Jean-Philippe Vasseur

MAKING NETWORK TROUBLESHOOTING AGENTS TRAINED USING REINFORCEMENT LEARNING ROBUST TO ADVERSARIAL ATTACKS

DYNAMIC ACTIVATION OF NETWORK TROUBLESHOOTING AGENT HOSTING

USER ROLE-AWARE INTERACTIONS BY NETWORK TROUBLESHOOTING LLM AGENTS

ISSUE DETECTION AND SENTIMENT ASSESSMENT IN A NETWORK TROUBLESHOOTING SYSTEM WITH AN LLM-BASED AGENT

MULTIMODAL FOUNDATION MODEL FOR NETWORKING

AI AGENT AS A SAFEGUARD AND NETWORK CHANGE REVIEWER

DYNAMIC INPUT GRANULARITY ESTIMATION FOR NETWORK PATH FORECASTING USING TIMESERIES FEATURES

HIGHLY INTERACTIVE, LANGUAGE MODEL-BASED NETWORK TROUBLESHOOTING AGENTS

GENERATING NEW USER FEEDBACK IN COGNITIVE NETWORKS

SAFETY NET ENGINE FOR MACHINE LEARNING-BASED NETWORK AUTOMATION

OPPORTUNISTIC RELAY AMONG MOBILE COMMUNICATION DEVICES

AUTONOMOUS SYSTEM BOTTLENECK DETECTION

DYNAMIC QoS ACTIVATION OF CRITICAL FLOWS UNDER DOWNSCALED TOPOLOGIES IN A GREEN ELASTIC NETWORK

ESTIMATING ENERGY CONSUMPTION IN GREEN ELASTIC NETWORKS

SAFETY NET MECHANISM FOR DETECTING CRITICAL SCALE UP IN A GREEN ELASTIC NETWORK

AUDITING AND RECOMMENDING SYSTEM FOR A GREEN ELASTIC NETWORK

DISCOVERY OF POWER DEGRADED MODES IN A GREEN ELASTIC NETWORK

OBTAINING GROUND TRUTH LABELS FROM NETWORK CHANGES TO TRAIN A LANGUAGE MODEL-BASED NETWORK TROUBLESHOOTING AGENT

PROVIDING TRANSPARENCY IN LANGUAGE MODEL-BASED NETWORK TROUBLESHOOTING SYSTEMS

MAKING A WHAT-IF SCENARIO EVALUATION IN A GREEN ELASTIC NETWORK WITH PARTIAL TRAFFIC AND TOPOLOGY INFORMATION

POLICY MANAGEMENT AND ENFORCEMENT IN A GREEN ELASTIC NETWORK

SOFT SLEEP ACTIVATION OF NETWORK RESOURCES IN A GREEN ELASTIC NETWORK

MARKET-BASED APPROACH TO ALLOCATE ENERGY-AWARE RIGHTS-TO-OPERATE IN A GREEN ELASTIC NETWORK

VALIDATING REUSABLE CODE FOR A LANGUAGE MODEL-BASED NETWORK AGENT

AI-DRIVEN ELASTIC NETWORK TO REDUCE ENERGY CONSUMPTION

QUALITY OF EXPERIENCE POLICY ENGINE FOR CUSTOM APPLICATIONS BASED ON FEEDBACK

SOFTWARE DEVELOPMENT KIT FOR INTEGRATING APPLICATIONS AND COGNITIVE NETWORKS

ENSEMBLE-BASED DETECTION OF ANOMALOUS FEEDBACK IN MACHINE LEARNING MODELING

MULTI-AGENT COORDINATION FOR NETWORK ANOMALY DETECTION, TROUBLESHOOTING, AND REMEDIATION USING LANGUAGE MODELS

GRAPH-BASED RETRIEVAL AUGMENTED GENERATION OF SDK SCHEMAS FOR A LANGUAGE MODEL-BASED NETWORK TROUBLESHOOTING AGENT

MODEL-BASED ASSESSMENT OF QUALITY OF EXPERIENCE

USING NEGATIVE FEEDBACK LEARNING ON A LANGUAGE MODEL-BASED NETWORK TROUBLESHOOTING AGENT

Multi-agent coordination for network anomaly detection, troubleshooting, and remediation using language models

