Papers

Filtered to deep learning models · clear filter

Browse by term

continual learning 86reinforcement learning 48benchmarking 13large language models 12benchmarks 11vision-language models 10language models 9robotics 7world models 7natural language processing 6recursive self-improvement 6generative models 5on-policy distillation 5video generation 5attention mechanisms 4coding agents 4LLMs 4multi-agent systems 4multimodal learning 4multimodal models 4self-distillation 4self-supervised learning 4transformers 4vision-language-action models 4world modeling 4agent-based systems 3agentic models 3agentic search 3agents 3autonomous systems 3

Matching papers

BDH-CQ: In-Context Learning with Recurrent Latent Reasoning

548 upvotes · 10 AUG 2026 · Björn Engdahl, Adrian Kosowski, Jan Chorowski et al.

This paper introduces a new AI model called BDH-CQ that can learn from context and reason iteratively without verbalizing its steps. Practitioners might care because this model achieves a high level of performance while being very efficient, which could be useful for applications where resources are limited.

in-context learningrecurrent latent reasoningdeep learning modelsbenchmarkingartificial general intelligence

AuK Technical Report: An Open-Source Foundational Model for Speech Generation and Editing

156 upvotes · 8 SEP 2026 · Ziyang Ma, Zhikang Niu, Wenming Tu et al.

This paper introduces AuK, an open-source model for speech generation and editing, which can perform a range of tasks with a single interface and achieves state-of-the-art performance on several tasks. Practitioners may care about this model for its potential to improve speech synthesis and editing capabilities in applications such as voice assistants and audio editing software.

speech generationspeech editingnatural language processingdeep learning modelsaudio processing