediction

https://github.com/harryw1248/covid_19_misinformation_weakly_supervised_bwgs

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A Weakly-Supervised Iterative Graph-Based Approach to Retrieve COVID-19 Misinformation Topics

https://github.com/jiesutd/NCRFpp

공식 코드

Design Challenges and Misconceptions in Neural Sequence Labeling

https://github.com/kach/watchat

공식 코드

WatChat: Explaining perplexing programs by debugging mental models

https://github.com/luffycodes/MalAlgoQA-Dataset

공식 코드

MalAlgoQA: Pedagogical Evaluation of Counterfactual Reasoning in Large Language Models and Implications for AI in Education

https://github.com/machine-teaching-group/edm2022_studentsyn

공식 코드

From {Solution Synthesis} to {Student Attempt Synthesis} for Block-Based Visual Programming Tasks

https://github.com/machine-teaching-group/edm2024-llm-student-modeling

공식 코드

Large Language Models for In-Context Student Modeling: Synthesizing Student's Behavior in Visual Programming

https://github.com/mhw32/rubric-sampling-public

공식 코드

Zero Shot Learning for Code Education: Rubric Sampling with Deep Learning Inference

https://github.com/mnoukhov/emergent-compete

공식 코드

Emergent Communication under Competition

https://github.com/nayeon7lee/factualityprompt

공식 코드

Factuality Enhanced Language Models for Open-Ended Text Generation

https://github.com/nicyscaria/AEQG-MCQ-Distractors-Physics

공식 코드

Harnessing Structured Knowledge: A Concept Map-Based Approach for High-Quality Multiple Choice Question Generation with Effective Distractors

https://github.com/octaviaguo/EchoMist

공식 코드

How to Protect Yourself from 5G Radiation? Investigating LLM Responses to Implicit Misinformation

https://github.com/olivia-fsm/p2mcq

공식 코드

Towards Process-Oriented, Modular, and Versatile Question Generation that Meets Educational Needs

https://github.com/purseclab/llm_security_privacy_advice

공식 코드

Can Large Language Models Provide Security & Privacy Advice? Measuring the Ability of LLMs to Refute Misconceptions

https://github.com/rajasekharmekala/query-rephrasing-subtask-cot

공식 코드

EchoPrompt: Instructing the Model to Rephrase Queries for Improved In-context Learning

https://github.com/ronaldiscool/VAETutorial

공식 코드

A Tutorial on VAEs: From Bayes' Rule to Lossless Compression

https://github.com/runame/laplace-redux

공식 코드

Laplace Redux -- Effortless Bayesian Deep Learning

https://github.com/sbudzinskiy/low-rank-big-data

공식 코드

When big data actually are low-rank, or entrywise approximation of certain function-generated matrices

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