Large Language Models

GPT, Claude, Gemini, and other LLMs

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Anthropic launches Claude Design, a new product for creating quick visuals | TechCrunch
Llms

Anthropic launches Claude Design, a new product for creating quick visuals | TechCrunch

The company says Claude Design is intended to help people like founders and product managers without a design background share their idea...

TechCrunch - AI · 4 min ·
Llms

Stories of bad AI workplace implementation

Anyone have a story about how AI was implemented at their workplace and it going horribly wrong. At my job they full-trust gave everyone ...

Reddit - Artificial Intelligence · 1 min ·
Llms

Opus 4.7 is terrible, and Anthropic has completely dropped the ball

Tried posting this in r/ClaudeAI but it got auto-removed, and I was told to post it in the "Bugs Megathread." Don't really think it shoul...

Reddit - Artificial Intelligence · 1 min ·

All Content

[2603.04480] AbAffinity: A Large Language Model for Predicting Antibody Binding Affinity against SARS-CoV-2
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[2603.04480] AbAffinity: A Large Language Model for Predicting Antibody Binding Affinity against SARS-CoV-2

Abstract page for arXiv paper 2603.04480: AbAffinity: A Large Language Model for Predicting Antibody Binding Affinity against SARS-CoV-2

arXiv - Machine Learning · 3 min ·
[2603.04466] Act-Observe-Rewrite: Multimodal Coding Agents as In-Context Policy Learners for Robot Manipulation
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[2603.04466] Act-Observe-Rewrite: Multimodal Coding Agents as In-Context Policy Learners for Robot Manipulation

Abstract page for arXiv paper 2603.04466: Act-Observe-Rewrite: Multimodal Coding Agents as In-Context Policy Learners for Robot Manipulation

arXiv - Machine Learning · 3 min ·
[2603.05232] SlideSparse: Fast and Flexible (2N-2):2N Structured Sparsity
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[2603.05232] SlideSparse: Fast and Flexible (2N-2):2N Structured Sparsity

Abstract page for arXiv paper 2603.05232: SlideSparse: Fast and Flexible (2N-2):2N Structured Sparsity

arXiv - Machine Learning · 3 min ·
[2603.04972] Functionality-Oriented LLM Merging on the Fisher--Rao Manifold
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[2603.04972] Functionality-Oriented LLM Merging on the Fisher--Rao Manifold

Abstract page for arXiv paper 2603.04972: Functionality-Oriented LLM Merging on the Fisher--Rao Manifold

arXiv - Machine Learning · 3 min ·
[2603.04956] WaterSIC: information-theoretically (near) optimal linear layer quantization
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[2603.04956] WaterSIC: information-theoretically (near) optimal linear layer quantization

Abstract page for arXiv paper 2603.04956: WaterSIC: information-theoretically (near) optimal linear layer quantization

arXiv - Machine Learning · 3 min ·
[2603.04948] $\nabla$-Reasoner: LLM Reasoning via Test-Time Gradient Descent in Latent Space
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[2603.04948] $\nabla$-Reasoner: LLM Reasoning via Test-Time Gradient Descent in Latent Space

Abstract page for arXiv paper 2603.04948: $\nabla$-Reasoner: LLM Reasoning via Test-Time Gradient Descent in Latent Space

arXiv - Machine Learning · 4 min ·
[2603.04898] U-Parking: Distributed UWB-Assisted Autonomous Parking System with Robust Localization and Intelligent Planning
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[2603.04898] U-Parking: Distributed UWB-Assisted Autonomous Parking System with Robust Localization and Intelligent Planning

Abstract page for arXiv paper 2603.04898: U-Parking: Distributed UWB-Assisted Autonomous Parking System with Robust Localization and Inte...

arXiv - Machine Learning · 3 min ·
[2603.04851] Why Is RLHF Alignment Shallow? A Gradient Analysis
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[2603.04851] Why Is RLHF Alignment Shallow? A Gradient Analysis

Abstract page for arXiv paper 2603.04851: Why Is RLHF Alignment Shallow? A Gradient Analysis

arXiv - Machine Learning · 3 min ·
[2603.04692] Engineering Regression Without Real-Data Training: Domain Adaptation for Tabular Foundation Models Using Multi-Dataset Embeddings
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[2603.04692] Engineering Regression Without Real-Data Training: Domain Adaptation for Tabular Foundation Models Using Multi-Dataset Embeddings

Abstract page for arXiv paper 2603.04692: Engineering Regression Without Real-Data Training: Domain Adaptation for Tabular Foundation Mod...

