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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 ·
Yupp shuts down after raising $33M from a16z crypto's Chris Dixon | TechCrunch
Machine Learning

Yupp shuts down after raising $33M from a16z crypto's Chris Dixon | TechCrunch

Less than a year after launching, with checks from some of the biggest names in Silicon Valley, crowdsourced AI model feedback startup Yu...

TechCrunch - AI · 4 min ·
Machine Learning

[R] Fine-tuning services report

If you have some data and want to train or run a small custom model but don't have powerful enough hardware for training, fine-tuning ser...

Reddit - Machine Learning · 1 min ·

All Content

[2603.08561] RetroAgent: From Solving to Evolving via Retrospective Dual Intrinsic Feedback
Llms

[2603.08561] RetroAgent: From Solving to Evolving via Retrospective Dual Intrinsic Feedback

Abstract page for arXiv paper 2603.08561: RetroAgent: From Solving to Evolving via Retrospective Dual Intrinsic Feedback

arXiv - AI · 4 min ·
[2601.18420] Gradient Regularized Natural Gradients
Machine Learning

[2601.18420] Gradient Regularized Natural Gradients

Abstract page for arXiv paper 2601.18420: Gradient Regularized Natural Gradients

arXiv - AI · 4 min ·
[2511.07436] Analysing Environmental Efficiency in AI for X-Ray Diagnosis
Llms

[2511.07436] Analysing Environmental Efficiency in AI for X-Ray Diagnosis

Abstract page for arXiv paper 2511.07436: Analysing Environmental Efficiency in AI for X-Ray Diagnosis

arXiv - AI · 4 min ·
[2601.02856] Electricity Price Forecasting: Bridging Linear Models, Neural Networks and Online Learning
Machine Learning

[2601.02856] Electricity Price Forecasting: Bridging Linear Models, Neural Networks and Online Learning

Abstract page for arXiv paper 2601.02856: Electricity Price Forecasting: Bridging Linear Models, Neural Networks and Online Learning

arXiv - Machine Learning · 4 min ·
[2601.00428] Interpretable ML Under the Microscope: Performance, Meta-Features, and the Regression-Classification Predictability Gap
Machine Learning

[2601.00428] Interpretable ML Under the Microscope: Performance, Meta-Features, and the Regression-Classification Predictability Gap

Abstract page for arXiv paper 2601.00428: Interpretable ML Under the Microscope: Performance, Meta-Features, and the Regression-Classific...

arXiv - Machine Learning · 4 min ·
[2510.18087] Planned Diffusion
Llms

[2510.18087] Planned Diffusion

Abstract page for arXiv paper 2510.18087: Planned Diffusion

arXiv - AI · 4 min ·
[2509.23768] From What to Why: A Multi-Agent System for Evidence-based Chemical Reaction Condition Reasoning
Llms

[2509.23768] From What to Why: A Multi-Agent System for Evidence-based Chemical Reaction Condition Reasoning

Abstract page for arXiv paper 2509.23768: From What to Why: A Multi-Agent System for Evidence-based Chemical Reaction Condition Reasoning

arXiv - AI · 3 min ·
[2512.18951] Benchmarking Attribute Discrimination in Infant-Scale Vision-Language Models
Llms

[2512.18951] Benchmarking Attribute Discrimination in Infant-Scale Vision-Language Models

Abstract page for arXiv paper 2512.18951: Benchmarking Attribute Discrimination in Infant-Scale Vision-Language Models

arXiv - Machine Learning · 3 min ·
[2509.03345] Do Language Models Follow Occam's Razor? An Evaluation of Parsimony in Inductive and Abductive Reasoning
Llms

[2509.03345] Do Language Models Follow Occam's Razor? An Evaluation of Parsimony in Inductive and Abductive Reasoning

Abstract page for arXiv paper 2509.03345: Do Language Models Follow Occam's Razor? An Evaluation of Parsimony in Inductive and Abductive ...

arXiv - AI · 4 min ·
[2512.10152] Rethinking Bivariate Causal Discovery Through the Lens of Exchangeability
Machine Learning

[2512.10152] Rethinking Bivariate Causal Discovery Through the Lens of Exchangeability

