Bedste Differentiated Instruction-podcasts (2024)

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151. Ask Me Anything! Part 2: Differentiated Instruction, Difficult Conversations, Work/Life Balance, and More! 44:39

16d ago44:39

44:39

I love celebrating podcast milestones with my listeners so much that I couldn’t celebrate with just one episode! Last week, I hit 150 episodes and decided to answer questions sent to me from listeners. Although I covered a variety of different topics, I received so many questions that I needed to do another episode to answer them all. So, in part 2…

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[QA] UnStar: Unlearning with Self-Taught Anti-Sample Reasoning for LLMs 8:06

2h ago8:06

8:06

This paper introduces UNSTAR, a novel unlearning method for large language models using anti-samples to efficiently and selectively reverse learned associations, enhancing privacy and model modification capabilities. https://arxiv.org/abs//2410.17050 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Po…

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UnStar: Unlearning with Self-Taught Anti-Sample Reasoning for LLMs 16:43

2h ago16:43

16:43

This paper introduces UNSTAR, a novel unlearning method for large language models using anti-samples to efficiently and selectively reverse learned associations, enhancing privacy and model modification capabilities. https://arxiv.org/abs//2410.17050 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Po…

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[QA] Representation Shattering in Transformers: A Synthetic Study with Knowledge Editing 7:48

2h ago7:48

7:48

This paper explores how Knowledge Editing algorithms can unintentionally distort model representations, leading to decreased factual recall and reasoning abilities, a phenomenon termed "representation shattering." https://arxiv.org/abs//2410.17194 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podca…

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Representation Shattering in Transformers: A Synthetic Study with Knowledge Editing 18:06

2h ago18:06

18:06

This paper explores how Knowledge Editing algorithms can unintentionally distort model representations, leading to decreased factual recall and reasoning abilities, a phenomenon termed "representation shattering." https://arxiv.org/abs//2410.17194 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podca…

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[QA] Generative Reward Models 7:10

22h ago7:10

7:10

The paper proposes GenRM, a hybrid approach combining RLHF and RLAIF, improving synthetic preference labels' quality and outperforming existing models in both in-distribution and out-of-distribution tasks. https://arxiv.org/abs//2410.12832 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: htt…

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Generative Reward Models 12:09

22h ago12:09

12:09

The paper proposes GenRM, a hybrid approach combining RLHF and RLAIF, improving synthetic preference labels' quality and outperforming existing models in both in-distribution and out-of-distribution tasks. https://arxiv.org/abs//2410.12832 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: htt…

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153. How to Make Boring Topics More Engaging 27:28

2d ago27:28

27:28

Even though you may love the science discipline you teach, that doesn’t mean that you’re excited to teach every topic, let alone your students enjoying everything you teach. Unfortunately, there are certain topics that are considered boring but still need to be taught! Knowing the topics that are deemed boring for you, how can you turn those around…

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51. 10 Ways to Tackle Work Refusal in the Classroom 12:53

1d ago12:53

12:53

In the latest Teach, Task Box, Inspire episode, Lisa tackles the tough topic of student work refusal, sharing hands-on strategies to turn resistance into engagement. She digs into why students might refuse to work—like feeling overwhelmed, fearing failure, or dealing with personal struggles—and stresses the need to understand the "why" behind the b…

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[QA] Debug Smarter, Not Harder: AI Agents for Error Resolution in Computational Notebooks 8:07

2d ago8:07

8:07

This paper presents an AI agent for error resolution in computational notebooks, enhancing bug-fixing capabilities while evaluating user experience and collaboration within the JetBrains Datalore service. https://arxiv.org/abs//2410.14393 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: http…

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Debug Smarter, Not Harder: AI Agents for Error Resolution in Computational Notebooks 10:28

2d ago10:28

10:28

This paper presents an AI agent for error resolution in computational notebooks, enhancing bug-fixing capabilities while evaluating user experience and collaboration within the JetBrains Datalore service. https://arxiv.org/abs//2410.14393 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: http…

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[QA] Decomposing The Dark Matter of Sparse Autoencoders 7:58

2d ago7:58

7:58

This study explores "dark matter" in sparse autoencoders, revealing that much unexplained variance can be predicted and proposing methods to reduce nonlinear error in model activations. https://arxiv.org/abs//2410.14670 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.apple.…

