56,966 blogs · [ { "id": "01a08796-fa1f-72f9-9f2c-71d46f78f8ab", "title": "Code Actions as Tools", "url": "https://krasserm.github.io/2025/12/16/code-actions/", "published_at": "2025-12-16T00:00:00+00:00" }, { "id": "01a08796-fa1f-72f9-9f2c-71d46faf5bf3", "title": "From single-user to multi-party conversational AI", "url": "https://krasserm.github.io/2025/11/12/multi-party-ai/", "published_at": "2025-11-12T00:00:00+00:00" }, { "id": "01a08796-fa1f-72f9-9f2c-71d46fbde88f", "title": "DeepSeek-R1 agents with code actions", "url": "https://krasserm.github.io/2025/02/05/deepseek-r1-agent/", "published_at": "2025-02-05T00:00:00+00:00" }, { "id": "01a08796-fa1f-72f9-9f2c-71d46ffbce8e", "title": "Impact of prompt masking on LLM agent step planning performance", "url": "https://krasserm.github.io/2024/06/26/planner-prompt-masking/", "published_at": "2024-06-26T00:00:00+00:00" }, { "id": "01a08796-fa1f-72f9-9f2c-71d470e60965", "title": "Planner fine-tuning on synthetic agent trajectories", "url": "https://krasserm.github.io/2024/05/31/planner-fine-tuning/", "published_at": "2024-05-31T00:00:00+00:00" }, { "id": "01a08796-fa1f-72f9-9f2c-71d470ff5246", "title": "Separation of step planning concerns in ReAct-style LLM agents", "url": "https://krasserm.github.io/2024/03/06/modular-agent/", "published_at": "2024-03-06T00:00:00+00:00" }, { "id": "01a08796-fa1f-72f9-9f2c-71d4713ad274", "title": "Schema-guided generation with open LLMs", "url": "https://krasserm.github.io/2023/12/18/llm-json-mode/", "published_at": "2023-12-18T00:00:00+00:00" }, { "id": "01a08796-fa1f-72f9-9f2c-71d4717e2386", "title": "Schema-guided generation in LangChain agents", "url": "https://krasserm.github.io/2023/12/10/grammar-based-agents/", "published_at": "2023-12-10T00:00:00+00:00" }, { "id": "01a08796-fa1f-72f9-9f2c-71d4725ce100", "title": "Extending Visual ChatGPT with image search engines", "url": "https://krasserm.github.io/2023/04/03/visual-chatgpt-search/", "published_at": "2023-04-03T00:00:00+00:00" }, { "id": "01a08796-fa1f-72f9-9f2c-71d472e7268f", "title": "Training compute-optimal Perceiver AR language models", "url": "https://krasserm.github.io/2023/01/23/scaling-perceiver-ar/", "published_at": "2023-01-23T00:00:00+00:00" }, { "id": "01a08796-fa1f-72f9-9f2c-71d473cb4987", "title": "A gentle introduction to Rotary Position Embedding", "url": "https://krasserm.github.io/2022/12/13/rotary-position-embedding/", "published_at": "2022-12-13T00:00:00+00:00" }, { "id": "01a08796-fa1f-72f9-9f2c-71d474053aba", "title": "Using AWS SageMaker with minimal dependencies, part 2", "url": "https://krasserm.github.io/2022/02/26/sagemaker-fault-tolerance/", "published_at": "2022-02-26T00:00:00+00:00" }, { "id": "01a08796-fa1f-72f9-9f2c-71d47456ecce", "title": "Using AWS SageMaker with minimal dependencies, part 1", "url": "https://krasserm.github.io/2022/01/21/sagemaker-multi-node/", "published_at": "2022-01-21T00:00:00+00:00" }, { "id": "01a08796-fa1f-72f9-9f2c-71d47507e5aa", "title": "Sparse Gaussian processes", "url": "https://krasserm.github.io/2020/12/12/gaussian-processes-sparse/", "published_at": "2020-12-12T00:00:00+00:00" }, { "id": "01a08796-fa1f-72f9-9f2c-71d475287ffa", "title": "Gaussian processes for classification", "url": "https://krasserm.github.io/2020/11/04/gaussian-processes-classification/", "published_at": "2020-11-04T00:00:00+00:00" }, { "id": "01a08796-fa1f-72f9-9f2c-71d475beb86b", "title": "Reliable uncertainty estimates for neural network predictions", "url": "https://krasserm.github.io/2020/09/25/reliable-uncertainty-estimates/", "published_at": "2020-09-25T00:00:00+00:00" }, { "id": "01a08796-fa1f-72f9-9f2c-71d475f6f560", "title": "Latent variable models, part 2", "url": "https://krasserm.github.io/2019/12/17/latent-variable-models-part-2/", "published_at": "2019-12-17T00:00:00+00:00" }, { "id": "01a08796-fa1f-72f9-9f2c-71d4766c09bb", "title": "Latent variable models, part 1", "url": "https://krasserm.github.io/2019/11/21/latent-variable-models-part-1/", "published_at": "2019-11-21T00:00:00+00:00" }, { "id": "01a08796-fa1f-72f9-9f2c-71d476c15593", "title": "Single image super-resolution with deep neural networks", "url": "https://krasserm.github.io/2019/09/04/super-resolution/", "published_at": "2019-09-04T00:00:00+00:00" }, { "id": "01a08796-fa1f-72f9-9f2c-71d477772120", "title": "Variational inference in Bayesian neural networks", "url": "https://krasserm.github.io/2019/03/14/bayesian-neural-networks/", "published_at": "2019-03-14T00:00:00+00:00" } ] posts Claim your blog

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krasserm.github.io

2025

Code Actions as Tools original ↗

16 Dec 2025

From single-user to multi-party conversational AI original ↗

12 Nov 2025

DeepSeek-R1 agents with code actions original ↗

5 Feb 2025

2024

Impact of prompt masking on LLM agent step planning performance original ↗

26 Jun 2024

Planner fine-tuning on synthetic agent trajectories original ↗

31 May 2024

Separation of step planning concerns in ReAct-style LLM agents original ↗

6 Mar 2024

2023

Schema-guided generation with open LLMs original ↗

18 Dec 2023

Schema-guided generation in LangChain agents original ↗

10 Dec 2023

Extending Visual ChatGPT with image search engines original ↗

3 Apr 2023

Training compute-optimal Perceiver AR language models original ↗

23 Jan 2023

2022

A gentle introduction to Rotary Position Embedding original ↗

13 Dec 2022

Using AWS SageMaker with minimal dependencies, part 2 original ↗

26 Feb 2022

Using AWS SageMaker with minimal dependencies, part 1 original ↗

21 Jan 2022

2020

Sparse Gaussian processes original ↗

12 Dec 2020

Gaussian processes for classification original ↗

4 Nov 2020

Reliable uncertainty estimates for neural network predictions original ↗

25 Sept 2020

2019

Latent variable models, part 2 original ↗

17 Dec 2019

Latent variable models, part 1 original ↗

21 Nov 2019

Single image super-resolution with deep neural networks original ↗

4 Sept 2019

Variational inference in Bayesian neural networks original ↗

14 Mar 2019