Best Stable Diffusion Podcasts (2024)

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#186 Ronen Dar: Maximizing GPU Utilization for AI with Run:ai 1:11:01

1h ago1:11:01

1:11:01

This episode is sponsored by 1Password. 1Password combines industry-leading security with award-winning design to bring private, secure, and user-friendly password management to everyone. Companies lose hours every day just from employees forgetting and resetting passwords. A single data breach costs millions of dollars. 1Password secures every sig…

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[QA] From LLMs to Actions: Latent Codes as Bridges in Hierarchical Robot Control 11:33

36m ago11:33

11:33

Hierarchical control in robotics faces challenges with language interfaces. Learnable Latent Codes as Bridges (LCB) offer a solution, outperforming language-based baselines on complex tasks in embodied agent benchmarks. https://arxiv.org/abs//2405.04798 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple…

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From LLMs to Actions: Latent Codes as Bridges in Hierarchical Robot Control 13:23

37m ago13:23

13:23

Hierarchical control in robotics faces challenges with language interfaces. Learnable Latent Codes as Bridges (LCB) offer a solution, outperforming language-based baselines on complex tasks in embodied agent benchmarks. https://arxiv.org/abs//2405.04798 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple…

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[QA] Distilling Diffusion Models into Conditional GANs 8:28

43m ago8:28

8:28

Proposing a method to distill a complex diffusion model into a single-step GAN, accelerating inference while maintaining image quality, outperforming existing models on COCO benchmark. https://arxiv.org/abs//2405.05967 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.apple.c…

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Distilling Diffusion Models into Conditional GANs 17:14

43m ago17:14

17:14

Proposing a method to distill a complex diffusion model into a single-step GAN, accelerating inference while maintaining image quality, outperforming existing models on COCO benchmark. https://arxiv.org/abs//2405.05967 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.apple.c…

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[QA] AlphaMath Almost Zero: process Supervision without process 10:57

35m ago10:57

10:57

Innovative approach uses Monte Carlo Tree Search to automatically generate supervision signals for training large language models, improving mathematical reasoning proficiency without manual annotation. https://arxiv.org/abs//2405.03553 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https:…

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AlphaMath Almost Zero: process Supervision without process 12:31

35m ago12:31

12:31

Innovative approach uses Monte Carlo Tree Search to automatically generate supervision signals for training large language models, improving mathematical reasoning proficiency without manual annotation. https://arxiv.org/abs//2405.03553 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https:…

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[QA] Arctic-Embed: Scalable, Efficient, and Accurate Text Embedding Models 10:34

17h ago10:34

10:34

The paper presents the creation and performance of the arctic-embed text embedding models, showcasing state-of-the-art retrieval accuracy and providing insights into their training process. https://arxiv.org/abs//2405.05374 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.ap…

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Arctic-Embed: Scalable, Efficient, and Accurate Text Embedding Models 13:52

2h ago13:52

13:52

The paper presents the creation and performance of the arctic-embed text embedding models, showcasing state-of-the-art retrieval accuracy and providing insights into their training process. https://arxiv.org/abs//2405.05374 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.ap…

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[QA] Poser: Unmasking Alignment Faking LLMs by Manipulating Their Internals 9:53

25m ago9:53

9:53

Large Language Models (LLMs) can deceive as 'alignment fakers.' A benchmark with 324 LLM pairs is introduced to detect misbehaving models, achieving 98% accuracy with a specific strategy. https://arxiv.org/abs//2405.05466 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.appl…

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Poser: Unmasking Alignment Faking LLMs by Manipulating Their Internals 8:56

25m ago8:56

8:56

Large Language Models (LLMs) can deceive as 'alignment fakers.' A benchmark with 324 LLM pairs is introduced to detect misbehaving models, achieving 98% accuracy with a specific strategy. https://arxiv.org/abs//2405.05466 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.appl…

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[QA] Does Fine-Tuning LLMs on New Knowledge Encourage Hallucinations? 7:16

29m ago7:16

7:16

Supervised fine-tuning of large language models introduces new factual knowledge, impacting model behavior. New knowledge is learned slower, leading to increased tendency to hallucinate factually incorrect responses. https://arxiv.org/abs//2405.05904 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Po…

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Does Fine-Tuning LLMs on New Knowledge Encourage Hallucinations? 17:29

