Large Language Models

GPT, Claude, Gemini, and other LLMs

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Llms

Uber burned its entire 2026 AI coding budget in 4 months - $500-2k per engineer per month

Uber deployed Claude Code to engineers in December 2025. By April 2026, the company had consumed its entire annual AI budget - not becaus...

Reddit - Artificial Intelligence · 1 min ·
Llms

Should agent architectures be fixed… or generated at runtime? [D]

I’m sharing a research prototype exploring a different approach to LLM-based multi-agent systems. Most current agent frameworks rely on f...

Reddit - Machine Learning · 1 min ·
Llms

What is the basic minimum while you prompt

I have realised Claude answers as best as you prompt it. And I suck at it. 😂 I have tried role playing you are top 1% etc and adding cons...

Reddit - Artificial Intelligence · 1 min ·

All Content

[2504.02010] When Reasoning Meets Compression: Understanding the Effects of LLMs Compression on Large Reasoning Models
Llms

[2504.02010] When Reasoning Meets Compression: Understanding the Effects of LLMs Compression on Large Reasoning Models

Abstract page for arXiv paper 2504.02010: When Reasoning Meets Compression: Understanding the Effects of LLMs Compression on Large Reason...

arXiv - Machine Learning · 4 min ·
[2503.12988] ROMA: a Read-Only-Memory-based Accelerator for QLoRA-based On-Device LLM
Llms

[2503.12988] ROMA: a Read-Only-Memory-based Accelerator for QLoRA-based On-Device LLM

Abstract page for arXiv paper 2503.12988: ROMA: a Read-Only-Memory-based Accelerator for QLoRA-based On-Device LLM

arXiv - AI · 4 min ·
[2503.21735] GateLens: A Reasoning-Enhanced LLM Agent for Automotive Software Release Analytics
Llms

[2503.21735] GateLens: A Reasoning-Enhanced LLM Agent for Automotive Software Release Analytics

Abstract page for arXiv paper 2503.21735: GateLens: A Reasoning-Enhanced LLM Agent for Automotive Software Release Analytics

arXiv - AI · 4 min ·
[2503.06749] Vision-R1: Incentivizing Reasoning Capability in Multimodal Large Language Models
Llms

[2503.06749] Vision-R1: Incentivizing Reasoning Capability in Multimodal Large Language Models

Abstract page for arXiv paper 2503.06749: Vision-R1: Incentivizing Reasoning Capability in Multimodal Large Language Models

arXiv - Machine Learning · 4 min ·
[2503.06238] Token-Efficient Item Representation via Images for LLM Recommender Systems
Llms

[2503.06238] Token-Efficient Item Representation via Images for LLM Recommender Systems

Abstract page for arXiv paper 2503.06238: Token-Efficient Item Representation via Images for LLM Recommender Systems

arXiv - AI · 4 min ·
[2404.08480] Using ChatGPT for Data Science Analyses
Llms

[2404.08480] Using ChatGPT for Data Science Analyses

Abstract page for arXiv paper 2404.08480: Using ChatGPT for Data Science Analyses

arXiv - Machine Learning · 3 min ·
[2503.03862] Not-Just-Scaling Laws: Towards a Better Understanding of the Downstream Impact of Language Model Design Decisions
Llms

[2503.03862] Not-Just-Scaling Laws: Towards a Better Understanding of the Downstream Impact of Language Model Design Decisions

Abstract page for arXiv paper 2503.03862: Not-Just-Scaling Laws: Towards a Better Understanding of the Downstream Impact of Language Mode...

arXiv - AI · 4 min ·
[2503.02879] Wikipedia in the Era of LLMs: Evolution and Risks
Llms

[2503.02879] Wikipedia in the Era of LLMs: Evolution and Risks

Abstract page for arXiv paper 2503.02879: Wikipedia in the Era of LLMs: Evolution and Risks

arXiv - Machine Learning · 4 min ·
[2502.12179] Sparse Shift Autoencoders for Identifying Concepts from Large Language Model Activations
Llms

[2502.12179] Sparse Shift Autoencoders for Identifying Concepts from Large Language Model Activations

Abstract page for arXiv paper 2502.12179: Sparse Shift Autoencoders for Identifying Concepts from Large Language Model Activations

arXiv - Machine Learning · 4 min ·
[2502.04326] WorldSense: Evaluating Real-world Omnimodal Understanding for Multimodal LLMs
Llms

