Publications

Neither Valid Nor Reliable? Investigating the Use of LLMs as Judges

Khaoula Chehbouni

Mohammed Haddou

Jackie Cheung

Golnoosh Farnadi

2025-09-22

NeurIPS.cc/2025/Workshop/WiML (published)

openreview.net

Reasoning with Preference Constraints: A Benchmark for Language Models in Many-to-One Matching Markets

2025-09-22

NeurIPS.cc/2025/Workshop/WiML (published)

openreview.net

Revisiting Replay and Gradient Alignment for Continual Pre-Training of Large Language Models

Istabrak Abbes

Gopeshh Subbaraj

Matthew D Riemer

Nizar Islah

Benjamin Therien

Tsuguchika Tabaru

Hiroaki Kingetsu

Sarath Chandar

Irina Rish

2025-09-22

NeurIPS.cc/2025/Workshop/WiML (published)

doi.org

openreview.net

Reward the Reward Designer: Making Reinforcement Learning Useful for Clinical Decision Making

Sumana Basu

Adriana Romero Soriano

Doina Precup

2025-09-22

NeurIPS.cc/2025/Workshop/WiML (published)

openreview.net

Say It Another Way: Auditing LLMs with a User-Grounded Automated Paraphrasing Framework

Clea Chataigner

Rebecca Ma

Prakhar Ganesh

Afaf Taïk

Elliot Creager

Golnoosh Farnadi

2025-09-22

NeurIPS.cc/2025/Workshop/WiML (published)

openreview.net

Towards Democratizing LLMs: Investigating Multilingual Mixture-of-Experts Models

2025-09-22

NeurIPS.cc/2025/Workshop/WiML (published)

openreview.net

Unifying Mechanistic Interpretations of Neural Networks Trained on Modular Addition

Gabriela Moisescu-Pareja

Gavin McCracken

Vincent Létourneau

Doina Precup

Jonathan Love

2025-09-22

NeurIPS.cc/2025/Workshop/WiML (published)

openreview.net

FocalCodec-Stream: Streaming Low-Bitrate Speech Coding via Causal Distillation

Luca Della Libera

Cem Subakan

Mirco Ravanelli

Neural audio codecs are a fundamental component of modern generative audio pipelines. Although recent codecs achieve strong low-bitrate reco… (see more)nstruction and provide powerful representations for downstream tasks, most are non-streamable, limiting their use in real-time applications. We present FocalCodec-Stream, a hybrid codec based on focal modulation that compresses speech into a single binary codebook at 0.55 - 0.80 kbps with a theoretical latency of 80 ms. Our approach combines multi-stage causal distillation of WavLM with targeted architectural improvements, including a lightweight refiner module that enhances quality under latency constraints. Experiments show that FocalCodec-Stream outperforms existing streamable codecs at comparable bitrates, while preserving both semantic and acoustic information. The result is a favorable trade-off between reconstruction quality, downstream task performance, latency, and efficiency. Code and checkpoints will be released at https://github.com/lucadellalib/focalcodec.

2025-09-19

ArXiv (preprint)

arxiv.org