arXiv
RetroThinker: Enabling Retrospective Thinking in Speech LLMs
Speech large language models (SpeechLLMs) offer reduced latency and retain paralinguistic nuances that are typically ...
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arXiv
The Last AI Built by Humans: Toward Genuine Recursive Self-Improvement
Recursive self-improvement (RSI) enables AI systems to turn experience and feedback into persistent changes that impr...
arXiv
On the Regularization Landscape for the Linear Recommendation Models
Recently, a wide range of recommendation algorithms inspired by deep learning techniques have emerged as the performa...
arXiv
Biology-in-the-loop: Amortized Adaptive Hit Discovery in CRISPR Screens
Many biological discovery problems require experiments to be selected sequentially under constrained budgets. CRISPR ...
arXiv
Domain-Specific Hallucination Detection in Large Language Models
Large language models generate fluent text that can contain unfaithful claims -- a phenomenon known as hallucination....
arXiv
MindTopo: Can Foundation Models Reason in Topological Space?
Spatial reasoning depends not only on metric properties such as distance, angle, and shape, but also on topological r...
arXiv
Artificial Id: Drive and Persistent Alignment in Agentic AI
Agentic AI is moving from bounded task execution toward systems that retain consequential state, continue operating a...
arXiv
Generative Marketing Mix Modeling: A Causal Inference Framework Linking GEO and GEM to Business Impact
Generative artificial intelligence changes how firms reach customers, but standard marketing data do not record how o...
arXiv
Can Edge-Deployable Vision-Language Models Identify Species?
Camera traps often run in the field on edge hardware with limited or no connectivity, making small, locally-deployabl...
arXiv
General Quantification of Covariate and Concept Shifts
Generalization under distribution shift remains a core challenge in modern machine learning, yet existing learning bo...
arXiv
GPU-CFR: 80x Faster Counterfactual Regret Minimization by Compiling the Game to Static Dataflow and CUDA Graph Replay
Counterfactual regret minimization (CFR) is one of the few large numerical workloads that still runs faster on CPUs t...
HuggingFace
Scaling Automatic Research Agents via World Models
Automating empirical research is a long-standing direction of AI. Recent automatic research (AutoResearch) agents bri...