· ai
[Paper] Unified Primitive Proxies for Structured Shape Completion
Structured shape completion recovers missing geometry as primitives rather than as unstructured points, which enables primitive-based surface reconstruction. In...
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- · ai
[Paper] Memory Bank Compression for Continual Adaptation of Large Language Models
Large Language Models (LLMs) have become a mainstay for many everyday applications. However, as data evolve their knowledge quickly becomes outdated. Continual ...
- · ai
[Paper] A Machine Learning Framework for Off Ball Defensive Role and Performance Evaluation in Football
Evaluating off-ball defensive performance in football is challenging, as traditional metrics do not capture the nuanced coordinated movements that limit opponen...
- · ai
[Paper] The Reasoning-Creativity Trade-off: Toward Creativity-Driven Problem Solving
State-of-the-art large language model (LLM) pipelines rely on bootstrapped reasoning loops: sampling diverse chains of thought and reinforcing the highest-scori...
- · ai
[Paper] An Agentic Framework for Neuro-Symbolic Programming
Integrating symbolic constraints into deep learning models could make them more robust, interpretable, and data-efficient. Still, it remains a time-consuming an...
- · ai
[Paper] Stochastic Actor-Critic: Mitigating Overestimation via Temporal Aleatoric Uncertainty
Off-policy actor-critic methods in reinforcement learning train a critic with temporal-difference updates and use it as a learning signal for the policy (actor)...
- · ai
[Paper] Exploring the Performance of Large Language Models on Subjective Span Identification Tasks
Identifying relevant text spans is important for several downstream tasks in NLP, as it contributes to model explainability. While most span identification appr...
- · ai
[Paper] Grading Handwritten Engineering Exams with Multimodal Large Language Models
Handwritten STEM exams capture open-ended reasoning and diagrams, but manual grading is slow and difficult to scale. We present an end-to-end workflow for gradi...
- · ai
[Paper] Precision Autotuning for Linear Solvers via Contextual Bandit-Based RL
We propose a reinforcement learning (RL) framework for adaptive precision tuning of linear solvers, and can be extended to general algorithms. The framework is ...
- · ai
[Paper] Multi-Level Feature Fusion for Continual Learning in Visual Quality Inspection
Deep neural networks show great potential for automating various visual quality inspection tasks in manufacturing. However, their applicability is limited in mo...
- · it
Microsoft CEO Satya Nadella is now blogging about AI slop
Now that Microsoft CEO Satya Nadella has appointed a new CEO to run Microsoft's biggest businesses, he has a little more time on his hands for other adventures....
- · ai
[Paper] Detecting Performance Degradation under Data Shift in Pathology Vision-Language Model
Vision-Language Models have demonstrated strong potential in medical image analysis and disease diagnosis. However, after deployment, their performance may dete...