arXiv - Machine Learning · 4 min ·
[2603.04606] PDE foundation model-accelerated inverse estimation of system parameters in inertial confinement fusion
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[2603.04606] PDE foundation model-accelerated inverse estimation of system parameters in inertial confinement fusion

Abstract page for arXiv paper 2603.04606: PDE foundation model-accelerated inverse estimation of system parameters in inertial confinemen...

arXiv - Machine Learning · 4 min ·
[2603.04545] An LLM-Guided Query-Aware Inference System for GNN Models on Large Knowledge Graphs
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[2603.04545] An LLM-Guided Query-Aware Inference System for GNN Models on Large Knowledge Graphs

Abstract page for arXiv paper 2603.04545: An LLM-Guided Query-Aware Inference System for GNN Models on Large Knowledge Graphs

arXiv - Machine Learning · 4 min ·
[2603.04478] Standing on the Shoulders of Giants: Rethinking EEG Foundation Model Pretraining via Multi-Teacher Distillation
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[2603.04478] Standing on the Shoulders of Giants: Rethinking EEG Foundation Model Pretraining via Multi-Teacher Distillation

Abstract page for arXiv paper 2603.04478: Standing on the Shoulders of Giants: Rethinking EEG Foundation Model Pretraining via Multi-Teac...

arXiv - Machine Learning · 4 min ·
[2602.07075] LatentChem: From Textual CoT to Latent Thinking in Chemical Reasoning
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[2602.07075] LatentChem: From Textual CoT to Latent Thinking in Chemical Reasoning

Abstract page for arXiv paper 2602.07075: LatentChem: From Textual CoT to Latent Thinking in Chemical Reasoning

arXiv - Machine Learning · 4 min ·
[2601.23236] YuriiFormer: A Suite of Nesterov-Accelerated Transformers
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[2601.23236] YuriiFormer: A Suite of Nesterov-Accelerated Transformers

Abstract page for arXiv paper 2601.23236: YuriiFormer: A Suite of Nesterov-Accelerated Transformers

arXiv - Machine Learning · 3 min ·
[2601.21149] Mobility-Embedded POIs: Learning What A Place Is and How It Is Used from Human Movement
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[2601.21149] Mobility-Embedded POIs: Learning What A Place Is and How It Is Used from Human Movement

Abstract page for arXiv paper 2601.21149: Mobility-Embedded POIs: Learning What A Place Is and How It Is Used from Human Movement

arXiv - Machine Learning · 4 min ·
[2601.16333] Where is the multimodal goal post? On the Ability of Foundation Models to Recognize Contextually Important Moments
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[2601.16333] Where is the multimodal goal post? On the Ability of Foundation Models to Recognize Contextually Important Moments

Abstract page for arXiv paper 2601.16333: Where is the multimodal goal post? On the Ability of Foundation Models to Recognize Contextuall...

arXiv - AI · 4 min ·
[2601.14327] Yuan3.0 Ultra: A Trillion-Parameter Enterprise-Oriented MoE LLM
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[2601.14327] Yuan3.0 Ultra: A Trillion-Parameter Enterprise-Oriented MoE LLM

Abstract page for arXiv paper 2601.14327: Yuan3.0 Ultra: A Trillion-Parameter Enterprise-Oriented MoE LLM

arXiv - Machine Learning · 4 min ·
[2601.11527] "What if she doesn't feel the same?" What Happens When We Ask AI for Relationship Advice
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[2601.11527] "What if she doesn't feel the same?" What Happens When We Ask AI for Relationship Advice

Abstract page for arXiv paper 2601.11527: "What if she doesn't feel the same?" What Happens When We Ask AI for Relationship Advice

arXiv - AI · 3 min ·
[2601.11063] EmboTeam: Grounding LLM Reasoning into Reactive Behavior Trees via PDDL for Embodied Multi-Robot Collaboration
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[2601.11063] EmboTeam: Grounding LLM Reasoning into Reactive Behavior Trees via PDDL for Embodied Multi-Robot Collaboration

Abstract page for arXiv paper 2601.11063: EmboTeam: Grounding LLM Reasoning into Reactive Behavior Trees via PDDL for Embodied Multi-Robo...

arXiv - Machine Learning · 4 min ·
[2601.08393] Controlled LLM Training on Spectral Sphere
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[2601.08393] Controlled LLM Training on Spectral Sphere

Abstract page for arXiv paper 2601.08393: Controlled LLM Training on Spectral Sphere

arXiv - Machine Learning · 3 min ·
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