QOE-DRIVEN PREDICTIVE NETWORKS

DYNAMIC CLASSIFICATION OF ONLINE APPLICATIONS BASED ON APPLICATION BEHAVIOR FOR COGNITIVE NETWORKS

QOE OPTIMIZED ELASTIC CLOUD NETWORKS

ESTIMATING USER SUITABILITY FOR COLLECTING APPLICATION QOE FEEDBACK

AUTOMATIC CURATION OF REUSABLE CODE SNIPPETS FOR LLM AGENTS

MEASURING PERFORMANCE IN COGNITIVE NETWORKS

Measuring performance in cognitive networks

PHYSICAL SPACE RECOMMENDATIONS TO OPTIMIZE USER APPLICATION QUALITY OF EXPERIENCE IN OFFICE ENVIRONMENTS

HIERARCHICAL MODELS USING SELF ORGANIZING LEARNING TOPOLOGIES

TEACHING LLM-BASED AGENTS TO TROUBLESHOOT NETWORKS USING REINFORCEMENT LEARNING

GENERATING NETWORK SCENARIOS TO TRAIN AN LLM-BASED NETWORK TROUBLESHOOTING AGENT

LLM-BASED AGENT AS A BACK-OFFICE VIRTUAL NETWORK TROUBLESHOOTING ASSISTANT

AI-BASED NETWORK TROUBLESHOOTING WITH EXPERT FEEDBACK

CITING SOURCES FROM USER INTERFACE VIEWS IN LLM-BASED NETWORK AGENTS

USING AN LLM-BASED AGENT TO PROVIDE SELF-HEALING CAPABILITIES TO A NETWORK

LLM-BASED NETWORK TROUBLESHOOTING USING EXPERT-CURATED RECIPES

USING A CURRICULUM FOR REINFORCEMENT LEARNING TO TRAIN AN LLM-BASED NETWORK TROUBLESHOOTING AGENT

OBJECTIVE SELECTION FOR LLM-BASED NETWORK TROUBLESHOOTING AND MONITORING AGENTS

EVALUATION FRAMEWORK FOR LLM-BASED NETWORK TROUBLESHOOTING AND MONITORING AGENTS

TESTING FRAMEWORK FOR LANGUAGE MODEL-BASED COMPUTER NETWORK TROUBLESHOOTING AGENTS

GENERATIVE MODELS TO CREATE NETWORK CONFIGURATIONS THROUGH NATURAL LANGUAGE PROMPTS

OPPORTUNISTIC RELAY AMONG MOBILE COMMUNICATION DEVICES

COMPUTER NETWORK MONITORING AND CONTROL USING A FINE-TUNED LANGUAGE MODEL

ADVERSARIAL TRAINING OF LANGUAGE MODELS TO PREVENT HIJACKING OF CONVERSATIONAL AGENTS

CLASSIFYING FAILURE MODES OF LARGE LANGUAGE MODELS (LLMS) FOR COMPUTER NETWORK ANALYTICS

USING A LARGE LANGUAGE MODEL FOR CODE GENERATION FOR NETWORK ANALYTICS WITH CODING HINTS

IDENTIFYING TRAFFIC SENSITIVE INTERFACES AND TRIGGERING CONFIGURATION CHANGES

PROACTIVE BYPASS SELECTION BASED ON ROOT CAUSE ANALYSIS OF TRACEROUTES

USING DISCRETIZED STATE-TRANSITIONS TO EXPLAIN AND TROUBLESHOOT APPLICATION EXPERIENCE DEGRADATION IN PREDICTIVE INTERNET

CONVERSATIONAL NETWORK ASSURANCE USING LARGE LANGUAGE MODELS

USER FEEDBACK COLLECTION FOR APPLICATION QOE PREDICTION

USING MACHINE LEARNING FOR ONLINE APPLICATION DETECTION

API CONSOLIDATION RECOMMENDATIONS TO IMPROVE WEB APPLICATION QOE

AI-DRIVEN WIRELESS RADIO RESOURCE MANAGEMENT FOR OPTIMIZATION OF USER EXPERIENCE

PRIVATE SD-WAN PEERING

INSPECTING GRADIENT BOOSTED TREES FOR NETWORK TROUBLESHOOTING AND APPLICATION OPTIMIZATION

APPLICATION QOE COMPARATIVE ANALYTICS FOR REMOTE VERSUS IN-OFFICE USERS

Estimating the need for user feedback in training multi-application QoE models

ROOT CAUSING NETWORK ISSUES USING CHAOS ENGINEERING

INFERRING QOE DEGRADATION FROM IMPLICIT SIGNALS IN USER BEHAVIOR

COMPUTING MOTIF SIGNATURES FOR QOE DISRUPTIONS

CROSS-APPLICATION PREDICTIVE ROUTING

IDENTIFYING NETWORK CONDITIONS ASSOCIATED WITH APPLICATION STATES

RECOMMENDATION GROUPING FOR PREDICTIVE NETWORKING

PREDICTIVE BGP PEERING

Learning probing strategies for QoE assessment

COGNITIVE NETWORKS

END USER RECOMMENDATION SERVICE TO ENSURE SATISFACTORY APPLICATION QOE

Gathering labels from proprietary applications for QoE predictions

USING NETWORK WATERFALL DATA TO ASSESS THE QOE OF WEB-BASED APPLICATIONS

RECOMMENDATION POLICY MANAGER FOR PREDICTIVE NETWORKING

Cognitive networking using a device endpoint agent

PREDICTIVE FAST REROUTE

LOCALIZATION OF QOE MODELS TO ACCOUNT FOR USER PREFERENCES AND BIASES

Feedback loop control of an online application based on network characteristics affecting user experience

End user recommendation service to ensure satisfactory application QoE

Robust training of application QoE prediction models

Application selection based on network characteristics

SYNCHRONIZED DETECTION OF WIRELESS DEVICE FRAME BY WIRELESS ACCESS POINTS FOR OPTIMIZED ACCESS POINT ALLOCATION BY NETWORK CONTROLLER

MOBILE NODE AWARENESS OF VIRTUAL ACCESS POINTS