ACL2025 Wu: RankCoT refining knowledge for retrieval augmented generation through ranking CoT Key insight: generally a bunch of chain of thoughts, including on irrelevant documents, re-rank using self reflection, and then DPO ACL2025 Trienes: behavioral analysis of information salience Key insight: you can ask models for summaries at shorter lengths, which distill what the models think is salient information ACL2025 Abbes: small encoders can rival large encoders in detecting groundedness Key insight: apparently groundedness classification doesn’t require that many parameters ACL2025 Luo: rethinking diverse human preference learning Key insight: learn a Bradley terry reward model, PCA it’s embeddings, turns out those are interpretable and matches human reward differences ACL2025 Chouayfati: GenDLN Key insight: Used genetic algos for Prompt mixtures to iteratively improve prompt quality ACL2025 (SRW): Sakunkoo Key insight: data for defective verbs and trained tagger ACL2025 Long: reinforcing compositional retrieval Key insight: auto progressive embedding retriever to be able to get sequential decision tasks for RAG ACL2025 Shelton: PQB-EQA Key insight: benchmark for vision grounding context attribution using Minecraft ACL2025 Green: BabelEdits Key insight: a cross linguistic model editing benchmark ACL2025 Ichihara: theoretical guarantees for minimum Bayes risk Key insight: easy Monte Carlo minimum Bayes risk decoding we can achieve closer to theoretical optimality for LM decoding