הפודקאסטים הטובים ביותר ב-Qa Tester (2024)

1
[QA] Automated Red Teaming with GOAT: the Generative Offensive Agent Tester 7:19

6d ago7:19

7:19

https://arxiv.org/abs//2410.01606 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…

1
[QA] EnsemW2S: Can an Ensemble of LLMs be Leveraged to Obtain a Stronger LLM? 7:42

21h ago7:42

7:42

This research proposes an innovative ensemble method for weak-to-strong generalization in AI, enhancing LLM performance through collaborative supervision, achieving significant improvements on challenging tasks. https://arxiv.org/abs//2410.04571 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcast…

1
EnsemW2S: Can an Ensemble of LLMs be Leveraged to Obtain a Stronger LLM? 18:39

21h ago18:39

18:39

This research proposes an innovative ensemble method for weak-to-strong generalization in AI, enhancing LLM performance through collaborative supervision, achieving significant improvements on challenging tasks. https://arxiv.org/abs//2410.04571 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcast…

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[QA] Density estimation with LLMs: a geometric investigation of in-context learning trajectories 8:13

21h ago8:13

8:13

This study explores LLaMA-2's in-context learning for probability density estimation, revealing unique learning trajectories and interpreting its behavior as adaptive kernel density estimation. https://arxiv.org/abs//2410.05218 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcast…

1
Density estimation with LLMs: a geometric investigation of in-context learning trajectories 12:31

22h ago12:31

12:31

This study explores LLaMA-2's in-context learning for probability density estimation, revealing unique learning trajectories and interpreting its behavior as adaptive kernel density estimation. https://arxiv.org/abs//2410.05218 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcast…

1
Empowering Parents Foster a Positive Gaming Space for Kids with Heidi Vogel of GuardianGamer AI 34:43

22h ago34:43

34:43

Heidi Vogel is a seasoned entrepreneur with over five companies under her belt, and today she shares her incredible journey from tech pioneer to gaming innovator. As a mother of four, she faced challenges managing her children's digital playground, which inspired her to develop GuardianGamer's monitoring solution. Her latest venture, GuardianGamer …

1
[QA] Teaching Transformers Modular Arithmetic at Scale 8:29

2d ago8:29

8:29

This paper enhances modular addition in machine learning by introducing diverse training data, angular embedding, and a custom loss function, improving performance for cryptographic applications and other modular arithmetic problems. https://arxiv.org/abs//2410.03569 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxi…

1
Teaching Transformers Modular Arithmetic at Scale 13:01

2d ago13:01

13:01

This paper enhances modular addition in machine learning by introducing diverse training data, angular embedding, and a custom loss function, improving performance for cryptographic applications and other modular arithmetic problems. https://arxiv.org/abs//2410.03569 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxi…

1
[QA] What Matters for Model Merging at Scale? 7:57

2d ago7:57

7:57

This study evaluates model merging at scale, revealing insights on expert model quality, size, and merging methods, ultimately enhancing generalization and performance in large-scale applications. https://arxiv.org/abs//2410.03617 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podc…

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What Matters for Model Merging at Scale? 24:32

2d ago24:32

24:32

This study evaluates model merging at scale, revealing insights on expert model quality, size, and merging methods, ultimately enhancing generalization and performance in large-scale applications. https://arxiv.org/abs//2410.03617 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podc…

1
[QA] Depth Pro: Sharp Monocular Metric Depth in Less Than a Second 7:17

4d ago7:17

7:17

Depth Pro is a fast foundation model for zero-shot monocular depth estimation, producing high-resolution, metric depth maps without metadata, outperforming previous methods in accuracy and detail. https://arxiv.org/abs//2410.02073 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podc…

1
Depth Pro: Sharp Monocular Metric Depth in Less Than a Second 14:08

4d ago14:08

14:08

Depth Pro is a fast foundation model for zero-shot monocular depth estimation, producing high-resolution, metric depth maps without metadata, outperforming previous methods in accuracy and detail. https://arxiv.org/abs//2410.02073 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podc…