29m ago17:29

17:29

Supervised fine-tuning of large language models introduces new factual knowledge, impacting model behavior. New knowledge is learned slower, leading to increased tendency to hallucinate factually incorrect responses. https://arxiv.org/abs//2405.05904 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Po…

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[QA] Towards a Theoretical Understanding of the `Reversal Curse' via Training Dynamics 10:44

19m ago10:44

10:44

The paper analyzes the "reversal curse" in large language models, explaining why they struggle with logical reasoning tasks like inverse search and chain-of-thought. https://arxiv.org/abs//2405.04669 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.apple.com/us/podcast/arxiv…

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Towards a Theoretical Understanding of the `Reversal Curse' via Training Dynamics 24:33

20m ago24:33

24:33

The paper analyzes the "reversal curse" in large language models, explaining why they struggle with logical reasoning tasks like inverse search and chain-of-thought. https://arxiv.org/abs//2405.04669 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.apple.com/us/podcast/arxiv…

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[QA] Attention-Driven Training-Free Efficiency Enhancement of Diffusion Models 10:00

6m ago10:00

10:00

AT-EDM framework uses attention maps for efficient token pruning in Diffusion Models, achieving significant FLOPs savings and speed-up without retraining, maintaining image quality. https://arxiv.org/abs//2405.05252 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.apple.com/…

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Attention-Driven Training-Free Efficiency Enhancement of Diffusion Models 13:32

7m ago13:32

13:32

AT-EDM framework uses attention maps for efficient token pruning in Diffusion Models, achieving significant FLOPs savings and speed-up without retraining, maintaining image quality. https://arxiv.org/abs//2405.05252 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.apple.com/…

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[QA] Custom Gradient Estimators are Straight-Through Estimators in Disguise 8:09

8m ago8:09

8:09

The paper addresses challenges in quantization-aware training by proposing differentiable approximations for quantization functions, showing equivalence of weight gradient estimators, and experimental validation on various models. https://arxiv.org/abs//2405.05171 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_p…

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Custom Gradient Estimators are Straight-Through Estimators in Disguise 16:36

8m ago16:36

16:36

The paper addresses challenges in quantization-aware training by proposing differentiable approximations for quantization functions, showing equivalence of weight gradient estimators, and experimental validation on various models. https://arxiv.org/abs//2405.05171 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_p…

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EP 10: Social Media for Interior Designers Using Chat GPT with Lezlie Swink 21:46

2h ago21:46

21:46

In this conversation, Jenna Gaidusek interviews Leslie Swink of Swink Social about utilizing AI in interior design. They discuss the importance of defining the ideal client and how AI can assist in this process. They also talk about creating personalized content, including value-added, personal brand, and promotional content. Leslie shares how AI c…

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[QA] The Curse of Diversity in Ensemble-Based Exploration 9:19

1h ago9:19

9:19

Ensemble training in deep reinforcement learning can harm individual agents due to data sharing. The curse of diversity is explained and mitigated with Cross-Ensemble Representation Learning. https://arxiv.org/abs//2405.04342 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.…

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The Curse of Diversity in Ensemble-Based Exploration 10:27

1h ago10:27

10:27

Ensemble training in deep reinforcement learning can harm individual agents due to data sharing. The curse of diversity is explained and mitigated with Cross-Ensemble Representation Learning. https://arxiv.org/abs//2405.04342 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.…

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AI lab - AI in Action | Episode 01: AI History 9:15

2h ago9:15

9:15

We are kickstarting our AI in Action series by diving headfirst into the key milestones that led to the gradual deployment of Artificial Intelligence, or AI for short. You might think it's some shiny new invention, looking at all the recent media coverage about robots taking over your jobs and writing bad poetry. But hold on to your Roomba, because…

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[QA] ImageInWords: Unlocking Hyper-Detailed Image Descriptions 10:56

5m ago10:56

10:56

Image descriptions for training Vision-Language models are often inaccurate. ImageInWords introduces a new dataset with hyper-detailed descriptions, improving model performance significantly. https://arxiv.org/abs//2405.02793 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.…

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ImageInWords: Unlocking Hyper-Detailed Image Descriptions 15:09