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Decomposing The Dark Matter of Sparse Autoencoders 15:36

2d ago15:36

15:36

This study explores "dark matter" in sparse autoencoders, revealing that much unexplained variance can be predicted and proposing methods to reduce nonlinear error in model activations. https://arxiv.org/abs//2410.14670 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.apple.…

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Episode 211: Elementary School Leader 33:35

3d ago33:35

33:35

Toni Rose is joined by Sara Bennis to talk about how she uses and adapts MCP as the principal of a rural elementary school. Show Notes The Energy Bus, by Jon Gordon Connect with Sara by email at sbennis@maquoketaschools.org, and check out her district and its Socials at [maquoketaschools.org](maquoketaschools.org) Learning Experiences for the Upcom…

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[QA] A Hitchhiker's Guide to Scaling Law Estimation 10:08

3d ago10:08

10:08

The paper analyzes scaling laws in machine learning, providing best practices for estimating model performance using a large dataset of pretrained models and emphasizing the importance of intermediate training checkpoints. https://arxiv.org/abs//2410.11840 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Ap…

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A Hitchhiker's Guide to Scaling Law Estimation 17:28

3d ago17:28

17:28

The paper analyzes scaling laws in machine learning, providing best practices for estimating model performance using a large dataset of pretrained models and emphasizing the importance of intermediate training checkpoints. https://arxiv.org/abs//2410.11840 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Ap…

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[QA] Semantic Image Inversion and Editing using Rectified Stochastic Differential Equations 7:39

3d ago7:39

7:39

This paper presents a novel method for image inversion and editing using rectified flow models, achieving superior performance in zero-shot tasks compared to existing diffusion model approaches. https://arxiv.org/abs//2410.10792 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcas…

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Semantic Image Inversion and Editing using Rectified Stochastic Differential Equations 10:29

3d ago10:29

10:29

This paper presents a novel method for image inversion and editing using rectified flow models, achieving superior performance in zero-shot tasks compared to existing diffusion model approaches. https://arxiv.org/abs//2410.10792 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcas…

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[QA] Looking Inward: Language Models Can Learn About Themselves by Introspection 7:28

4d ago7:28

7:28

The paper explores whether large language models (LLMs) can introspect, finding that finetuned models can predict their own behavior, suggesting a form of internal knowledge access. https://arxiv.org/abs//2410.13787 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.apple.com/…

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Looking Inward: Language Models Can Learn About Themselves by Introspection 26:21

4d ago26:21

26:21

The paper explores whether large language models (LLMs) can introspect, finding that finetuned models can predict their own behavior, suggesting a form of internal knowledge access. https://arxiv.org/abs//2410.13787 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.apple.com/…

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[QA] Thinking LLMs: General Instruction Following with Thought Generation 7:25

4d ago7:25

7:25

The paper proposes a method to enhance LLMs' thinking abilities for better instruction following, improving performance across various tasks without additional human data through iterative search and optimization. https://arxiv.org/abs//2410.10630 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podca…

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Thinking LLMs: General Instruction Following with Thought Generation 15:52

4d ago15:52

15:52

The paper proposes a method to enhance LLMs' thinking abilities for better instruction following, improving performance across various tasks without additional human data through iterative search and optimization. https://arxiv.org/abs//2410.10630 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podca…

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[QA] Active-Dormant Attention Heads: Mechanistically Demystifying Extreme-Token Phenomena in LLMs 7:44

4d ago7:44

7:44

The paper investigates extreme-token phenomena in transformer-based LLMs, revealing mechanisms behind attention sinks and proposing strategies to mitigate their impact during pretraining. https://arxiv.org/abs//2410.13835 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.appl…

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Active-Dormant Attention Heads: Mechanistically Demystifying Extreme-Token Phenomena in LLMs 17:44

4d ago17:44

17:44

The paper investigates extreme-token phenomena in transformer-based LLMs, revealing mechanisms behind attention sinks and proposing strategies to mitigate their impact during pretraining. https://arxiv.org/abs//2410.13835 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.appl…

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[QA] MOVIE GEN: A Cast of Media Foundation Models 8:52