[2502.04326] WorldSense: Evaluating Real-world Omnimodal Understanding for Multimodal LLMs

Abstract page for arXiv paper 2502.04326: WorldSense: Evaluating Real-world Omnimodal Understanding for Multimodal LLMs

arXiv - AI · 4 min ·
[2412.19496] Multi-PA: A Multi-perspective Benchmark on Privacy Assessment for Large Vision-Language Models
Llms

[2412.19496] Multi-PA: A Multi-perspective Benchmark on Privacy Assessment for Large Vision-Language Models

Abstract page for arXiv paper 2412.19496: Multi-PA: A Multi-perspective Benchmark on Privacy Assessment for Large Vision-Language Models

arXiv - AI · 4 min ·
[2411.03292] Interaction2Code: Benchmarking MLLM-based Interactive Webpage Code Generation from Interactive Prototyping
Llms

[2411.03292] Interaction2Code: Benchmarking MLLM-based Interactive Webpage Code Generation from Interactive Prototyping

Abstract page for arXiv paper 2411.03292: Interaction2Code: Benchmarking MLLM-based Interactive Webpage Code Generation from Interactive ...

arXiv - AI · 4 min ·
[2410.13648] SimpleToM: Exposing the Gap between Explicit ToM Inference and Implicit ToM Application in LLMs
Llms

[2410.13648] SimpleToM: Exposing the Gap between Explicit ToM Inference and Implicit ToM Application in LLMs

Abstract page for arXiv paper 2410.13648: SimpleToM: Exposing the Gap between Explicit ToM Inference and Implicit ToM Application in LLMs

arXiv - AI · 4 min ·
[2410.05254] GLEE: A Unified Framework and Benchmark for Language-based Economic Environments
Llms

[2410.05254] GLEE: A Unified Framework and Benchmark for Language-based Economic Environments

Abstract page for arXiv paper 2410.05254: GLEE: A Unified Framework and Benchmark for Language-based Economic Environments

arXiv - Machine Learning · 4 min ·
[2603.02080] From Pixels to Patches: Pooling Strategies for Earth Embeddings
Llms

[2603.02080] From Pixels to Patches: Pooling Strategies for Earth Embeddings

Abstract page for arXiv paper 2603.02080: From Pixels to Patches: Pooling Strategies for Earth Embeddings

arXiv - Machine Learning · 3 min ·
[2603.02026] Learning to Read Where to Look: Disease-Aware Vision-Language Pretraining for 3D CT
Llms

[2603.02026] Learning to Read Where to Look: Disease-Aware Vision-Language Pretraining for 3D CT

Abstract page for arXiv paper 2603.02026: Learning to Read Where to Look: Disease-Aware Vision-Language Pretraining for 3D CT

arXiv - Machine Learning · 4 min ·
[2603.01834] Probing Materials Knowledge in LLMs: From Latent Embeddings to Reliable Predictions
Llms

[2603.01834] Probing Materials Knowledge in LLMs: From Latent Embeddings to Reliable Predictions

Abstract page for arXiv paper 2603.01834: Probing Materials Knowledge in LLMs: From Latent Embeddings to Reliable Predictions

arXiv - Machine Learning · 3 min ·
[2602.11661] Quark Medical Alignment: A Holistic Multi-Dimensional Alignment and Collaborative Optimization Paradigm
Llms

[2602.11661] Quark Medical Alignment: A Holistic Multi-Dimensional Alignment and Collaborative Optimization Paradigm

Abstract page for arXiv paper 2602.11661: Quark Medical Alignment: A Holistic Multi-Dimensional Alignment and Collaborative Optimization ...

arXiv - AI · 4 min ·
[2602.10625] To Think or Not To Think, That is The Question for Large Reasoning Models in Theory of Mind Tasks
Llms

[2602.10625] To Think or Not To Think, That is The Question for Large Reasoning Models in Theory of Mind Tasks

Abstract page for arXiv paper 2602.10625: To Think or Not To Think, That is The Question for Large Reasoning Models in Theory of Mind Tasks

arXiv - AI · 4 min ·
[2602.09794] Learning Global Hypothesis Space for Enhancing Synergistic Reasoning Chain
Llms

[2602.09794] Learning Global Hypothesis Space for Enhancing Synergistic Reasoning Chain

Abstract page for arXiv paper 2602.09794: Learning Global Hypothesis Space for Enhancing Synergistic Reasoning Chain

arXiv - AI · 4 min ·
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