How RecursiveMAS swaps text between AI agents for continuous vectors, making multi-agent systems differentiable end-to-end with just 0.31% trainable parameters.
WikiSkill adds a wiki layer that never gets rolled back between raw agent traces and skill files, so each skill edit builds on accumulated cross-iteration evidence.
LLM-as-a-Verifier reads the full score-token probability distribution instead of argmax, eliminating ties and beating trained reward models with zero training.
A close reading of RAGU's GraphRAG engine -- two-stage extraction, DBSCAN consolidation, Leiden clustering -- and the number in its own tables: the graph is worth 1.2 to 4.3 pp.
SAG skips the offline knowledge graph, storing events and entities in SQL, joined at query time -- beating HippoRAG 2 on multi-hop benchmarks like MuSiQue.
A walkthrough of SketchVLM: with no retraining, a coordinate grid, XML commands and Bezier smoothing let a VLM annotate the image so its answers become verifiable.
Persona-Aware D2S (EACL 2024) generates four slide-deck versions of one paper by audience and length, via an RLHF-lite pipeline we unpack and critique.