Stanford University

Entry-level doors closing, showing up as reduced hiring rather than layoffs. The authors state that these are descriptive indicators, not causal ones

AI for science became a subject of measurement in its own right

A counterexample from the attack side to optimism about CoT monitoring

Argues that prompt evolution can compete with RL on sample efficiency

A technique for controlling reasoning length itself at the prompt and decoding level

The theoretical basis of DSPy's optimizers

Lowered the barrier to entry for academia and small and medium-sized companies

Extended the automatic-differentiation metaphor to text systems in general

The multi-hop retrieval branch of the GraphRAG lineage

Proposed a hierarchical summary index as an alternative to chunk-level retrieval

A framework that shifted from writing prompts to compiling programs

A branch that gets the few-shot effect without labeling examples

The first large-scale counterevidence to the assumption that you can simply put in a long context

Optimizes directly on preference pairs without a reward model or PPO, popularizing open-source alignment

A rebuttal arguing that emergence is an artifact of discontinuous metrics; with continuous metrics the curves are smooth

Emergent social behavior in a sandbox of 25 agents, produced by an observation-memory-reflection-planning architecture

Demonstrated that instruction-following can be replicated for a small sum

The work that made comparability between models possible in the first place

Effectively opened up the road to long context

The starting point of the diffusion language model lineage

The follow-up that brought late interaction down to practically sized indexes

The starting point of the late interaction lineage, distinct from single-vector retrieval

An early case of applying GPUs to deep learning training in earnest. The starting point of the premise that compute is a resource