large language models

A local non-containment in Step (v) of IUT IV, Theorem 1.10

Step (v) of the proof of Theorem 1.10 in Mochizuki's Inter-universal Teichmüller theory IV bounds, for each tuple of places, the log-volume of the corresponding component of the holomorphic hull of the union of possible images of a Θ-pilot object defined in Corollary 3.12 of the third paper. This note gives an explicit...

Age Is Not Evidence of Staleness: A Recency Decay Is a One-Rate Survival Model, the Rate Belongs to the Fact Rather Than the Clock, and the Silent Change Only a Rate Could Catch Is the Case No Agent-Memory Benchmark Scores

(c) 2026 Pranay Mahendrakar. Licensed under CC BY 4.0. Language agents that keep memories across sessions usually discount a record by how long ago it was written or last read. That discount was introduced to decide what an agent attends to, but it is increasingly read as a statement about whether a record is still tru...

A local non-containment in Step (v) of IUT IV, Theorem 1.10

Step (v) of the proof of Theorem 1.10 in Mochizuki's Inter-universal Teichmüller theory IV bounds, for each tuple of places, the log-volume of the corresponding component of the holomorphic hull of the union of possible images of a Θ-pilot object defined in Corollary 3.12 of the third paper. This note gives an explicit...

Age Is Not Evidence of Staleness: A Recency Decay Is a One-Rate Survival Model, the Rate Belongs to the Fact Rather Than the Clock, and the Silent Change Only a Rate Could Catch Is the Case No Agent-Memory Benchmark Scores

(c) 2026 Pranay Mahendrakar. Licensed under CC BY 4.0. Language agents that keep memories across sessions usually discount a record by how long ago it was written or last read. That discount was introduced to decide what an agent attends to, but it is increasingly read as a statement about whether a record is still tru...

ToshLLM: local LLM inference on Intel Macs with AMD GPUs

A native SwiftUI application that runs large language models locally on Intel Macs with AMD GPUs, a configuration mainstream inference stacks leave unsupported or incorrect. Beyond packaging, it contributes original work to the Metal backend of llama.cpp: ToshGEMM, a manually tiled matrix multiply that replaces the sim...

SPIRIT-CONSORT-ELM: element-level annotated dataset and large language model approach for assessing randomized controlled trial reporting

Abstract Randomized controlled trials (RCTs) are central to assessing the benefits and harms of interventions, but incomplete reporting undermines their verifiability and usefulness. Although SPIRIT and CONSORT reporting guidelines promote complete reporting of RCT protocols and results publications, many RCTs remain i...

Causal Encyclopedia

Causal Encyclopedia — Cumulative PASS295 A Canonical Knowledge Infrastructure for LLM-Assisted Reasoning The Causal Encyclopedia is a cumulative, machine-oriented knowledge infrastructure designed primarily to support large language models, reasoning systems, and human–AI research workflows. Rather than functioning as...

AutoQA-MAS: An LLM-Based Multi-agent System for Autonomous Website End-to-End Testing

Manual execution of website end-to-end (E2E) test cases is a repetitive, labour-intensive process that creates bottlenecks in modern software development workflows. We investigate the feasibility of automating this process using AutoQA-MAS, a large language model (LLM)-based multi-agent system (MAS) comprising four spe...

IWAC Sentiment Analysis Visualization

Interactive SvelteKit dashboard for exploring large language model sentiment annotations of the Islam West Africa Collection (IWAC), a corpus of 12,349 francophone West African press articles from 57 newspapers, published between 1961 and 2025 in Benin, Burkina Faso, Côte d'Ivoire, Niger and Togo. Each article is annot...

Little Brains, Big Feats: Exploring Compact Language Models

NRITYAM: Language Models Meet Art and Heritage of Dance

Deploying LLM Inference on a Repurposed UMA APU: Transferable Lessons from a Vulkan-Only, 16 GB Edge Platform

Cost-driven interest in running large language models (LLMs) on non-mainstream silicon outpaces the maturity of the surrounding software stacks. This paper uses one such platform, the AMD BC-250 (a repurposed cryptocurrency-mining board with a GFX1013 "Cyan Skillfish" accelerated processing unit (APU), 16 GB of unified...