4d ago8:52

8:52

https://arxiv.org/abs//2410.13720 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-papers/id1692476016 Spotify: https://podcasters.spotify.com/pod/show/arxiv-papers --- Support this podcast: https://podcasters.spotify.com/pod/show/arxiv-papers/supp…

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MOVIE GEN: A Cast of Media Foundation Models 1:53:06

4d ago1:53:06

1:53:06

https://arxiv.org/abs//2410.13720 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-papers/id1692476016 Spotify: https://podcasters.spotify.com/pod/show/arxiv-papers --- Support this podcast: https://podcasters.spotify.com/pod/show/arxiv-papers/supp…

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[QA] One Step Diffusion via Shortcut Models 8:06

6d ago8:06

8:06

https://arxiv.org/abs//2410.12557 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-papers/id1692476016 Spotify: https://podcasters.spotify.com/pod/show/arxiv-papers --- Support this podcast: https://podcasters.spotify.com/pod/show/arxiv-papers/supp…

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One Step Diffusion via Shortcut Models 17:39

6d ago17:39

17:39

https://arxiv.org/abs//2410.12557 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-papers/id1692476016 Spotify: https://podcasters.spotify.com/pod/show/arxiv-papers --- Support this podcast: https://podcasters.spotify.com/pod/show/arxiv-papers/supp…

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[QA] Inference Scaling for Long-Context Retrieval Augmented Generation 7:17

6d ago7:17

7:17

https://arxiv.org/abs//2410.04343 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-papers/id1692476016 Spotify: https://podcasters.spotify.com/pod/show/arxiv-papers --- Support this podcast: https://podcasters.spotify.com/pod/show/arxiv-papers/supp…

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Inference Scaling for Long-Context Retrieval Augmented Generation 22:02

6d ago22:02

22:02

https://arxiv.org/abs//2410.04343 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-papers/id1692476016 Spotify: https://podcasters.spotify.com/pod/show/arxiv-papers --- Support this podcast: https://podcasters.spotify.com/pod/show/arxiv-papers/supp…

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[QA] What Matters in Transformers? Not All Attention is Needed 8:07

7d ago8:07

8:07

This study explores redundancy in Transformer architectures, revealing that many attention layers can be pruned with minimal performance loss, enhancing efficiency for large language models. https://arxiv.org/abs//2406.15786 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.a…

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What Matters in Transformers? Not All Attention is Needed 16:20

7d ago16:20

16:20

This study explores redundancy in Transformer architectures, revealing that many attention layers can be pruned with minimal performance loss, enhancing efficiency for large language models. https://arxiv.org/abs//2406.15786 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.a…

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[QA] Language Models Encode Numbers Using Digit Representations in Base 10 7:33

7d ago7:33

7:33

The paper investigates how large language models represent numbers, revealing they use digit-wise circular representations, which explains their frequent errors in numerical reasoning tasks. https://arxiv.org/abs//2410.11781 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.a…

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Language Models Encode Numbers Using Digit Representations in Base 10 10:36

7d ago10:36

10:36

The paper investigates how large language models represent numbers, revealing they use digit-wise circular representations, which explains their frequent errors in numerical reasoning tasks. https://arxiv.org/abs//2410.11781 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.a…

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50. 5 Ways to Support Flexibility in Autistic Students 13:31

9d ago13:31

13:31

In this episode, Lisa dives into practical strategies for teaching flexibility and reducing rigid thinking in autistic students. Since many kids with autism find comfort in routines, Lisa highlights the need to balance maintain structure and create room for growth. She shares insights on how understanding the roots of rigidity, modeling flexible be…

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152. Absences - How to Deal With Them 35:39

9d ago35:39

35:39

There are many elements of teaching that are unpredictable and out of your control, which can make it difficult to handle or prepare for. One of those things are student absences. Let’s be honest, it’s a miracle when all of your students are in class on the same day! So, you need to prepare and determine how you’re going to deal with the absences o…

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[QA] Don't Transform the Code, Code the Transforms: Towards Precise Code Rewriting using LLMs 7:31

9d ago7:31

7:31

This paper explores using large language models to generate code transformations through a chain-of-thought approach, demonstrating improved precision and adaptability compared to direct code rewriting methods. https://arxiv.org/abs//2410.08806 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts…

