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Llms

Is the Mirage Effect a bug, or is it Geometric Reconstruction in action? A framework for why VLMs perform better "hallucinating" than guessing, and what that may tell us about what's really inside these models

Last week, a team from Stanford and UCSF (Asadi, O'Sullivan, Fei-Fei Li, Euan Ashley et al.) dropped two companion papers. The first, MAR...

Reddit - Artificial Intelligence · 1 min ·
The Galaxy S26’s photo app can sloppify your memories | The Verge
Nlp

The Galaxy S26’s photo app can sloppify your memories | The Verge

Samsung’s S26 series offers some new AI photo editing capabilities to transform your photos. But where’s the line between acceptable edit...

The Verge - AI · 8 min ·
Llms

[D] The problem with comparing AI memory system benchmarks — different evaluation methods make scores meaningless

I've been reviewing how various AI memory systems evaluate their performance and noticed a fundamental issue with cross-system comparison...

Reddit - Machine Learning · 1 min ·

All Content

[2505.13109] FreeKV: Boosting KV Cache Retrieval for Efficient LLM Inference
Llms

[2505.13109] FreeKV: Boosting KV Cache Retrieval for Efficient LLM Inference

Abstract page for arXiv paper 2505.13109: FreeKV: Boosting KV Cache Retrieval for Efficient LLM Inference

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 ·
[2503.06238] 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 ·
[2503.04812] LLaVE: Large Language and Vision Embedding Models with Hardness-Weighted Contrastive Learning
Machine Learning

[2503.04812] LLaVE: Large Language and Vision Embedding Models with Hardness-Weighted Contrastive Learning

Abstract page for arXiv paper 2503.04812: LLaVE: Large Language and Vision Embedding Models with Hardness-Weighted Contrastive Learning

arXiv - Machine Learning · 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 ·
[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 ·
[2404.17768] Changing the Training Data Distribution to Reduce Simplicity Bias Improves In-distribution Generalization
Machine Learning

[2404.17768] Changing the Training Data Distribution to Reduce Simplicity Bias Improves In-distribution Generalization

Abstract page for arXiv paper 2404.17768: Changing the Training Data Distribution to Reduce Simplicity Bias Improves In-distribution Gene...

arXiv - Machine Learning · 4 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 ·
[2603.01986] Accurate, private, secure, federated U-statistics with higher degree
Nlp

[2603.01986] Accurate, private, secure, federated U-statistics with higher degree

Abstract page for arXiv paper 2603.01986: Accurate, private, secure, federated U-statistics with higher degree

arXiv - Machine Learning · 3 min ·
[2603.01971] LOCUS: A Distribution-Free Loss-Quantile Score for Risk-Aware Predictions
Machine Learning

[2603.01971] LOCUS: A Distribution-Free Loss-Quantile Score for Risk-Aware Predictions

Abstract page for arXiv paper 2603.01971: LOCUS: A Distribution-Free Loss-Quantile Score for Risk-Aware Predictions

arXiv - Machine Learning · 3 min ·
[2603.01870] Generalizing Logic-based Explanations for Machine Learning Classifiers via Optimization
Machine Learning

[2603.01870] Generalizing Logic-based Explanations for Machine Learning Classifiers via Optimization

Abstract page for arXiv paper 2603.01870: Generalizing Logic-based Explanations for Machine Learning Classifiers via Optimization

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 ·
[2603.01824] OpenAutoNLU: Open Source AutoML Library for NLU
Machine Learning

[2603.01824] OpenAutoNLU: Open Source AutoML Library for NLU

Abstract page for arXiv paper 2603.01824: OpenAutoNLU: Open Source AutoML Library for NLU

arXiv - Machine Learning · 3 min ·
[2603.01719] Co-optimization for Adaptive Conformal Prediction
Nlp

[2603.01719] Co-optimization for Adaptive Conformal Prediction

Abstract page for arXiv paper 2603.01719: Co-optimization for Adaptive Conformal Prediction

arXiv - Machine Learning · 3 min ·
[2603.01710] Legal RAG Bench: an end-to-end benchmark for legal RAG
Nlp

[2603.01710] Legal RAG Bench: an end-to-end benchmark for legal RAG

Abstract page for arXiv paper 2603.01710: Legal RAG Bench: an end-to-end benchmark for legal RAG

arXiv - Machine Learning · 4 min ·
[2601.06502] DRAGON: LLM-Driven Decomposition and Reconstruction Agents for Large-Scale Combinatorial Optimization
Llms

[2601.06502] DRAGON: LLM-Driven Decomposition and Reconstruction Agents for Large-Scale Combinatorial Optimization

Abstract page for arXiv paper 2601.06502: DRAGON: LLM-Driven Decomposition and Reconstruction Agents for Large-Scale Combinatorial Optimi...

arXiv - AI · 4 min ·
[2603.01691] Building a Strong Instruction Language Model for a Less-Resourced Language
Llms

[2603.01691] Building a Strong Instruction Language Model for a Less-Resourced Language

Abstract page for arXiv paper 2603.01691: Building a Strong Instruction Language Model for a Less-Resourced Language

arXiv - Machine Learning · 4 min ·
[2603.01590] IDProxy: Cold-Start CTR Prediction for Ads and Recommendation at Xiaohongshu with Multimodal LLMs
Llms

[2603.01590] IDProxy: Cold-Start CTR Prediction for Ads and Recommendation at Xiaohongshu with Multimodal LLMs

Abstract page for arXiv paper 2603.01590: IDProxy: Cold-Start CTR Prediction for Ads and Recommendation at Xiaohongshu with Multimodal LLMs

arXiv - Machine Learning · 3 min ·
[2512.01351] Benchmarking Overton Pluralism in LLMs
Llms

[2512.01351] Benchmarking Overton Pluralism in LLMs

Abstract page for arXiv paper 2512.01351: Benchmarking Overton Pluralism in LLMs

arXiv - AI · 3 min ·
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