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YHN3h ago

3.6

Ask HN: What are you building that's not AI related?

I don&x27;t have anything against AI, but HN (and everywhere else) seems to be drowning in AI atm.<pSeems like every man and his dog is building an AI agent harness. And power to you (and your dog) if that&x27;s you.<pBut it would be refreshing to hear about some non AI related projects people are w

arXiv7h ago

4.3

Cross-Lingual Transfer and Parameter-Efficient Adaptation in the Turkic Language Family: A Theoretical Framework for Low-Resource Language Models

arXiv:2604.06202v1 Announce Type: new Abstract: Large language models (LLMs) have transformed natural language processing, yet their capabilities remain uneven across languages. Most multilingual models are trained primarily on high-resource languages, leaving many languages with large speaker popul

arXiv7h ago

4.8

Beyond Facts: Benchmarking Distributional Reading Comprehension in Large Language Models

arXiv:2604.06201v1 Announce Type: new Abstract: While most reading comprehension benchmarks for LLMs focus on factual information that can be answered by localizing specific textual evidence, many real-world tasks require understanding distributional information, such as population-level trends and

arXiv7h ago

4.3

Temporally Phenotyping GLP-1RA Case Reports with Large Language Models: A Textual Time Series Corpus and Risk Modeling

arXiv:2604.06197v1 Announce Type: new Abstract: Type 2 diabetes case reports describe complex clinical courses, but their timelines are often expressed in language that is difficult to reuse in longitudinal modeling. To address this gap, we developed a textual time-series corpus of 136 PubMed Open A

arXiv7h ago

4.8

Consistency-Guided Decoding with Proof-Driven Disambiguation for Three-Way Logical Question Answering

arXiv:2604.06196v1 Announce Type: new Abstract: Three-way logical question answering (QA) assigns $True/False/Unknown$ to a hypothesis $H$ given a premise set $S$. While modern large language models (LLMs) can be accurate on isolated examples, we identify two recurring failure modes in 3-way logic Q

arXiv7h ago

4.8

Depression Detection at the Point of Care: Automated Analysis of Linguistic Signals from Routine Primary Care Encounters

arXiv:2604.06193v1 Announce Type: new Abstract: Depression is underdiagnosed in primary care, yet timely identification remains critical. Recorded clinical encounters, increasingly common with digital scribing technologies, present an opportunity to detect depression from naturalistic dialogue. We i

arXiv7h ago

4.5

The Stepwise Informativeness Assumption: Why are Entropy Dynamics and Reasoning Correlated in LLMs?

arXiv:2604.06192v1 Announce Type: new Abstract: Recent work uses entropy-based signals at multiple representation levels to study reasoning in large language models, but the field remains largely empirical. A central unresolved puzzle is why internal entropy dynamics, defined under the predictive di

arXiv7h ago

3.0

LLM-Augmented Knowledge Base Construction For Root Cause Analysis

arXiv:2604.06171v1 Announce Type: new Abstract: Communications networks now form the backbone of our digital world, with fast and reliable connectivity. However, even with appropriate redundancy and failover mechanisms, it is difficult to guarantee "five 9s" (99.999 %) reliability, requiring rapid a

arXiv7h ago

4.6

Bridging Theory and Practice in Crafting Robust Spiking Reservoirs

arXiv:2604.06395v1 Announce Type: new Abstract: Spiking reservoir computing provides an energy-efficient approach to temporal processing, but reliably tuning reservoirs to operate at the edge-of-chaos is challenging due to experimental uncertainty. This work bridges abstract notions of criticality a