scale
PulseAugur coverage of scale — every cluster mentioning scale across labs, papers, and developer communities, ranked by signal.
- developed alphaXiv 95%
- developed DagsHub 90%
- developed by ScienceCast 90%
- developed ScienceCast 90%
- developed CatalyzeX 90%
- developed Gotit.pub 90%
- instance of ScienceCast 90%
- developed by DagsHub 90%
- instance of DagsHub 70%
- instance of Gotit.pub 70%
- instance of alphaXiv 70%
- instance of CatalyzeX 70%
- 2026-10-28 regulatory noyb.eu filed five complaints in four countries against Scale AI for alleged illegal worker surveillance and data collection. source
5 day(s) with sentiment data
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New SCALE method enables real-time latent communication for cyber-physical agents
Researchers have developed SCALE, a novel method for real-time latent communication specifically designed for cyber-physical agents. Unlike previous approaches focused on LLMs, SCALE addresses the bandwidth and deadline…
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noyb.eu files 5 complaints against Scale AI for worker surveillance
The organization noyb.eu has filed five complaints across four countries against the AI training company Scale. These complaints allege that Scale illegally surveils its workers, collecting extensive personal data and r…
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llama.cpp updates, AI code tools, hallucination mitigation research, and LLM neutrality discussed
The llama.cpp project has released updates focusing on performance and compatibility across various operating systems and hardware. Release b11977 addresses issues with the ggml-openvino integration for SCALE operations…
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New SCALE method enhances AI out-of-distribution detection without training data
Researchers have developed a new method called Anti-coherence Regularized Absolute Scaling (SCALE) to improve out-of-distribution (OOD) detection in AI safety. This method addresses limitations in existing SCALE techniq…
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New SCALE framework enhances long-horizon language agent performance
Researchers have developed a new reinforcement learning framework called SCALE, designed to improve the performance of long-horizon language agents. SCALE addresses the challenge of assigning credit to intermediate acti…
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New SCALE framework improves visual generation without Classifier-Free Guidance
Researchers have introduced SCALE, a novel training framework designed to enhance visual generation quality without the computational overhead of traditional Classifier-Free Guidance (CFG). SCALE utilizes a self-contras…
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New SMAT method enhances AI model merging with minimal overhead
Researchers have developed SMAT (Simple Merge-Aware Training), a novel method to improve the performance of merged AI models. SMAT addresses limitations in existing merge-aware training techniques by simulating common m…
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Transformers learn symmetries in geometric machine learning, study finds
A new research paper explores how Transformer architectures learn to represent symmetries in geometric machine learning tasks, specifically focusing on point cloud datasets. The study identifies an order of learnability…
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New method improves pathology model calibration without multi-annotator labels
Researchers have developed a new method called Synthetic Agreement Calibration to improve the calibration of foundation models used in computational pathology. This technique addresses the issue where models may be over…
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AI tutoring system DeepEdu-v1 launched for Vietnamese education
Researchers have developed DeepEdu-v1, an AI tutoring system designed for Vietnamese education that addresses data sovereignty and local content challenges. Unlike cloud-based models like ChatGPT, DeepEdu-v1 keeps data …
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New SCALE method enhances SFT by controlling feature usage
Researchers have introduced SCALE (Selective Control of Adaptation via Local Entropy), a novel method for supervised fine-tuning (SFT) that aims to improve model adaptation by controlling how learned features are used. …
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Together AI outlines strategy for migrating to open-source models
Together AI's blog post outlines a strategy for migrating from closed-source to open-source AI models, emphasizing that such migrations can be faster and less complex than traditional ones, especially when utilizing man…
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New AI model predicts cellular responses from unpaired data
Researchers have developed SCALE, a novel conditional transport model designed to predict cellular responses to perturbations. Unlike previous methods that required paired control and treated cell populations, SCALE can…
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AfterQuery becomes YC's fastest unicorn at $3.2B valuation
AI training data startup AfterQuery has achieved unicorn status with a valuation of $3.2 billion, marking it as Y Combinator's fastest-ever to reach this milestone. This rapid ascent, occurring just five months after a …
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Harvey Tenet: New Legal Agent Model Leverages Kimi K3 and Fireworks
Harvey has unveiled Harvey Tenet, a new research preview model specifically designed for long-horizon legal tasks. This model is built upon the Kimi K3 base and enhanced through asynchronous reinforcement learning using…
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NVIDIA hires 109 Poolside AI staff in unique licensing deal
Poolside, a company known for its AI model factory, has undergone a significant shift involving NVIDIA and its founder Jensen Huang. Instead of a traditional acquisition, NVIDIA has licensed Poolside's technology and hi…
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New SCALE method enhances AI planning by improving latent space geometry
Researchers have developed SCALE (State-Calibrated Latent Embeddings), a new method to improve planning in joint-embedding predictive world models. SCALE enhances the geometric properties of latent representations, simi…
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New frameworks leverage LLMs and embeddings to expand scientific taxonomies · 2 sources tracked
Two new research papers introduce frameworks for enhancing scientific taxonomies using Large Language Models (LLMs) and embeddings. The first, ReLTEx, focuses on reliable LLM-based taxonomy expansion by combining LLM ge…
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New AI framework tackles semiconductor design rule violations
Researchers have developed SCALE, a novel framework designed to address complex design rule violations in semiconductor manufacturing at advanced sub-2nm nodes. The system utilizes a self-supervised layout-generation st…
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AI model quality shifts from scale to embedded reasoning
The era of AI model quality being solely dependent on scale is ending. Future advancements will focus on embedding reasoning directly into model weights, rather than relying on external tools like scratchpads or complex…