· ai
[Paper] Counterfactual Fairness with Graph Uncertainty
Evaluating machine learning (ML) model bias is key to building trustworthy and robust ML systems. Counterfactual Fairness (CF) audits allow the measurement of b...
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[Paper] Recursive querying of neural networks via weighted structures
Expressive querying of machine learning models - viewed as a form of intentional data - enables their verification and interpretation using declarative language...
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[Paper] DIP: Dynamic In-Context Planner For Diffusion Language Models
Diffusion language models (DLMs) have shown strong potential for general natural language tasks with in-context examples. However, due to the bidirectional atte...
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[Paper] Empowering Reliable Visual-Centric Instruction Following in MLLMs
Evaluating the instruction-following (IF) capabilities of Multimodal Large Language Models (MLLMs) is essential for rigorously assessing how faithfully model ou...
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[Paper] Sparse Knowledge Distillation: A Mathematical Framework for Probability-Domain Temperature Scaling and Multi-Stage Compression
We develop a unified theoretical framework for sparse knowledge distillation based on probability-domain softening operators. While the equivalence p^{1/T} prop...
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[Paper] UniCorn: Towards Self-Improving Unified Multimodal Models through Self-Generated Supervision
While Unified Multimodal Models (UMMs) have achieved remarkable success in cross-modal comprehension, a significant gap persists in their ability to leverage su...
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[Paper] AnatomiX, an Anatomy-Aware Grounded Multimodal Large Language Model for Chest X-Ray Interpretation
Multimodal medical large language models have shown impressive progress in chest X-ray interpretation but continue to face challenges in spatial reasoning and a...
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[Paper] Decentralized Autoregressive Generation
We present a theoretical analysis of decentralization of autoregressive generation. We define the Decentralized Discrete Flow Matching objective, by expressing ...
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[Paper] Multi-Modal Data-Enhanced Foundation Models for Prediction and Control in Wireless Networks: A Survey
Foundation models (FMs) are recognized as a transformative breakthrough that has started to reshape the future of artificial intelligence (AI) across both acade...
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[Paper] Unified Thinker: A General Reasoning Modular Core for Image Generation
Despite impressive progress in high-fidelity image synthesis, generative models still struggle with logic-intensive instruction following, exposing a persistent...
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[Paper] From Muscle to Text with MyoText: sEMG to Text via Finger Classification and Transformer-Based Decoding
Surface electromyography (sEMG) provides a direct neural interface for decoding muscle activity and offers a promising foundation for keyboard-free text input i...
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The Best Data Scientists Are Always Learning
Part 2: Avoiding burnout, learning strategies and the superpower of solitude The post The Best Data Scientists Are Always Learning appeared first on Towards Dat...