#neural-architectures News & Analysis

3 articles tagged with #neural-architectures. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

3 articles

AIBullisharXiv – CS AI · Jun 27/10

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PolarMem: A Training-Free Polarized Latent Graph Memory for Verifiable Vision-Language Models

Researchers introduce PolarMem, a training-free memory framework that enhances vision-language models by explicitly tracking what has been verified as absent or excluded, not just what is similar. The system uses a polarized graph structure with positive and negative memory relations to reduce logical contradictions and improve reasoning reliability across multiple multimodal benchmarks.

AINeutralarXiv – CS AI · Jun 26/10

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Learning to Remember, Learn, and Forget in Attention-Based Models

Researchers propose Palimpsa, a self-attention model that frames in-context learning as a continual learning problem using Bayesian metaplasticity to overcome memory interference in long sequences. The framework unifies existing gated linear attention models as special cases and demonstrates improved performance on associative recall and reasoning tasks, offering a theoretical foundation for enhancing memory capacity in transformer-based architectures.

AINeutralarXiv – CS AI · May 296/10

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Survey of End-to-End Multi-Speaker Automatic Speech Recognition for Monaural Audio

This survey comprehensively reviews end-to-end neural architectures for multi-speaker automatic speech recognition on monaural audio, analyzing SIMO vs. SISO paradigms, recent algorithmic improvements, and extensions to long-form speech. The work addresses a critical gap in literature by systematizing recent advances in a field transitioning from cascade to unified E2E systems that better handle overlapping speech and speaker attribution.