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cs.CL2026

Not All Fallbacks Are Failures: Understanding and Recovering from Fallbacks in Mobile Voice Assistants

Phillip Schneider, Alexandre Mercier, Joshua Oehms +2

Robust understanding of user input is a core requirement for voice assistants deployed in real-world environments. In practice, these systems encounter heterogeneous fallback situa…

cs.CL2026

GAMBIT: A Three-Mode Benchmark for Adversarial Robustness in Multi-Agent LLM Collectives

Alexandre Le Mercier, Chris Develder, Thomas Demeester

In multi-agent systems (MAS), a single deceptive agent can nullify all gains of an agentic AI collective and evade deployed defenses. However, existing adversarial studies on MAS t…

cs.CL2026

CLASP: Defending Hybrid Large Language Models Against Hidden State Poisoning Attacks

Alexandre Le Mercier, Thomas Demeester, Chris Develder

State space models (SSMs) like Mamba have gained significant traction as efficient alternatives to Transformers, achieving linear complexity while maintaining competitive performan…

cs.CL2026

Hidden State Poisoning Attacks against Mamba-based Language Models

Alexandre Le Mercier, Chris Develder, Thomas Demeester

State space models (SSMs) like Mamba offer efficient alternatives to Transformer-based language models, with linear time complexity. Yet, their adversarial robustness remains criti…

cs.CL2025

JaccDiv: A Metric and Benchmark for Quantifying Diversity of Generated Marketing Text in the Music Industry

Anum Afzal, Alexandre Mercier, Florian Matthes

Online platforms are increasingly interested in using Data-to-Text technologies to generate content and help their users. Unfortunately, traditional generative methods often fall i…