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www.mixedbread.com/blog/toast-1

Introducing Toast 1

Meet Toast 1, Mixedbread's search agent for knowledge-intensive tasks, matching or outperforming Claude Opus 5 and GPT-5.6 Sol while being up to 10× cheaper and 12× faster.

github.com/sandipanrakshit34/Mars-Crater-Detection-and-Segmentation-with-MaskRCNN

sandipanrakshit34/Mars-Crater-Detection-and-Segmentation-with-MaskRCNN

Detection of craters on planetary surface is very crucial for the better understanding of planet topography. It is also important for the selection of landing sites of various lander mission, path planning for rover missions. This project is about application of deep learning met…

arxiv.org/abs/1910.02446v1

Modal Logic via Global Consequence

In modal logic, semantic consequence is usually defined locally by truth preservation at all worlds in all models (with respect to a class of frames). It can also be defined globally by truth preservation in all models (with respect to a class of fra...

arxiv.org/abs/2102.02881v1

Aggregating Bipolar Opinions (With Appendix)

We introduce a novel method to aggregate Bipolar Argumentation (BA) Frameworks expressing opinions by different parties in debates. We use Bipolar Assumption-based Argumentation (ABA) as an all-encompassing formalism for BA under different semantics....

arxiv.org/abs/1004.2159v2

Algebraic Proofs over Noncommutative Formulas

We study possible formulations of algebraic propositional proof systems operating with noncommutative formulas. We observe that a simple formulation gives rise to systems at least as strong as Frege---yielding a semantic way to define a Cook-Reckhow...

github.com/danyQe/codebase-mcp

danyQe/codebase-mcp

Open-source AI development assistant via Model Context Protocol (MCP). Turn Claude or any LLM into your personal coding assistant. Privacy-first with local semantic search, AI-assisted editing, persistent memory, and quality-checked code generation. Built for Python & React. Free…

arxiv.org/abs/2309.04105v1

Weakly Supervised Point Clouds Transformer for 3D Object Detection

The annotation of 3D datasets is required for semantic-segmentation and object detection in scene understanding. In this paper we present a framework for the weakly supervision of a point clouds transformer that is used for 3D object detection. The a...

arxiv.org/abs/2302.11157v2

FiNER-ORD: Financial Named Entity Recognition Open Research Dataset

Over the last two decades, the development of the CoNLL-2003 named entity recognition (NER) dataset has helped enhance the capabilities of deep learning and natural language processing (NLP). The finance domain, characterized by its unique semantic a...

arxiv.org/abs/1105.4395v1

Default-all is dangerous!

We show that the default-all propagation scheme for database annotations is dangerous. Dangerous here means that it can propagate annotations to the query output which are semantically irrelevant to the query the user asked. This is the result of con...

www.bing.com/ck/a?!&&p=04048ae15243fe36a24dc94eb38c52487bcf022009f91a79a21af6265cb5a008JmltdHM9MTc3Mjg0MTYwMA&ptn=3&ver=2&hsh=4&fclid=0bf3fc8e-e1cc-627a-0007-eb98e09f63e8&u=a1aHR0cHM6Ly9lbmdsaXNoLnN0YWNrZXhjaGFuZ2UuY29tL3F1ZXN0aW9ucy80NTU5MjEvY2FuLWktdXNlLXdvcnNlLXdvcnN0LWluc3RlYWQtb2YtYmFkZGVyLWJhZGRlc3Q&ntb=1

Can I use "worse, worst" instead of "badder, baddest"?

Jul 16, 2018 · Ooh! - You are awful! I don't think I've ever encountered this kind of "slang semantic inversion" with worse, worst. But I'm an ole fart, so I think badder, baddest = better, best just sounds …

github.com/qubvel-org/segmentation_models.pytorch

qubvel-org/segmentation_models.pytorch

Semantic segmentation models with 500+ pretrained convolutional and transformer-based backbones. (⭐ 11379)

arxiv.org/abs/1608.00869v4

SimVerb-3500: A Large-Scale Evaluation Set of Verb Similarity

Verbs play a critical role in the meaning of sentences, but these ubiquitous words have received little attention in recent distributional semantics research. We introduce SimVerb-3500, an evaluation resource that provides human ratings for the simil...