Multi-LLM
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Related Articles from SNS
Ontology-constrained multi-LLM scoring of hypothesis support in the predictive processing literature
arXiv:2606.05206v1 Announce Type: cross Abstract: Fragmentation is common in interdisciplinary fields with diverse methods and theoretical commitments. Predictive coding neuroscience is a clear example: its literature spans computational theory, electrophysiology, imaging, behavior, and modeling, creating a synthesis problem that conventional meta-analysis cannot easily resolve. Here, we describe a local multi-LLM pipeline for ontology-constrained literature synthesis.
LRAgent: Efficient KV Cache Sharing for Multi-LoRA LLM Agents
Announce Type: replace Abstract: Role specialization in multi-LLM agent systems is often realized via multi-LoRA, where agents share a pretrained backbone and differ only by lightweight adapters. Despite sharing base model weights, each agent independently builds and stores its own KV cache for the same long, tool-augmented trajectories, incurring substantial memory and compute overhead. Existing KV cache sharing methods largely overlook this multi-LoRA setting.
Beyond Agreement: Scoring Panel-Surfaced Biomedical Entity Candidates for Curator Triage
arXiv:2605.30826v1 Announce Type: new Abstract: Biomedical NER is deceptively simple for modern LLMs: plausible biomedical mentions are easy to surface, but corpus-convention correctness depends on annotation conventions, span boundaries, entity granularity, and type schemas. Multi-LLM agreement is a salience signal, not corpus-convention correctness. We introduce a candidate-level panel-output benchmark for panel-surfaced candidate verification, where the unit is an aligned candidate...
Privacy Policy Enforcement Guardrails for Data-Sensitive Retrieval-Augmented Generation
arXiv:2605.17034v2 Announce Type: replace Abstract: Standard PII filters often miss contextual data leakage in RAG systems, such as non-regulated attribute clusters that collectively identify individuals. We introduce a Privacy Policy Enforcement (PPE) framework using dual one-class density estimators with fused text embeddings and a calibrated abstain region for out-of-distribution inputs. Using an axis-stratified, multi-LLM synthetic data pipeline across medicine, finance, and law, we...
Natural Language Access Control (NLAC): From Help Desk Requests to Structured Policies
arXiv:2606.06726v1 Announce Type: new Abstract: Configuring network access control policies in large, complex networks is error-prone and requires significant expert effort. LLMs offer a promising interface for expressing such policies in natural language, but their capability for translating user requests into access policies, and the system architectures best suited to leverage LLMs, remain underexplored. We present an architecture for natural-language access control (NLAC) that uses LLMs...
LLM Self-Recognition: Steering and Retrieving Activation Signatures
Announce Type: new Abstract: Recent advances in interpretability suggest that large language models (LLMs) implicitly encode signals in their generated text that enable self-recognition of their outputs. We demonstrate that this capability is reliable, even in low-entropy scenarios, and that it can be amplified through targeted intervention. By steering the internal residual stream during generation with a random sparse vector, we create a detectable fingerprint that enables attribution of a...
Personality Anchoring for Social Simulation: Linking Personality, Social Behavior, and Interaction Success with LLM Agents
arXiv:2606.06936v1 Announce Type: new Abstract: Social interactions are shaped by the interplay of dispositional traits and situational context, yet systematically investigating how personality configurations between individuals jointly influence social behavior across diverse social contexts remains methodologically challenging. We address this gap by introducing a simulation pipeline adapted from the CHARISMA framework, which employs well-known movie characters and public figures as...