1
[QA] Were RNNs All We Needed? 9:32

4d ago9:32

9:32

This work revisits LSTMs and GRUs, introducing minimal versions that eliminate hidden state dependencies, enabling efficient parallel training while matching the performance of recent sequence models. https://arxiv.org/abs//2410.01201 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://…

1
Were RNNs All We Needed? 16:06

4d ago16:06

16:06

This work revisits LSTMs and GRUs, introducing minimal versions that eliminate hidden state dependencies, enabling efficient parallel training while matching the performance of recent sequence models. https://arxiv.org/abs//2410.01201 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://…

1
[QA] OOD-CHAMELEON: Is Algorithm Selection for OOD Generalization Learnable? 8:08

5d ago8:08

8:08

The paper introduces OOD-CHAMELEON, a method for selecting algorithms for out-of-distribution generalization by predicting performance based on dataset characteristics, outperforming individual algorithms and heuristics. https://arxiv.org/abs//2410.02735 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Appl…

1
OOD-CHAMELEON: Is Algorithm Selection for OOD Generalization Learnable? 21:51

5d ago21:51

21:51

The paper introduces OOD-CHAMELEON, a method for selecting algorithms for out-of-distribution generalization by predicting performance based on dataset characteristics, outperforming individual algorithms and heuristics. https://arxiv.org/abs//2410.02735 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Appl…

1
[QA] Training Language Models on Synthetic Edit Sequences Improves Code Synthesis 7:53

5d ago7:53

7:53

The paper presents LintSeq, a synthetic data generation algorithm that refactors code into edit sequences, improving LLM performance in code synthesis and achieving state-of-the-art results with smaller models. https://arxiv.org/abs//2410.02749 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts…

1
Training Language Models on Synthetic Edit Sequences Improves Code Synthesis 18:46

5d ago18:46

18:46

The paper presents LintSeq, a synthetic data generation algorithm that refactors code into edit sequences, improving LLM performance in code synthesis and achieving state-of-the-art results with smaller models. https://arxiv.org/abs//2410.02749 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts…

1
From Sales to Software Testing - A Vietnamese Tester's Journey | Ep. [2] 4:41

5d ago4:41

4:41

Join host Charlie as he interviews Duy (Paul), a successful software tester from Vietnam 🇻🇳, in this episode of #TestIOOpenMic. Discover how Paul transitioned from an Area Sales Manager to a top performer on the Test IO platform. 🎬 Episode Highlights: - Paul's love for plot-twist movies like 'Shutter Island' - The journey from IT graduate to sales …

1
Automated Red Teaming with GOAT: the Generative Offensive Agent Tester 13:38

6d ago13:38

13:38

https://arxiv.org/abs//2410.01606 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…

1
[QA] Not All LLM Reasoners Are Created Equal 7:23

6d ago7:23

7:23

https://arxiv.org/abs//2410.01748 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…

1
Not All LLM Reasoners Are Created Equal 9:40

6d ago9:40

9:40

https://arxiv.org/abs//2410.01748 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…

1
[QA] Law of the Weakest Link: Cross Capabilities of Large Language Models 7:32

7d ago7:32

7:32

https://arxiv.org/abs//2409.19951 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…

1
Law of the Weakest Link: Cross Capabilities of Large Language Models 16:18

7d ago16:18

16:18

https://arxiv.org/abs//2409.19951 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…

1
[QA] Realistic Evaluation of Model Merging for Compositional Generalization 8:29

8d ago8:29

8:29

This paper evaluates various model merging methods for compositional generalization in image classification, generation, and NLP, clarifying their merits, requirements, and computational costs in a shared experimental setting. https://arxiv.org/abs//2409.18314 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_paper…

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Realistic Evaluation of Model Merging for Compositional Generalization 21:13

8d ago21:13

21:13

This paper evaluates various model merging methods for compositional generalization in image classification, generation, and NLP, clarifying their merits, requirements, and computational costs in a shared experimental setting. https://arxiv.org/abs//2409.18314 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_paper…

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The Rise of Unity Asia and the Evolution of Cloud Gaming with John Goodale of Jam.gg 49:35

