Progress-Aware Distillation for Mitigating Stagnation in Small Language Model Agents
While LLM-based agent systems have demonstrated remarkable proficiency in reasoning and solving complex real-world ta...
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While LLM-based agent systems have demonstrated remarkable proficiency in reasoning and solving complex real-world ta...
Scene-level 3D generation has long been dominated by 2D multi-view or video diffusion models. Typically, these 2D-bas...
Recent advances in self-improving LLM agents have demonstrated the potential of AI systems that drive their own intel...
Coding agents keep working on runs that will fail verification, and asking a frontier model to watch for this is expe...
Large language models (LLMs) are increasingly used in critical domains, where their susceptibility to hallucinations ...
On-policy self-distillation (OPSD) enables large language models (LLMs) to learn from privileged information (PI) wit...
People ask conversational AI models about their legal rights, obligations, procedures, and personal situations that m...
Recent advances in large language models (LLMs) have brought impressive performance across diverse tasks; however, sh...
Augmenting softmax attention with forget gates typically relies on summing decay contributions along the key--query p...
End-to-end visual generation with pixel-space loss has recently achieved competitive performance without the need for...
Estimating a humanoid robot's internal state from video has a wide range of real-world applications but remains unexp...
Harness evolution automatically optimizes the prompts, skills, tools, and orchestration code around a fixed-weight mo...