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Deployed LLM agents increasingly keep their long-term memory as a filesystem: a directory tree of markdown files that...
Multimodal large language models increasingly use sketches, annotations, tools, and intermediate images during reason...
Memory is central to long-horizon LLM agents, yet existing memory systems primarily preserve interaction content rath...
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...