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The Bodies Behind the Bus is a podcast centering on the voices of spiritual abuse survivors. We began with stories out of the Acts 29 network and have branched into many organizations since our launch. We are the discarded few. We have been abused, gaslit, ignored, slandered, deceived, intentionally hurt, and betrayed. Our stories were manipulated and our voices were stolen. We were left alone with all the confusion, grief, hurt, and pain but today we begin to reclaim our stories and find ou ...
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Running out of time to catch up with new arXiv papers? We take the most impactful papers and present them as convenient podcasts. If you're a visual learner, we offer these papers in an engaging video format. Our service fills the gap between overly brief paper summaries and time-consuming full paper reads. You gain academic insights in a time-efficient, digestible format. Code behind this work: https://github.com/imelnyk/ArxivPapers Support this podcast: https://podcasters.spotify.com/pod/s ...
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Take chances, make mistakes and get messy! Random Theory is here to blow your mind and challenge the way we talk about science. A theory is: a plausible or scientifically acceptable general principal or body of principals offered to explain a phenomena. I’m Grace Dirig, your host and around here at TKOR we like to think the Random Theory best explains how we come up with ideas! Miss Frizzle was the first person to challenge the way I saw the world! Yeah, you know the super cool girl from the ...
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https://clergysexualmisconduct.com Support the Show.By Bodies Behind The Bus
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1
[QA] Does Liking Yellow Imply Driving a School Bus? Semantic Leakage in Language Models
7:26
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The paper identifies "semantic leakage" in language models, revealing how irrelevant prompt information influences outputs, and proposes methods for detection and evaluation across multiple languages and scenarios. https://arxiv.org/abs//2408.06518 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podc…
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Does Liking Yellow Imply Driving a School Bus? Semantic Leakage in Language Models
16:13
16:13
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The paper identifies "semantic leakage" in language models, revealing how irrelevant prompt information influences outputs, and proposes methods for detection and evaluation across multiple languages and scenarios. https://arxiv.org/abs//2408.06518 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podc…
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1
[QA] Learned Ranking Function: From Short-term Behavior Predictions to Long-term User Satisfaction
8:28
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The Learned Ranking Function (LRF) optimizes recommendations for long-term user satisfaction using short-term behavior predictions, employing a novel constraint optimization algorithm, and is tested on YouTube. https://arxiv.org/abs//2408.06512 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts…
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1
Learned Ranking Function: From Short-term Behavior Predictions to Long-term User Satisfaction
15:10
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The Learned Ranking Function (LRF) optimizes recommendations for long-term user satisfaction using short-term behavior predictions, employing a novel constraint optimization algorithm, and is tested on YouTube. https://arxiv.org/abs//2408.06512 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts…
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1
[QA] The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery
8:34
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The paper introduces THE AI SCIENTIST, a framework enabling LLMs to autonomously conduct scientific research, generate ideas, write papers, and evaluate findings, significantly advancing scientific discovery and democratizing research. https://arxiv.org/abs//2408.06292 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@ar…
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The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery
30:36
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The paper introduces THE AI SCIENTIST, a framework enabling LLMs to autonomously conduct scientific research, generate ideas, write papers, and evaluate findings, significantly advancing scientific discovery and democratizing research. https://arxiv.org/abs//2408.06292 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@ar…
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1
[QA] Body Transformer: Leveraging Robot Embodiment for Policy Learning
7:59
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The Body Transformer (BoT) enhances robot learning by leveraging robot embodiment, outperforming vanilla transformers and multilayer perceptrons in task completion and efficiency. Open-source code is available. https://arxiv.org/abs//2408.06316 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts…
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Body Transformer: Leveraging Robot Embodiment for Policy Learning
15:21
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The Body Transformer (BoT) enhances robot learning by leveraging robot embodiment, outperforming vanilla transformers and multilayer perceptrons in task completion and efficiency. Open-source code is available. https://arxiv.org/abs//2408.06316 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts…
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1
[QA] VITA: Towards Open-Source Interactive Omni Multimodal LLM
8:16
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VITA is the first open-source Multimodal Large Language Model, integrating video, image, text, and audio processing, enhancing human-computer interaction with innovative features like non-awakening and audio interrupt interactions. https://arxiv.org/abs//2408.05211 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_…
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1
VITA: Towards Open-Source Interactive Omni Multimodal LLM
13:18
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VITA is the first open-source Multimodal Large Language Model, integrating video, image, text, and audio processing, enhancing human-computer interaction with innovative features like non-awakening and audio interrupt interactions. https://arxiv.org/abs//2408.05211 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_…
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1
[QA] Gemma Scope: Open Sparse Autoencoders Everywhere All At Once on Gemma 2
7:45
