Text Classification

Clinical language models can achieve strong in-hospital accuracy yet fail under deployment shifts because they exploit note-specific artifacts (e.g., templates, separators, boilerplate) that do not reflect patient state.…

Mortality Prediction Text Classification

HelaBERT: Enhancing Sinhala Language Understanding with Dual Pooling Classification Head

2026-08-24 · Thisen Ekanayake, Nisansa de Silva arxiv

We present HelaBERT, a family of two BERT-based masked language models pre-trained from scratch on approximately 1 billion tokens of Sinhala text sourced from MADLAD-400, CulturaX, and a custom corpus comprising news art…

Text Classification Sentiment Analysis

MIL-BERT: Classification of Arbitrarily Large Text with Performance and Explanatory Guarantees

2026-08-21 · John Cadigan, Dayne Freitag, Eric Yeh arxiv

Many text classification decisions are viable based on constituent excerpts alone. Taking inspiration from the field of multiple instance learning, we present an algorithm for training a neural network to classify text b…

Multiple Instance Learning Text Classification

Task-CoEvolve: Efficient Harness Optimization via Adaptive Validation Task Selection

2026-08-20 · Atsuyuki Miyai, Kiyoharu Aizawa, Toshihiko Yamasaki arxiv

We present a novel approach to efficient LLM harness optimization through adaptive validation task selection. Harness optimization iteratively rewrites the harness code based on validation performance, enabling substanti…

Text Classification

FraQ: Efficient Coordinate-Space Recompression for Federated Low-Rank Adaptation

2026-08-04 · Shenghui Li, Thiemo Voigt arxiv

Federated fine-tuning with Low-Rank Adaptation (LoRA) enables efficient collaborative adaptation of Large Language Models (LLMs) without centralizing private data. However, LoRA's two-factor parameterization creates an a…

Text Classification

Relative Parameter Importance in Task-Agnostic Replay-Free Continual Learning

2026-08-01 · Malavika Suresh, Ikechukwu Nkisi-Orji, Nirmalie Wiratunga arxiv

Achieving continual learning (CL) with deep neural networks requires balancing stability and plasticity while enabling knowledge transfer. In this work, we focus on offline learning algorithms under the constraints: (I) …

Incremental Learning Text Classification Continual Learning Text Generation

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