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20222026
most citedScalable Collaborative Learning via Representation Sharing

1 citations · 1 across the 17 of their papers we have counts for

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cs.SD2026

Geometric Iterative Retrieval for Neural Audio Codec Resynthesis

Leo Schmidt-Traub, Frédéric Berdoz, Luca A. Lanzendörfer +1

Neural audio codecs based on Residual Vector Quantization (RVQ) have become the dominant discrete representation for token-based general audio generation, yet resynthesizing high-q…

cs.LG2026

Post-Training Speech Enhancement Language Models with Perceptual Rewards

Frédéric Berdoz, Luca A. Lanzendörfer, Antonis Asonitis +1

Speech enhancement language models achieve strong results when trained on discrete audio tokens, but their optimization relies on token-level cross-entropy rather than the perceptu…

cs.LG2026

Data Attribution in Large Language Models via Bidirectional Gradient Optimization

Frédéric Berdoz, Luca A. Lanzendörfer, Kaan Bayraktar +1

Large Language Models (LLMs) are increasingly deployed across diverse applications, raising critical questions for governance, accountability, and data provenance. Understanding wh…

cs.AI2026

Reasoning Structure of Large Language Models

Frédéric Berdoz, Luca A. Lanzendörfer, Fabian Farestam +1

Large reasoning models (LRMs) are often evaluated using metrics such as final-answer accuracy or token count. However, identical scores on these metrics can hide fundamentally diff…

cs.LG2026

TreeFlash: Parallel AR-Approximation for Faster Speculative Decoding

Peer Rheinboldt, Frédéric Berdoz, Roger Wattenhofer

One-shot block drafters for speculative decoding generate the full draft in a single forward pass, achieving strong throughput by eliminating sequential token generation. However,…

cs.LG2026

N-vium: Mixture-of-Exits Transformer for Accelerated Exact Generation

Aleksander Lorenc, Frédéric Berdoz, Joël Mathys +1

Improving the inference efficiency of autoregressive transformers typically means reducing FLOPs per token, usually through approximations that degrade model quality. We introduce…

cs.CL2026

WorldSpeech: A Multilingual Speech Corpus from Around the World

Antonis Asonitis, Luca A. Lanzendörfer, Frédéric Berdoz +1

Automatic speech recognition (ASR) performs well for high-resource languages with abundant paired audio-transcript data, but its accuracy degrades sharply for most languages due to…

cs.CL2026

Reasoning Boosts Opinion Alignment in LLMs

Frédéric Berdoz, Yann Billeter, Yann Vonlanthen +1

Opinion modeling aims to capture individual or group political preferences, enabling applications such as digital democracies, where models could help shape fairer and more popular…

cs.MA2026

Can AI Agents Agree?

Frédéric Berdoz, Leonardo Rugli, Roger Wattenhofer

Large language models are increasingly deployed as cooperating agents, yet their behavior in adversarial consensus settings has not been systematically studied. We evaluate LLM-bas…

cs.LG2026

Subliminal Signals in Preference Labels

Isotta Magistrali, Frédéric Berdoz, Sam Dauncey +1

As AI systems approach superhuman capabilities, scalable oversight increasingly relies on LLM-as-a-judge frameworks where models evaluate and guide each other's training. A core as…