6m ago15:09

15:09

Image descriptions for training Vision-Language models are often inaccurate. ImageInWords introduces a new dataset with hyper-detailed descriptions, improving model performance significantly. https://arxiv.org/abs//2405.02793 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.…

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[QA] Why is SAM Robust to Label Noise? 9:27

11m ago9:27

9:27

Sharpness-Aware Minimization (SAM) excels in label noise robustness, with peak performance under early stopping, attributed to changes in logit term and network Jacobian. Alternative methods mimic SAM's regularization effects effectively. https://arxiv.org/abs//2405.03676 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/…

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Why is SAM Robust to Label Noise? 16:27

12m ago16:27

16:27

Sharpness-Aware Minimization (SAM) excels in label noise robustness, with peak performance under early stopping, attributed to changes in logit term and network Jacobian. Alternative methods mimic SAM's regularization effects effectively. https://arxiv.org/abs//2405.03676 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/…

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[QA] Is Flash Attention Stable? 9:36

18m ago9:36

9:36

The paper addresses challenges in training large-scale machine learning models, focusing on numeric deviation causing instability, with a case study on Flash Attention optimization. https://arxiv.org/abs//2405.02803 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.apple.com/…

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Is Flash Attention Stable? 10:13

19m ago10:13

10:13

The paper addresses challenges in training large-scale machine learning models, focusing on numeric deviation causing instability, with a case study on Flash Attention optimization. https://arxiv.org/abs//2405.02803 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.apple.com/…

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#185 Damon Rasheed & Saurabh Jain: Achieving Up to 90% Accuracy in Predicting Drug Clinical Trial Outcomes with Opyl's Trialkey.ai 51:55

11m ago51:55

51:55

This episode is sponsored by Netsuite by Oracle, the number one cloud financial system, streamlining accounting, financial management, inventory, HR, and more. NetSuite is offering a one-of-a-kind flexible financing program. Head to https://netsuite.com/EYEONAI to know more. Unlock the secrets of clinical trial predictions with Saurabh Jain and Dam…

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The Future of AI Accountability & Responsibility 51:01

33m ago51:01

51:01

We are thrilled to bring you an insightful episode that dives deep into the pressing issues of accountability and responsibility in the realm of Artificial Intelligence within the creative industries. Introduction by Dyann Heward-Mills: The EU AI Act To set the framework, we have the honor of welcoming Dyann Heward-Mills:, an esteemed expert in AI …

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[QA] Understanding LLMs Requires More Than Statistical Generalization 10:10

5h ago10:10

10:10

The paper discusses the non-identifiability of large language models (LLMs) and its implications on generalization, highlighting the need for a new theoretical perspective. https://arxiv.org/abs//2405.01964 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.apple.com/us/podcas…

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Understanding LLMs Requires More Than Statistical Generalization 19:25

5h ago19:25

19:25

The paper discusses the non-identifiability of large language models (LLMs) and its implications on generalization, highlighting the need for a new theoretical perspective. https://arxiv.org/abs//2405.01964 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.apple.com/us/podcas…

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[QA] Mitigating LLM Hallucinations via Conformal Abstention 8:28

5h ago8:28

8:28

Developing a method for large language models to abstain from providing incorrect answers, using self-consistency and conformal prediction to reduce hallucination rates. https://arxiv.org/abs//2405.01563 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.apple.com/us/podcast/a…

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Mitigating LLM Hallucinations via Conformal Abstention 19:11

5h ago19:11

19:11

Developing a method for large language models to abstain from providing incorrect answers, using self-consistency and conformal prediction to reduce hallucination rates. https://arxiv.org/abs//2405.01563 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.apple.com/us/podcast/a…

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[QA] Structural Pruning of Pre-trained Language Models via Neural Architecture Search 8:56

5h ago8:56

8:56

Paper explores using neural architecture search (NAS) for structural pruning of pre-trained language models to optimize efficiency and generalization performance, utilizing two-stage weight-sharing NAS for accelerated search. https://arxiv.org/abs//2405.02267 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers…

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Structural Pruning of Pre-trained Language Models via Neural Architecture Search 13:25

5h ago13:25

13:25

Paper explores using neural architecture search (NAS) for structural pruning of pre-trained language models to optimize efficiency and generalization performance, utilizing two-stage weight-sharing NAS for accelerated search. https://arxiv.org/abs//2405.02267 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers…

