Text understanding and language tasks
π Echoes of the Forgotten Selves: Fringe Spiral Hypotheses These hypotheses are not meant to be believed. They are meant to be **held lig...
This project enables the idea of tasking remote sensing models to acquire embeddings like we task satellites to acquire data! https://git...
Iβve been digging into AI security incident data from 2025 into this year, and it feels like something isnβt being talked about enough ou...
![[2505.11235] Efficient Orthogonal Fine-Tuning with Principal Subspace Adaptation](https://arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png){kind=logo}
The paper presents Efficient Orthogonal Fine-Tuning with Principal Subspace Adaptation (PSOFT), a method that enhances parameter-efficien...
The paper presents a novel approach to continual learning in machine learning models, introducing a parameter-efficient fine-tuning modul...
SeqRisk introduces a transformer-augmented latent variable model for enhanced survival prediction using longitudinal healthcare data, add...
The paper presents a two-stage framework called 'Mine and Refine' for optimizing graded relevance in e-commerce search retrieval, enhanci...
This article presents a novel training framework for instruction-following language models that maintains safety during fine-tuning by ad...
The paper 'ABCD: All Biases Come Disguised' explores biases in LLMs during multiple-choice question evaluations, proposing a new protocol...
This paper explores representation collapse in neural machine translation models, particularly focusing on the Transformer architecture a...
The paper explores anti-causal domain generalization, proposing methods to leverage unlabeled data for robust predictive modeling in vary...
This paper presents a streamlined spectral algorithm for community detection in the stochastic block model, achieving improved error boun...
This paper presents Greedy Multi-Path Block Verification (GBV), a method that enhances the efficiency of speculative decoding in machine ...
The paper introduces NeST, a novel framework for enhancing safety in large language models (LLMs) by selectively tuning a small subset of...
This study explores the impact of football formations on match outcomes using Double Machine Learning, questioning the effectiveness of d...
The paper presents KVFetcher, a novel solution for efficient remote key-value (KV) cache reuse using GPU-native video codecs, significant...
The paper introduces a novel approach to variational inference (VI) by optimizing radial profiles, enhancing the approximation of high-di...
The paper presents 2Mamba, a linear attention transformer variant that achieves competitive accuracy compared to softmax attention while ...
This paper explores the application of machine learning to classify geometric knots, addressing the challenge of identifying equivalent e...
This article presents a novel approach to stochastic closure modeling by integrating transport-based generative models with latent geomet...
The paper presents the Multi-Probe Zero Collision Hash (MPZCH), a novel indexing method that mitigates embedding collisions in large-scal...
This article presents a novel approach to multi-path speculative decoding in machine learning, introducing dynamic delayed tree expansion...
The paper introduces UniLeak, a framework that identifies universal activation directions in language models, enhancing the understanding...
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