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https://arxiv.org/abs//2408.05147 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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1
Gemma Scope: Open Sparse Autoencoders Everywhere All At Once on Gemma 2
22:04
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https://arxiv.org/abs//2408.05147 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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This paper presents a guided diffusion model that enhances auto-regressive language models, enabling controlled text generation with improved fluency and flexibility, outperforming existing guidance methods. https://arxiv.org/abs//2408.04220 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: h…
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--- Support this podcast: https://podcasters.spotify.com/pod/show/arxiv-papers/support
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Conversational Prompt Engineering (CPE) simplifies prompt creation for LLMs, enabling personalized, efficient outputs through user interaction, ultimately saving time and enhancing performance in summarization tasks. https://arxiv.org/abs//2408.04560 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Po…
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Conversational Prompt Engineering (CPE) simplifies prompt creation for LLMs, enabling personalized, efficient outputs through user interaction, ultimately saving time and enhancing performance in summarization tasks. https://arxiv.org/abs//2408.04560 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Po…
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1
[QA] Img-Diff: Contrastive Data Synthesis for Multimodal Large Language Models
8:49
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This study presents Img-Diff, a novel dataset for fine-grained image recognition in MLLMs, enhancing performance through contrastive learning and image difference captioning, outperforming existing models. https://arxiv.org/abs//2408.04594 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: htt…
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Img-Diff: Contrastive Data Synthesis for Multimodal Large Language Models
23:13
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This study presents Img-Diff, a novel dataset for fine-grained image recognition in MLLMs, enhancing performance through contrastive learning and image difference captioning, outperforming existing models. https://arxiv.org/abs//2408.04594 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: htt…
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1
[QA] Better Alignment with Instruction Back-and-Forth Translation
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The paper introduces instruction back-and-forth translation for generating high-quality synthetic data, enhancing large language model alignment through improved instruction and response quality compared to existing datasets. https://arxiv.org/abs//2408.04614 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers…
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1
Better Alignment with Instruction Back-and-Forth Translation
23:23
23:23
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23:23
The paper introduces instruction back-and-forth translation for generating high-quality synthetic data, enhancing large language model alignment through improved instruction and response quality compared to existing datasets. https://arxiv.org/abs//2408.04614 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers…
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This paper addresses The Ungrounded Alignment Problem, proposing a method for unsupervised learners to associate images with class labels using letter bigram frequencies, enabling innate behavior in modality-agnostic models. https://arxiv.org/abs//2408.04242 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers …
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This paper addresses The Ungrounded Alignment Problem, proposing a method for unsupervised learners to associate images with class labels using letter bigram frequencies, enabling innate behavior in modality-agnostic models. https://arxiv.org/abs//2408.04242 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers …
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1
[QA] Prioritize Alignment in Dataset Distillation
8:19
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The paper introduces Prioritize Alignment in Dataset Distillation (PAD), enhancing dataset compression by aligning information extraction and embedding, leading to significant performance improvements in distillation algorithms. https://arxiv.org/abs//2408.03360 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_pap…
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1
Prioritize Alignment in Dataset Distillation
20:57
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The paper introduces Prioritize Alignment in Dataset Distillation (PAD), enhancing dataset compression by aligning information extraction and embedding, leading to significant performance improvements in distillation algorithms. https://arxiv.org/abs//2408.03360 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_pap…
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1
[QA] Optimus-1: Hybrid Multimodal Memory Empowered Agents Excel in Long-Horizon Tasks
7:57
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The paper presents Optimus-1, a multimodal agent utilizing a Hybrid Multimodal Memory module to enhance long-horizon task performance in Minecraft, outperforming existing agents and achieving near human-level results. https://arxiv.org/abs//2408.03615 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple P…
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1
Optimus-1: Hybrid Multimodal Memory Empowered Agents Excel in Long-Horizon Tasks
16:31
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The paper presents Optimus-1, a multimodal agent utilizing a Hybrid Multimodal Memory module to enhance long-horizon task performance in Minecraft, outperforming existing agents and achieving near human-level results. https://arxiv.org/abs//2408.03615 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple P…
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1
[QA] Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters
7:17
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https://arxiv.org/abs//2408.03314 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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1
Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters
29:43
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https://arxiv.org/abs//2408.03314 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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1
Stephanie’s Story/ Chicagoland Part 1
1:58:22
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https://clergysexualmisconduct.com Contact Stephanie: s.nelsonbbtb@gmail.com Support the Show.
