Large Language Models

GPT, Claude, Gemini, and other LLMs

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Llms

main skill in software engineering in 2026 is knowing what to ask Claude, not knowing how to code. and I can’t decide if that’s depressing or just the next abstraction layer.

Been writing code professionally for 8+ years. I’m now mass spending more time describing features in plain english than writing actual c...

Reddit - Artificial Intelligence · 1 min ·
Llms

Can we even achieve AGI with LLMs, why do AI bros still believe we can?

I've heard mixed discussions around this. Although not much evidence just rhetoric from the AGI will come from LLMs camp. submitted by /u...

Reddit - Artificial Intelligence · 1 min ·
Llms

You can now prompt OpenClaw into existence. fully 1st party on top of Claude Code

OpenClaw is basically banned from Claude ¯_(ツ)_/¯ Claude Code has Telegram support.. so what if we just, made it always stay on? turns ou...

Reddit - Artificial Intelligence · 1 min ·

All Content

[2603.04466] Act-Observe-Rewrite: Multimodal Coding Agents as In-Context Policy Learners for Robot Manipulation
Llms

[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
Llms

[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
Llms

[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
Llms

[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
Llms

[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
Llms

[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
Llms

[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
Llms

[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
Llms

[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
Llms

[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
Llms

[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
Llms

[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
Llms

[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
Llms

[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
Llms

[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
Llms

[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
Llms

[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
Llms

[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
Llms

[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 ·
[2601.04548] Identifying Good and Bad Neurons for Task-Level Controllable LLMs
Llms

[2601.04548] Identifying Good and Bad Neurons for Task-Level Controllable LLMs

Abstract page for arXiv paper 2601.04548: Identifying Good and Bad Neurons for Task-Level Controllable LLMs

arXiv - AI · 4 min ·
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