OCL is a governance layer for LLM agents that cuts unsafe executions from 88% to near-zero and raises valid success from 12% to 96% in adversarial buyer-seller negotiations across frontier LLMs.
Interactive text- to-image retrieval with large language models: A plug-and-play approach.arXiv preprint arXiv:2406.03411
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GRAPE applies GRPO to an LLM query rewriter with a corpus-relative ranking reward to improve frozen CLIP retrieval by an average 4.9% Recall@10 on shifted benchmarks without retraining or re-embedding.
ROGLE introduces automated pseudo region-sentence pairs via RSM and multi-granular learning to boost fine-grained alignment in text-based person search, plus the P-VLG benchmark with over 100k annotated regions.
citing papers explorer
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Organizational Control Layer: Governance Infrastructure at the Execution Boundary of LLM Agent Systems
OCL is a governance layer for LLM agents that cuts unsafe executions from 88% to near-zero and raises valid success from 12% to 96% in adversarial buyer-seller negotiations across frontier LLMs.
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GRAPE: Let GRPO Supervise Query Rewriting by Ranking for Retrieval
GRAPE applies GRPO to an LLM query rewriter with a corpus-relative ranking reward to improve frozen CLIP retrieval by an average 4.9% Recall@10 on shifted benchmarks without retraining or re-embedding.
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ROGLE: Robust Global-Local Alignment with Automated Region Supervision for Text-Based Person Search
ROGLE introduces automated pseudo region-sentence pairs via RSM and multi-granular learning to boost fine-grained alignment in text-based person search, plus the P-VLG benchmark with over 100k annotated regions.