8d ago49:35

49:35

John Goodale was employee #60 at Unity in 2010, where he launched and rapidly expanded Unity Asia. Under his leadership, he transformed Unity into the preferred platform for game developers across the region, driving exceptional growth and establishing the company as a dominant force in the gaming industry. Having also held key positions at Sega an…

1
[QA] Emu3: Next-Token Prediction is All You Need 7:43

9d ago7:43

7:43

Emu3 introduces a next-token prediction model for multimodal tasks, outperforming existing models and simplifying design by focusing on tokenization of images, text, and videos. https://arxiv.org/abs//2409.18869 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.apple.com/us/p…

1
Emu3: Next-Token Prediction is All You Need 17:28

9d ago17:28

17:28

Emu3 introduces a next-token prediction model for multimodal tasks, outperforming existing models and simplifying design by focusing on tokenization of images, text, and videos. https://arxiv.org/abs//2409.18869 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.apple.com/us/p…

1
[QA] MIO: A Foundation Model on Multimodal Tokens 8:38

9d ago8:38

8:38

MIO is a novel multimodal foundation model that excels in understanding and generating speech, text, images, and videos, outperforming existing models in any-to-any capabilities and diverse tasks. https://arxiv.org/abs//2409.17692 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podc…

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MIO: A Foundation Model on Multimodal Tokens 19:09

9d ago19:09

19:09

MIO is a novel multimodal foundation model that excels in understanding and generating speech, text, images, and videos, outperforming existing models in any-to-any capabilities and diverse tasks. https://arxiv.org/abs//2409.17692 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podc…

1
[QA] A Preliminary Study of o1 in Medicine: Are We Closer to an AI Doctor ? 7:52

10d ago7:52

7:52

The paper evaluates OpenAI's o1 model in medical scenarios, highlighting its enhanced reasoning and accuracy over GPT-4, while also identifying weaknesses and releasing data for further research. https://arxiv.org/abs//2409.15277 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podca…

1
A Preliminary Study of o1 in Medicine: Are We Closer to an AI Doctor ? 8:52

10d ago8:52

8:52

The paper evaluates OpenAI's o1 model in medical scenarios, highlighting its enhanced reasoning and accuracy over GPT-4, while also identifying weaknesses and releasing data for further research. https://arxiv.org/abs//2409.15277 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podca…

1
[QA] Logic-of-Thought: Injecting Logic into Contexts for Full Reasoning in Large Language Models 8:44

10d ago8:44

8:44

The Logic-of-Thought (LoT) prompting method enhances logical reasoning in Large Language Models by integrating propositional logic, significantly improving performance across various reasoning tasks. https://arxiv.org/abs//2409.17539 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://p…

1
Logic-of-Thought: Injecting Logic into Contexts for Full Reasoning in Large Language Models 16:05

10d ago16:05

16:05

The Logic-of-Thought (LoT) prompting method enhances logical reasoning in Large Language Models by integrating propositional logic, significantly improving performance across various reasoning tasks. https://arxiv.org/abs//2409.17539 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://p…

1
[QA] Making Text Embedders Few-Shot Learners 7:45

11d ago7:45

7:45

We propose bge-en-icl, a model leveraging in-context learning in LLMs for high-quality text embeddings, achieving state-of-the-art performance on MTEB and AIR-Bench benchmarks. https://arxiv.org/abs//2409.15700 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.apple.com/us/po…

1
Making Text Embedders Few-Shot Learners 16:11

11d ago16:11

16:11

We propose bge-en-icl, a model leveraging in-context learning in LLMs for high-quality text embeddings, achieving state-of-the-art performance on MTEB and AIR-Bench benchmarks. https://arxiv.org/abs//2409.15700 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.apple.com/us/po…

1
[QA] Programming Every Example: Lifting Pre-training Data Quality Like Experts at Scale 6:45

11d ago6:45

6:45

The paper introduces PROX, a framework enabling small language models to refine data effectively, outperforming human-crafted methods and enhancing efficiency in LLM pre-training across various benchmarks. https://arxiv.org/abs//2409.17115 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: htt…

