Large Language Models

GPT, Claude, Gemini, and other LLMs

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Llms

We gave 45 psychological questionnaires to 50 LLMs. What we found was not “personality.”

What is the “personality” of an LLM? What actually differentiates models psychometrically? Since LLMs entered public use, researchers hav...

Reddit - Artificial Intelligence · 1 min ·
How to Disable Google's Gemini in Chrome | WIRED
Llms

How to Disable Google's Gemini in Chrome | WIRED

Chrome users were caught off guard by a 4-GB Google AI model baked into Chrome, sparking privacy concerns. The good news: You can easily ...

Wired - AI · 6 min ·
OpenAI introduces new 'Trusted Contact' safeguard for cases of possible self-harm | TechCrunch
Llms

OpenAI introduces new 'Trusted Contact' safeguard for cases of possible self-harm | TechCrunch

The company is expanding its efforts to protect ChatGPT users in cases where conversations may turn to self-harm.

TechCrunch - AI · 5 min ·

All Content

[2505.02872] Decoding Open-Ended Information Seeking Goals from Eye Movements in Reading
Llms

[2505.02872] Decoding Open-Ended Information Seeking Goals from Eye Movements in Reading

Abstract page for arXiv paper 2505.02872: Decoding Open-Ended Information Seeking Goals from Eye Movements in Reading

arXiv - AI · 4 min ·
[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 ·
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