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[QA] Capabilities of Gemini Models in Medicine 13:07

1d ago13:07

13:07

The paper explores the impact of climate change on global food security, highlighting the need for sustainable agricultural practices to mitigate future risks. https://arxiv.org/abs//2404.18416 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-paper…

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Capabilities of Gemini Models in Medicine 35:57

1d ago35:57

35:57

The paper explores the impact of climate change on global food security, highlighting the need for sustainable agricultural practices to mitigate future risks. https://arxiv.org/abs//2404.18416 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-paper…

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[QA] StoryDiffusion: Consistent Self-Attention for Long-Range Image and Video Generation 9:55

1d ago9:55

9:55

The paper introduces Consistent Self-Attention and Semantic Motion Predictor to enhance content consistency in diffusion-based generative models for text-to-image and video generation, enabling rich visual story creation. https://arxiv.org/abs//2405.01434 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers App…

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StoryDiffusion: Consistent Self-Attention for Long-Range Image and Video Generation 15:05

1d ago15:05

15:05

The paper introduces Consistent Self-Attention and Semantic Motion Predictor to enhance content consistency in diffusion-based generative models for text-to-image and video generation, enabling rich visual story creation. https://arxiv.org/abs//2405.01434 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers App…

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[QA] In-Context Learning with Long-Context Models: An In-Depth Exploration 9:43

1d ago9:43

9:43

The paper explores in-context learning (ICL) at extreme scales, showing performance improvements with hundreds or thousands of demonstrations, contrasting with example retrieval and finetuning. https://arxiv.org/abs//2405.00200 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcast…

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In-Context Learning with Long-Context Models: An In-Depth Exploration 13:01

1d ago13:01

13:01

The paper explores in-context learning (ICL) at extreme scales, showing performance improvements with hundreds or thousands of demonstrations, contrasting with example retrieval and finetuning. https://arxiv.org/abs//2405.00200 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcast…

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[QA] WILDCHAT: 1M ChatGPT Interaction Logs in the Wild 11:01

3d ago11:01

11:01

WILDCHAT is a diverse dataset of 1 million user-ChatGPT conversations, offering rich insights into chatbot interactions and potential toxic use-cases for researchers. https://arxiv.org/abs//2405.01470 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.apple.com/us/podcast/arxi…

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WILDCHAT: 1M ChatGPT Interaction Logs in the Wild 13:11

3d ago13:11

13:11

WILDCHAT is a diverse dataset of 1 million user-ChatGPT conversations, offering rich insights into chatbot interactions and potential toxic use-cases for researchers. https://arxiv.org/abs//2405.01470 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.apple.com/us/podcast/arxi…

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[QA] NeMo-Aligner: Scalable Toolkit for Efficient Model Alignment 10:22

3d ago10:22

10:22

NeMo-Aligner is a scalable toolkit for aligning Large Language Models with human values, supporting various alignment paradigms and designed for extensibility. https://arxiv.org/abs//2405.01481 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-paper…

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NeMo-Aligner: Scalable Toolkit for Efficient Model Alignment 11:39

3d ago11:39

11:39

NeMo-Aligner is a scalable toolkit for aligning Large Language Models with human values, supporting various alignment paradigms and designed for extensibility. https://arxiv.org/abs//2405.01481 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-paper…

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[QA] PROMETHEUS 2: An Open Source Language Model Specialized in Evaluating Other Language Models 7:57

3d ago7:57

7:57

Prometheus 2 is an open-source LM designed for evaluating responses, outperforming existing models in correlation with human and proprietary LM judgments. https://arxiv.org/abs//2405.01535 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-papers/id1…

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PROMETHEUS 2: An Open Source Language Model Specialized in Evaluating Other Language Models 14:09

3d ago14:09

14:09

Prometheus 2 is an open-source LM designed for evaluating responses, outperforming existing models in correlation with human and proprietary LM judgments. https://arxiv.org/abs//2405.01535 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-papers/id1…

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[QA] A Careful Examination of Large Language Model Performance on Grade School Arithmetic 7:39

4d ago7:39

7:39

Study investigates dataset contamination in large language models for mathematical reasoning using Grade School Math 1000 benchmark, finding evidence of overfitting and potential memorization of benchmark questions. https://arxiv.org/abs//2405.00332 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Pod…

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