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[QA] Language Model Can Listen While Speaking
7:07
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The paper presents the listening-while-speaking language model (LSLM), enhancing real-time human-computer interaction through full duplex modeling, enabling effective interruptions and improved conversational AI performance. https://arxiv.org/abs//2408.02622 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers …
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The paper presents the listening-while-speaking language model (LSLM), enhancing real-time human-computer interaction through full duplex modeling, enabling effective interruptions and improved conversational AI performance. https://arxiv.org/abs//2408.02622 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers …
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This work introduces a self-improvement method for LLM evaluators using synthetic data, enhancing performance significantly without human annotations, surpassing GPT-4 and matching top reward models. https://arxiv.org/abs//2408.02666 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://p…
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This work introduces a self-improvement method for LLM evaluators using synthetic data, enhancing performance significantly without human annotations, surpassing GPT-4 and matching top reward models. https://arxiv.org/abs//2408.02666 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://p…
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The paper introduces COND P-DIFF, a method for generating high-performance neural network parameters using controllable latent diffusion, enhancing task-specific adaptation in computer vision and natural language processing. https://arxiv.org/abs//2408.01415 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers …
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The paper introduces COND P-DIFF, a method for generating high-performance neural network parameters using controllable latent diffusion, enhancing task-specific adaptation in computer vision and natural language processing. https://arxiv.org/abs//2408.01415 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers …
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1
[QA] Mission Impossible: A Statistical Perspective on Jailbreaking LLMs
7:33
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This paper analyzes preference alignment and jailbreaking in large language models, proposing E-RLHF as a cost-effective method to enhance safety without compromising performance. https://arxiv.org/abs//2408.01420 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.apple.com/us…
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Mission Impossible: A Statistical Perspective on Jailbreaking LLMs
10:56
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This paper analyzes preference alignment and jailbreaking in large language models, proposing E-RLHF as a cost-effective method to enhance safety without compromising performance. https://arxiv.org/abs//2408.01420 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.apple.com/us…
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1
[QA] Meta-Rewarding Language Models: Self-Improving Alignment with LLM-as-a-Meta-Judge
7:19
7:19
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7:19
The paper introduces a Meta-Rewarding mechanism for LLMs, enhancing their self-judgment capabilities, leading to significant performance improvements without relying on human data. https://arxiv.org/abs//2407.19594 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.apple.com/u…
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Meta-Rewarding Language Models: Self-Improving Alignment with LLM-as-a-Meta-Judge
22:41
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The paper introduces a Meta-Rewarding mechanism for LLMs, enhancing their self-judgment capabilities, leading to significant performance improvements without relying on human data. https://arxiv.org/abs//2407.19594 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.apple.com/u…
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1
[QA] MindSearch : Mimicking Human Minds Elicits Deep AI Searcher
7:05
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7:05
MindSearch mimics human cognitive processes for information seeking and integration, using a multi-agent framework to enhance search engine performance and improve response quality significantly. https://arxiv.org/abs//2407.20183 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podca…
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1
MindSearch : Mimicking Human Minds Elicits Deep AI Searcher
14:16
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MindSearch mimics human cognitive processes for information seeking and integration, using a multi-agent framework to enhance search engine performance and improve response quality significantly. https://arxiv.org/abs//2407.20183 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podca…
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1
[QA] Safetywashing: Do AI Safety Benchmarks Actually Measure Safety Progress?
7:50
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7:50
The paper analyzes AI safety benchmarks, revealing their correlation with general capabilities, and proposes a clearer framework for defining and measuring AI safety research goals. https://arxiv.org/abs//2407.21792 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.apple.com/…
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Safetywashing: Do AI Safety Benchmarks Actually Measure Safety Progress?
15:20
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The paper analyzes AI safety benchmarks, revealing their correlation with general capabilities, and proposes a clearer framework for defining and measuring AI safety research goals. https://arxiv.org/abs//2407.21792 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.apple.com/…
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1
[QA] Gemma 2: Improving Open Language Models at a Practical Size
7:30
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7:30
https://arxiv.org/abs//2408.00118 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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Gemma 2: Improving Open Language Models at a Practical Size
21:55
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https://arxiv.org/abs//2408.00118 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] AI-Assisted Generation of Difficult Math Questions
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The paper presents a framework combining LLMs and human input to generate diverse, challenging math questions, enhancing quality through iterative refinement and skill-based question generation. https://arxiv.org/abs//2407.21009 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcas…
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AI-Assisted Generation of Difficult Math Questions
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The paper presents a framework combining LLMs and human input to generate diverse, challenging math questions, enhancing quality through iterative refinement and skill-based question generation. https://arxiv.org/abs//2407.21009 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcas…
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1
[QA] SAM 2: Segment Anything in Images and Videos
7:25
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https://arxiv.org/abs//2408.00714 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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SAM 2: Segment Anything in Images and Videos
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https://arxiv.org/abs//2408.00714 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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