1
Programming Every Example: Lifting Pre-training Data Quality Like Experts at Scale 8:57

11d ago8:57

8:57

The paper introduces PROX, a framework enabling small language models to refine data effectively, outperforming human-crafted methods and enhancing efficiency in LLM pre-training across various benchmarks. https://arxiv.org/abs//2409.17115 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: htt…

1
[QA] Infer Human's Intentions Before Following Natural Language Instruction 8:18

12d ago8:18

8:18

The FISER framework enhances AI's ability to follow ambiguous human instructions by inferring intentions, outperforming traditional methods in collaborative tasks, particularly on the HandMeThat benchmark. https://arxiv.org/abs//2409.18073 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: htt…

1
Infer Human's Intentions Before Following Natural Language Instruction 27:36

12d ago27:36

27:36

The FISER framework enhances AI's ability to follow ambiguous human instructions by inferring intentions, outperforming traditional methods in collaborative tasks, particularly on the HandMeThat benchmark. https://arxiv.org/abs//2409.18073 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: htt…

1
[QA] MaskLLM: Learnable Semi-Structured Sparsity for Large Language Models 7:05

12d ago7:05

7:05

This paper presents a learnable pruning method for Large Language Models, achieving efficient N:M sparsity, improved mask quality, and transferability across tasks, outperforming existing techniques in empirical evaluations. https://arxiv.org/abs//2409.17481 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers …

1
MaskLLM: Learnable Semi-Structured Sparsity for Large Language Models 15:10

12d ago15:10

15:10

This paper presents a learnable pruning method for Large Language Models, achieving efficient N:M sparsity, improved mask quality, and transferability across tasks, outperforming existing techniques in empirical evaluations. https://arxiv.org/abs//2409.17481 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers …

1
[QA] Counterfactual Token Generation in Large Language Models 7:53

13d ago7:53

7:53

This paper presents a method to enable large language models to perform counterfactual token generation, enhancing their capabilities without fine-tuning, and applying it for bias detection. https://arxiv.org/abs//2409.17027 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.a…

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Counterfactual Token Generation in Large Language Models 14:52

13d ago14:52

14:52

This paper presents a method to enable large language models to perform counterfactual token generation, enhancing their capabilities without fine-tuning, and applying it for bias detection. https://arxiv.org/abs//2409.17027 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.a…

1
[QA] Characterizing stable regions in the residual stream of LLMs 7:45

13d ago7:45

7:45

The paper identifies stable regions in Transformers' residual streams, showing insensitivity to small changes but high sensitivity at boundaries, aligning with semantic distinctions and clustering similar prompts. https://arxiv.org/abs//2409.17113 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podca…

1
Characterizing stable regions in the residual stream of LLMs 5:26

13d ago5:26

5:26

The paper identifies stable regions in Transformers' residual streams, showing insensitivity to small changes but high sensitivity at boundaries, aligning with semantic distinctions and clustering similar prompts. https://arxiv.org/abs//2409.17113 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podca…

1
[QA] Watch Your Steps: Observable and Modular Chains of Thought 7:30

14d ago7:30

7:30

We introduce Program Trace Prompting, enhancing chain of thought explanations with formal syntax, improving observability, and enabling analysis of reasoning errors across diverse tasks in the BIG-Bench Hard benchmark. https://arxiv.org/abs//2409.15359 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple …

1
Watch Your Steps: Observable and Modular Chains of Thought 29:35

14d ago29:35

29:35

We introduce Program Trace Prompting, enhancing chain of thought explanations with formal syntax, improving observability, and enabling analysis of reasoning errors across diverse tasks in the BIG-Bench Hard benchmark. https://arxiv.org/abs//2409.15359 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple …

1
[QA] Seeing Faces in Things: A Model and Dataset for Pareidolia 7:38

14d ago7:38

7:38

This paper explores face pareidolia in computer vision, presenting a dataset of annotated images and analyzing the differences in face detection between humans and machines. https://arxiv.org/abs//2409.16143 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.apple.com/us/podca…

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