Running a large language model on a PlayStation 2 - Adafruit
Running a large language model on a PlayStation 2 Adafruit
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Inter-Speaker Relative Cues for Two-Stage Text-Guided Target Speech Extraction
arXiv:2603.01316v2 Announce Type: replace Abstract: This paper investigates the use of relative cues for text-based target speech extraction (TSE). We first provide a theoretical justification for relative cues from the perspectives of human perception and label quantization, showing that relative cues preserve fine-grained distinctions that are often lost in absolute categorical representations for continuous-valued attributes. Building on this analysis, we propose a two-stage TSE framework in which a speech separation model first generates candidate sources, followed by a text-guided classifier that selects the target speaker based on embedding similarity. Within this framework, we train two separate classification models to evaluate the advantages of relative cues over independent cues
Empirical and Statistical Characterisation of 28 GHz mmWave Propagation in Office Environments
arXiv:2604.01814v1 Announce Type: new Abstract: Millimeter wave (mmWave) technology at 28 GHz is vital for beyond-5G systems, but indoor deployment remains challenging due to limited statistical evidence on propagation. This study investigates path loss, material penetration, and coverage enhancement using TMYTEK-based measurements. Statistical tests and confidence interval analysis show that path loss aligns with free-space theory, with an exponent of n = 2.07 plus or minus 0.073 (p = 0.385), confirming the suitability of classical models. Material analysis reveals significant variation: desk dividers introduce 3.4 dB more attenuation than display boards (95 percent CI: 1.81 to 4.98 dB, p less than 0.01), contradicting thickness-based assumptions. Reflector optimisation yields a significa
MIMO Capacity Enhancement by Grating Walls: A Physics-Based Proof of Principle
arXiv:2604.01786v1 Announce Type: new Abstract: This paper investigates the passive enhancement of MIMO spectral efficiency through boundary engineering in a simplified two dimensional indoor proof of principle model. The propagation channel is constructed from the electromagnetic Green's function of a room with boundaries modeled as free space, drywall, perfect electric conductor (PEC), or binary gratings. Within this framework, grating coated walls enrich the non line of sight (NLoS) multipath field, reduce channel correlation, and enhance spatial multiplexing over a broad range of receiver locations. Comparisons with the drywall and PEC reference cases further reveal that the observed capacity enhancement arises not from diffraction alone, but from the combined effects of effective wall
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Tracking the emergence of linguistic structure in self-supervised models learning from speech
arXiv:2604.02043v1 Announce Type: cross Abstract: Self-supervised speech models learn effective representations of spoken language, which have been shown to reflect various aspects of linguistic structure. But when does such structure emerge in model training? We study the encoding of a wide range of linguistic structures, across layers and intermediate checkpoints of six Wav2Vec2 and HuBERT models trained on spoken Dutch. We find that different levels of linguistic structure show notably distinct layerwise patterns as well as learning trajectories, which can partially be explained by differences in their degree of abstraction from the acoustic signal and the timescale at which information from the input is integrated. Moreover, we find that the level at which pre-training objectives are d
My most common research advice: do quick sanity checks
Written quickly as part of the Inkhaven Residency . At a high level, research feedback I give to more junior research collaborators often can fall into one of three categories: Doing quick sanity checks Saying precisely what you want to say Asking why one more time In each case, I think the advice can be taken to an extreme I no longer endorse. Accordingly, I’ve tried to spell out the degree to which you should implement the advice, as well as what “taking it too far” might look like. This piece covers doing quick sanity checks, which is the most common advice I give to junior researchers. I’ll cover the other two pieces of advice in a subsequent piece. Doing quick sanity checks Research is hard (almost by definition) and people are often wrong. Every researcher has wasted countless hours
Fast dynamical similarity analysis
arXiv:2511.22828v2 Announce Type: replace-cross Abstract: Understanding how nonlinear dynamical systems (e.g., artificial neural networks and neural circuits) process information requires comparing their underlying dynamics at scale, across diverse architectures and large neural recordings. While many similarity metrics exist, current approaches fall short for large-scale comparisons. Geometric methods are computationally efficient but fail to capture governing dynamics, limiting their accuracy. In contrast, traditional dynamical similarity methods are faithful to system dynamics but are often computationally prohibitive. We bridge this gap by combining the efficiency of geometric approaches with the fidelity of dynamical methods. We introduce fast dynamical similarity analysis (fastDSA),
Combining Masked Language Modeling and Cross-Modal Contrastive Learning for Prosody-Aware TTS
arXiv:2604.01247v1 Announce Type: cross Abstract: We investigate multi-stage pretraining for prosody modeling in diffusion-based TTS. A speaker-conditioned dual-stream encoder is trained with masked language modeling followed by SigLIP-style cross-modal contrastive learning using mixed-phoneme batches, with an additional same-phoneme refinement stage studied separately. We evaluate intrinsic text-audio retrieval and downstream synthesis in Grad-TTS and a latent diffusion TTS system. The two-stage curriculum (MLM + mixed-phoneme contrastive learning) achieves the best overall synthesis quality in terms of intelligibility, speaker similarity, and perceptual measures. Although same-phoneme refinement improves prosodic retrieval, it reduces phoneme discrimination and degrades synthesis. These
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