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Cursor makes its biggest India push yet ahead of SpaceX acquisition with localized pricing4h◆Reverso: Efficient Time Series Foundation Models for Zero-shot Forecasting5h◆Multinex: Lightweight Low-light Image Enhancement via Multi-prior Retinex5h◆Market Design for AI: Beyond the Copyright Binary5h◆Who Pays the Price? Stakeholder-Centric Prompt Injection Benchmarking for Real-world Web Agents5h◆TextRich: A Multi-Domain Benchmark for Detecting AI-Generated Text-Rich Images from GPT-Image-25h◆DiscoLoop: Looping Discrete Embeddings and Continuous Hidden States for Multi-hop Reasoning5h◆From World Models to World Action Models: A Concise Tutorial for Robotics5h◆QuantFlow: A Federated Mamba-Based Post-Transformer Foundation Model for Time-Series Forecasting5h◆Multi-Turn On-Policy Distillation with Prefix Replay5h◆Operational Proto-Introspection in Looped Language Models: Process-Quality Taps, Executable Branching, and the Readout-Control Boundary5h◆Skillware: A Software Ontology and Engineering Lifecycle for Persistent Behavioral Artifacts5h◆MedDDC-Eval: Diagnosis-Decoupled Evaluation of Multi-Turn Medical Consultation Agents5h◆PhantomFill: When the Form Demands an Answer, Language Models Invent One5h◆Error Certificates for KV-Cache Eviction via Randomized Design5h◆Explaining GAND: A Resource on Gender-Ambiguous Natural Data & Contrastive Attribution5h◆MioFFAn: an Annotation Software for Formula Formalization with LLM Automation Capabilities5h◆LA-RL: Label-Aware Self-Reflection for Reinforcement Learning in Information Extraction5h◆Mwando: Leveraging AI to Preserve and Teach shiKomori5h◆The JEPA Paradox in Language: The Geometry of Linguistic Alternatives5h◆Cursor makes its biggest India push yet ahead of SpaceX acquisition with localized pricing4h◆Reverso: Efficient Time Series Foundation Models for Zero-shot Forecasting5h◆Multinex: Lightweight Low-light Image Enhancement via Multi-prior Retinex5h◆Market Design for AI: Beyond the Copyright Binary5h◆Who Pays the Price? Stakeholder-Centric Prompt Injection Benchmarking for Real-world Web Agents5h◆TextRich: A Multi-Domain Benchmark for Detecting AI-Generated Text-Rich Images from GPT-Image-25h◆DiscoLoop: Looping Discrete Embeddings and Continuous Hidden States for Multi-hop Reasoning5h◆From World Models to World Action Models: A Concise Tutorial for Robotics5h◆QuantFlow: A Federated Mamba-Based Post-Transformer Foundation Model for Time-Series Forecasting5h◆Multi-Turn On-Policy Distillation with Prefix Replay5h◆Operational Proto-Introspection in Looped Language Models: Process-Quality Taps, Executable Branching, and the Readout-Control Boundary5h◆Skillware: A Software Ontology and Engineering Lifecycle for Persistent Behavioral Artifacts5h◆MedDDC-Eval: Diagnosis-Decoupled Evaluation of Multi-Turn Medical Consultation Agents5h◆PhantomFill: When the Form Demands an Answer, Language Models Invent One5h◆Error Certificates for KV-Cache Eviction via Randomized Design5h◆Explaining GAND: A Resource on Gender-Ambiguous Natural Data & Contrastive Attribution5h◆MioFFAn: an Annotation Software for Formula Formalization with LLM Automation Capabilities5h◆LA-RL: Label-Aware Self-Reflection for Reinforcement Learning in Information Extraction5h◆Mwando: Leveraging AI to Preserve and Teach shiKomori5h◆The JEPA Paradox in Language: The Geometry of Linguistic Alternatives5h◆
Tag

#interpretable-ai

3 articles tagged #interpretable-ai

arxivJun 18bullish

Explaining Attention with Program Synthesis

arXiv:2606.19317v1 Announce Type: cross Abstract: A longstanding goal of research on interpretable deep learning is to replace opaque neural computations with human-meaningful symbolic descriptions. In this paper, we propose an approach for approximating the behavior of components of deep networks w

GPTIME3 models#interpretable-ai#transformer-models#reverse-engineeringRead on arxiv →
arxivJun 11bullish

MARIC: Multi-Agent Reasoning for Image Classification

arXiv:2509.14860v2 Announce Type: replace-cross Abstract: Image classification has traditionally relied on parameter-intensive model training, requiring large-scale annotated datasets and extensive fine tuning to achieve competitive performance. While recent vision language models (VLMs) alleviate s

MAVL2 models#computer-vision#multiagent-systems#image-classificationRead on arxiv →
arxivMay 8

A renormalization-group inspired lattice-based framework for piecewise generalized linear models

arXiv:2605.05493v1 Announce Type: cross Abstract: We formally introduce a class of models inspired by renormalization group (RG) theory, built on additive hierarchical expansions analogous to those appearing in functional ANOVA and mixed-effects models. Like ReLU convolutional neural networks, they

REPIHI4 models · +1#interpretable-ai#statistical-physics#machine-learningRead on arxiv →
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