Abstract page for arXiv paper 2512.10152: Rethinking Bivariate Causal Discovery Through the Lens of Exchangeability

arXiv - Machine Learning · 4 min ·
[2512.01906] Delays in Spiking Neural Networks: A State Space Model Approach
Machine Learning

[2512.01906] Delays in Spiking Neural Networks: A State Space Model Approach

Abstract page for arXiv paper 2512.01906: Delays in Spiking Neural Networks: A State Space Model Approach

arXiv - Machine Learning · 4 min ·
[2504.15780] TrustGeoGen: Formal-Verified Data Engine for Trustworthy Multi-modal Geometric Problem Solving
Llms

[2504.15780] TrustGeoGen: Formal-Verified Data Engine for Trustworthy Multi-modal Geometric Problem Solving

Abstract page for arXiv paper 2504.15780: TrustGeoGen: Formal-Verified Data Engine for Trustworthy Multi-modal Geometric Problem Solving

arXiv - AI · 4 min ·
[2503.03361] Concepts Learned Visually by Infants Can Contribute to Visual Learning and Understanding in AI Models
Machine Learning

[2503.03361] Concepts Learned Visually by Infants Can Contribute to Visual Learning and Understanding in AI Models

Abstract page for arXiv paper 2503.03361: Concepts Learned Visually by Infants Can Contribute to Visual Learning and Understanding in AI ...

arXiv - AI · 4 min ·
[2512.01678] Morphling: Fast, Fused, and Flexible GNN Training at Scale
Machine Learning

[2512.01678] Morphling: Fast, Fused, and Flexible GNN Training at Scale

Abstract page for arXiv paper 2512.01678: Morphling: Fast, Fused, and Flexible GNN Training at Scale

arXiv - Machine Learning · 4 min ·
[2511.22344] Cleaning the Pool: Progressive Filtering of Unlabeled Pools in Deep Active Learning
Machine Learning

[2511.22344] Cleaning the Pool: Progressive Filtering of Unlabeled Pools in Deep Active Learning

Abstract page for arXiv paper 2511.22344: Cleaning the Pool: Progressive Filtering of Unlabeled Pools in Deep Active Learning

arXiv - Machine Learning · 4 min ·
[2410.20894] Working Paper: Active Causal Structure Learning with Latent Variables: Towards Learning to Detour in Autonomous Robots
Machine Learning

[2410.20894] Working Paper: Active Causal Structure Learning with Latent Variables: Towards Learning to Detour in Autonomous Robots

Abstract page for arXiv paper 2410.20894: Working Paper: Active Causal Structure Learning with Latent Variables: Towards Learning to Deto...

arXiv - Machine Learning · 4 min ·
[2511.16992] FIRM: Federated In-client Regularized Multi-objective Alignment for Large Language Models
Llms

[2511.16992] FIRM: Federated In-client Regularized Multi-objective Alignment for Large Language Models

Abstract page for arXiv paper 2511.16992: FIRM: Federated In-client Regularized Multi-objective Alignment for Large Language Models

arXiv - Machine Learning · 4 min ·
[2511.14961] Graph Memory: A Structured and Interpretable Framework for Modality-Agnostic Embedding-Based Inference
Machine Learning

[2511.14961] Graph Memory: A Structured and Interpretable Framework for Modality-Agnostic Embedding-Based Inference

Abstract page for arXiv paper 2511.14961: Graph Memory: A Structured and Interpretable Framework for Modality-Agnostic Embedding-Based In...

arXiv - Machine Learning · 4 min ·
[2603.25741] Vega: Learning to Drive with Natural Language Instructions
Machine Learning

[2603.25741] Vega: Learning to Drive with Natural Language Instructions

Abstract page for arXiv paper 2603.25741: Vega: Learning to Drive with Natural Language Instructions

arXiv - AI · 3 min ·
[2510.13772] Tensor Gaussian Processes: Efficient Solvers for Nonlinear PDEs
Machine Learning

[2510.13772] Tensor Gaussian Processes: Efficient Solvers for Nonlinear PDEs

Abstract page for arXiv paper 2510.13772: Tensor Gaussian Processes: Efficient Solvers for Nonlinear PDEs

arXiv - Machine Learning · 4 min ·
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