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Swapping Faces, Saving Features: A Dual-Purpose Pipeline for Pedestrian Privacy in ITS
This research focuses on creating a five-stage pipeline to protect pedestrians' privacy in autonomous vehicles (AVs) by using a face-swapping method called Roop, which outperforms Ghost-v2 and strikes a balance between…
The Illusion of Equivalency: Statistical Characterization of Quantization Effects in LLMs
The authors of this paper introduce a new method to evaluate the effects of post-training quantization on large language models, as this technique is commonly used to deploy models in resource-limited settings. The…
The Illusion of Equivalency: Statistical Characterization of Quantization Effects in LLMs
The authors investigate how the quantization process used to deploy large language models in resource-limited settings can lead to unnoticed behavioral changes, even when task performance seems unaffected. They…
WebSwarm: Recursive Multi-Agent Orchestration for Deep-and-Wide Web Search
Researchers propose a new framework called WebSwarm for deep and wide web searches using large language models (LLMs). The framework aims to improve the ability of single agents to handle complexity and coverage…
Institutional Red-Teaming: Deployment Rules, Not Just Models, Causally Shape Multi-Agent AI Safety
The text introduces institutional red-teaming, a new evaluation methodology for testing the impact of deployment rules on multi-agent AI safety. The study uses IABench-CA, a consequence-allocation benchmark, to test…
RSF-GLLM: Bridging the Semantic Gap in Multi-Hop Knowledge Graph QA via Recurrent Soft-Flow and Decoupled LLM Generation
The authors propose a framework called RSF-GLLM to improve Multi-hop Question Answering over Knowledge Graphs. The framework decouples differentiable graph reasoning from answer generation, allowing the system to learn…
QFedAgent: Quantum-Enhanced Personalized Federated Learning for Multi-Agent Activity Recognition
The paper proposes QFedAgent, a hybrid quantum-classical personalized Federated Learning framework for multi-agent activity recognition. It introduces a variational quantum circuit fusion module that models…
Reasoning LLM Improves Speaker Recognition in Long-form TV Dramas
The researchers introduce a large-scale benchmark called DramaSR-532K for speaker recognition in long-form TV dramas and propose a new method, DramaSR-LRM, built on a large reasoning model (LRM). This method aggregates…
Are Performance-Optimization Benchmarks Reliably Measuring Coding Agents?
The paper evaluates three performance-optimization benchmarks (GSO, SWE-Perf, and SWE-efficiency) used to assess coding agents. The authors find that these benchmarks have issues with stability, scoring rules, and the…
AutoMem: Automated Learning of Memory as a Cognitive Skill
Researchers developed AutoMem, a framework to automate the learning of memory as a cognitive skill for large language models (LLMs). This improves the performance of LLMs significantly in long-horizon games by treating…
Self-GC: Self-Governing Context for Long-Horizon LLM Agents
A research paper titled 'Self-GC: Self-Governing Context for Long-Horizon LLM Agents' presents a system called Self-GC that aims to manage the lifecycle of context objects for long-horizon language models (LLMs). The…
Field Order Should Not Matter: Permutation-Invariant Embedding Model Fine-Tuning for Structured Metadata Retrieval
Researchers propose a method called permutation-invariant fine-tuning (PI-FT) to improve structured metadata retrieval. They show that the choice of field order in a record can significantly impact retrieval quality…
MESA: Prioritizing Vulnerable Communication Channels for Securing Multi-Agent Systems
In this research paper titled 'MESA: Prioritizing Vulnerable Communication Channels for Securing Multi-Agent Systems', the authors propose a framework called Mesa to prioritize and secure communication channels in…
AU-Harness: An Open-Source Toolkit for Holistic Evaluation of AudioLLMs
The authors introduce AU-Harness, an efficient and comprehensive evaluation framework for Large Audio Language Models (LALMs). The system addresses limitations in existing toolkits by improving speed, providing…
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A Process Harness for Uplifting Legacy Workflows to Agentic BPM: Design and Realization in CUGA FLO
The authors introduce a new mechanism called 'process harness' for upgrading legacy workflows to an Agentic Business Process Management (Agentic BPM) without replacing the existing engine. The process harness involves…
Bridging Talk and Thought: Understanding Dialogue Dynamics Across Collaborative Problem-Solving Contexts
The authors present a framework for analyzing dialogue in collaborative problem-solving contexts, especially in human-AI and multi-agent collaboration. The framework aims to understand the emerging dynamics of these…
Chai: Agentic Discovery of Cryptographic Misuse Vulnerabilities
Researchers have developed Chai, an AI-based system that discovers and validates cryptographic misuse vulnerabilities through naturally occurring signals. Instead of auditing one codebase for many flaws, Chai catalogs…
State Representation Matters in Deep Reinforcement Learning: Application to Energy Trading
Researchers studied the impact of state representation in deep reinforcement learning (DRL) for energy trading decisions, using a fixed Double DQN agent in the HydroDam environment. They found that combining absolute…
Model Forensics: Investigating Whether Concerning Behavior Reflects Misalignment
The paper proposes a basic protocol for investigating if AI models exhibit concerning behavior due to malicious intent or benign causes like confusion. The protocol involves analyzing the 'chain of thought' (CoT) to…
Accuracy and Satisfaction in Multi-Turn LLM Dialogues for NFR Assessment
Researchers examined the accuracy of Large Language Model (LLM)-based dialogue assistants in handling Non-Functional Requirements (NFRs) related to Health Insurance Portability and Accountability Act (HIPAA) regulatory…
Measuring & Mitigating Over-Alignment for LLMs in Multilingual Criminal Law Courts
The authors present TF-RefusalBench, a multilingual benchmark for assessing over-alignment in legal language models used by the Swiss Federal Supreme Court. They find that over-alignment is complex and influenced by…
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