CADENCE: Closing the Reasoning Gap via Coverage-Adaptive On-Policy Distillation
On-policy knowledge distillation transfers reasoning from large teachers to compact students, but existing approaches...
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On-policy knowledge distillation transfers reasoning from large teachers to compact students, but existing approaches...
Memory has evolved into a foundational architectural dimension in large language models (LLMs), shifting from an impl...
Generalist manipulation policies increasingly take the form of action-chunking flow policies built on large pretraine...
We present Voice Memory, a inference-only scheme for agentic speech recognition: at stream time, a frozen corrector r...
Existing autoregressive video distillation methods commonly adopt a Distribution Matching Distillation (DMD)-based mu...
Coding agents have made substantial progress on software engineering tasks that modify existing codebases, including ...
LLM-based agents excel at software engineering tasks where an existing codebase provides context, but constructing a ...
Fine-tuning is the dominant paradigm for specializing large language models (LLMs), yet it exposes a critical vulnera...
As LLM agents increasingly depend on diverse external services such as search engines, databases, and connectors, age...
Scientific images are the core elements of presenting experimental conclusions, elaborating system architecture, and ...
With the development of audio large language models (AudioLLMs), audio captioning needs to move from brief descriptio...
Ontology matching (OM) has traditionally been formulated as either equivalence discovery or subsumption matching. The...