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Don't Transform the Code, Code the Transforms: Towards Precise Code Rewriting using LLMs 6:15

9d ago6:15

6:15

This paper explores using large language models to generate code transformations through a chain-of-thought approach, demonstrating improved precision and adaptability compared to direct code rewriting methods. https://arxiv.org/abs//2410.08806 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts…

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[QA] Do Unlearning Methods Remove Information from Language Model Weights? 8:03

9d ago8:03

8:03

The paper evaluates unlearning techniques in Large Language Models, revealing that current methods inadequately remove sensitive information, allowing attackers to recover significant pre-unlearning accuracy. https://arxiv.org/abs//2410.08827 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: …

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Do Unlearning Methods Remove Information from Language Model Weights? 17:56

9d ago17:56

17:56

The paper evaluates unlearning techniques in Large Language Models, revealing that current methods inadequately remove sensitive information, allowing attackers to recover significant pre-unlearning accuracy. https://arxiv.org/abs//2410.08827 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: …

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Episode 210: You're Not the Only Expert in the Room 1:04:38

10d ago1:04:38

1:04:38

Toni Rose is joined by Sabrina Monserate-Lindsay for a deep dive into her approach to using the MCP model in her high school math class. Show Notes World Jigsaw Puzzle Championship 2024 Connect with Sabrina on Instagram @puzzle_bites Learning Experiences for the Upcoming Week We’re attending MassCUE in Foxborough, MA from Oct. 15-17. We have four o…

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[QA] MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering 7:19

10d ago7:19

7:19

MLE-bench is a benchmark for evaluating AI agents in machine learning engineering, featuring 75 Kaggle competitions and establishing human baselines, with open-source code for future research. https://arxiv.org/abs//2410.07095 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts…

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MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering 16:41

10d ago16:41

16:41

MLE-bench is a benchmark for evaluating AI agents in machine learning engineering, featuring 75 Kaggle competitions and establishing human baselines, with open-source code for future research. https://arxiv.org/abs//2410.07095 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts…

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[QA] Pixtral 12B 7:34

10d ago7:34

7:34

https://arxiv.org/abs//2410.07073 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-papers/id1692476016 Spotify: https://podcasters.spotify.com/pod/show/arxiv-papers --- Support this podcast: https://podcasters.spotify.com/pod/show/arxiv-papers/supp…

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Pixtral 12B 13:01

10d ago13:01

13:01

https://arxiv.org/abs//2410.07073 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-papers/id1692476016 Spotify: https://podcasters.spotify.com/pod/show/arxiv-papers --- Support this podcast: https://podcasters.spotify.com/pod/show/arxiv-papers/supp…

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[QA] Differential Transformer 7:20

11d ago7:20

7:20

DIFF Transformer enhances attention to relevant context while reducing noise, improving performance in language modeling, long-context tasks, and in-context learning, making it a promising architecture for large language models. https://arxiv.org/abs//2410.05258 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_pap…

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Differential Transformer 13:09

11d ago13:09

13:09

DIFF Transformer enhances attention to relevant context while reducing noise, improving performance in language modeling, long-context tasks, and in-context learning, making it a promising architecture for large language models. https://arxiv.org/abs//2410.05258 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_pap…

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[QA] GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language Models 7:45

11d ago7:45

7:45

This study introduces GSM-Symbolic, a benchmark revealing LLMs' inconsistent mathematical reasoning, highlighting performance drops with altered questions and increased complexity, questioning their genuine logical reasoning abilities. https://arxiv.org/abs//2410.05229 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@ar…

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GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language Models 12:39

11d ago12:39

12:39

This study introduces GSM-Symbolic, a benchmark revealing LLMs' inconsistent mathematical reasoning, highlighting performance drops with altered questions and increased complexity, questioning their genuine logical reasoning abilities. https://arxiv.org/abs//2410.05229 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@ar…

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[QA] Efficient Dictionary Learning with Switch Sparse Autoencoders 7:43

12d ago7:43

7:43

Switch Sparse Autoencoders efficiently scale feature extraction in neural networks by routing activations through smaller expert models, improving reconstruction and sparsity while reducing computational costs. https://arxiv.org/abs//2410.08201 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts…

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Differentiated Instruction Podcasts

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