Research Library
Library
Papers, patents & whitepapers, annotated
Agentic Context Management: Solving Agent Memory and Cost by Treating Them as Lifecycle and Architecture Problems
Gaurav Dadhich · arXiv · 2026
Read this before you build another retrieval layer for your agent. The quadratic cost argument alone reframes context management as an architecture decision rather than a tuning detail.
SANA-Video 2.0: Hybrid Linear Attention with Attention Residuals for Efficient Video Generation
Junsong Chen, Jincheng Yu, Yitong Li et al. · arXiv · 2026
The clearest recent evidence that linear attention works as one half of a hybrid rather than as a wholesale replacement — the same trade-off now shaping long-context language models.
K12-KGraph: A Curriculum-Aligned Knowledge Graph for Benchmarking and Training Educational LLMs
Hao Liang, Qihan Lin, Zhaoyang Han et al. · arXiv · 2026
A good demonstration that a benchmark score answers only the question the benchmark asks. Models that ace exam items still fumble the structure underneath them — a real gap for anyone building tutoring products.
Sample-Efficient Learning from Agent Experience
Chenhui Gou, Haoqin Tu, Yunhao Fang et al. · arXiv · 2026
The gap between 65 and 4 percent is the entire paper. How you train on collected experience matters far more than whether you collect it in the first place.
Molt: A Scalable PyTorch-Native Training Framework for Agentic Reinforcement Learning
Jian Hu, Huiying Li, Hao Zhang et al. · arXiv · 2026
Worth reading as an argument about research velocity rather than as a tool announcement: when every algorithm change has to thread through layers of framework glue, the framework has become the bottleneck.
Interactive Training 2: Auditable Control Plane for Live Model Training
Wentao Zhang, Xuanhe Pan, Han Zhou et al. · arXiv · 2026
The auditability is the point. Once agents can steer training runs, a written record of who changed what and what happened next stops being a nicety and becomes the only way to debug.
Multi-Turn On-Policy Distillation with Prefix Replay
Baohao Liao, Hanze Dong, Christof Monz et al. · arXiv · 2026
Pairs naturally with the relay-distillation work in this collection — both attack the same tension from opposite sides. Read them together if you are training agents on teacher supervision.
Training Compute-Optimal Large Language Models
Jordan Hoffmann, Sebastian Borgeaud, Arthur Mensch et al. · arXiv · 2022
The result that redirected the field from 'bigger' to 'better fed', and the reason the models that followed got smaller and cheaper to serve while getting better. If you read one scaling paper, read this one.
Language Models are Few-Shot Learners
Brown, Mann, Ryder et al. · arXiv · 2020
The GPT-3 paper — where "just give it a few examples in the prompt" became a real strategy. It reframed prompting as programming.
Generative Adversarial Networks
Ian J. Goodfellow, Jean Pouget-Abadie, Mehdi Mirza et al. · arXiv · 2014
The adversarial framing dominated generative modelling for most of a decade before diffusion displaced it. Worth reading for the idea that a learned critic can replace a hand-specified loss — a pattern that reappears throughout modern alignment work.
Showing 21–30 of 30 sources · newest first
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