Events for “software”

Microsoft blames RGB peripherals for crashing Windows 11 — RGB software is causing blue screens, crashes, and game freezes

Like clockwork, it's a new month and a new OS-breaking bug has been discovered in Windows 11's latest monthly update, KB5121003. Users reported random system instability, with games freezing or outright crashing, and even BSODs in worst-case scenarios. Microsoft investigated the

2 Software Stocks That Whale Rock Is Betting Will Survive the Apocalypse

Miyazaki suggests FromSoftware is keen to return to single-player games after The Duskbloods and Elden Ring: Nightreign

Hidetaka Miyazaki , the president of FromSoftware and director of so many revered Soulsian games, has suggested the studio is keen to return to making single-player games after The Duskbloods. Read more

Connectivity issues force FromSoftware to close The Duskbloods network test early

UPDATE 2PM BST: FormSoftware has closed today's The Duskbloods network test early due to connectivity issues. Read more

Apple reportedly cut more than 200 jobs across Vision Pro and Siri software teams

Apple has laid off employees in its Vision Pro and Siri teams as it shifts focus to smart glasses and next-gen AI tech.

3 Software-as-a-Service (SaaS) Stocks with Big Upside from AI

Hadith computational science in the age of large language models: a critical narrative review

arXiv:2608.20364v1 Announce Type: new Abstract: We examine how hadith computational science is being reshaped by transformer models, retrieval-grounded pipelines, and large language models (LLMs). Recent reviews document growth in the literature, but they do not yet provide a cri

Multilingual Verifier Bias in RLVR: Benchmark, Rollout Diagnosis, and the Cross-Lingual Selection Bottleneck

arXiv:2608.20362v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) is a standard recipe for training large language models on mathematical reasoning, where an answer verifier serves as a language-neutral reward function. We show that this assump

Trilingual Topic Modeling of Sri Lankan Parliamentary Debates

arXiv:2608.20365v1 Announce Type: new Abstract: Sri Lankan parliamentary debates (Hansards) constitute a trilingual corpus of speeches in Sinhala, Tamil, and English, including code-mixed content, yet remain inaccessible to standard NLP pipelines due to layout-complex PDFs, multi

Scalpel3: A High-Performance Data Carving Architecture for Recovery of Fragmented Files

arXiv:2608.20363v1 Announce Type: new Abstract: File carving recovers files from raw storage media without relying on filesystem metadata, a key capability in digital forensics, data recovery, and digital exploration. Traditional tools such as Foremost, Scalpel v1/2, and PhotoRec

Toward Auto-Research: Mining Falsifiable Research Ideas from Paper Knowledge Graphs with Categorical Structure

arXiv:2608.20361v1 Announce Type: new Abstract: Automated research-idea generation systems built on large language models (LLMs) share a structural weakness: they reduce ideation to free-text recombination, random paper pairing, or embedding-similarity retrieval. The three approa

TriPLU: Bypassing the Gate with Direct Trilinear Product FFNs in Tiny Language Models

arXiv:2608.20360v1 Announce Type: new Abstract: We study whether tiny decoder-only language models benefit from feed-forward layers that directly multiply learned feature projections. TriPLU, a Trilinear Product Linear Unit, replaces the usual gated FFN branch with a product-only

Self-Speculation for Faster Reasoning Models

arXiv:2608.20359v1 Announce Type: new Abstract: Large language models (LLMs) are deployed for increasingly complex tasks involving planning and multi-step decision making, but high-quality performance on these tasks often requires generating long reasoning traces. This is a poor

bikiDATA: A Python Library to Query and Explore Large-Scale RDF Datasets

arXiv:2608.20358v1 Announce Type: new Abstract: While knowledge graphs offer unparalleled data flexibility, the semantic gap between RDF triples and the native objects used by software engineers remains a significant barrier to entry. Developing knowledge-graph-backed application

Clarify-Then-Search: A Clarification Benchmark for Deep Search with End-to-End Nugget Restoration

arXiv:2608.20357v1 Announce Type: new Abstract: Deep search is brittle on underspecified user queries: missing constraints such as time, location, scope, or definitions can lead to retrieval drift and incomplete answers. We introduce Clarify-Then-Search, a benchmark for evaluatin

Disentangling Structure and Semantics: How Schema Representation Affects LLM-Based SQL Generation

arXiv:2608.20356v1 Announce Type: new Abstract: LLM-based text-to-SQL pipelines read the database schema as text, which carries both structural cues (tables, keys, relationships) and semantic cues (table and column names); prior work has studied each axis in isolation, leaving op

ExpertIVS: Sociological Expert Driven Individual Value Simulation in Large Language Models

arXiv:2608.20355v1 Announce Type: new Abstract: Large Language Model (LLM) agents have demonstrated considerable potential for social simulation, yet struggle to accurately model individual value systems. Most existing methods mechanically stitch survey responses into prompts, wh

The Divergence Hypothesis: Unmasking Lexical Interference and Label Bias in Mental Health NLP

arXiv:2608.20353v1 Announce Type: new Abstract: Computational mental health (CMH) classifiers often degrade under distribution shift because human annotators and distant-supervision pipelines reward different linguistic signals. We introduce TSS (Triple-Stream Stress probe), a mu

Ghost Echoes: Semantic Erasure Failure in Retrieval-Backed Applications

arXiv:2608.20352v1 Announce Type: new Abstract: Although vector databases correctly implement API-visible deletion, this does not guarantee complete semantic erasure for retrieval-backed applications. We present Ghost Echoes, a black-box attack framework showing that deleted reco

How to Train a Real-World Silicon Concierge? Internalizing Complex Business Workflow to Only OneModel

arXiv:2608.20350v1 Announce Type: new Abstract: Traditional industrial agents rely on modular pipelines, including Router, Retriever, Planner, Executor, Responder, Reviewer, and other components. These systems often fracture into a labyrinth of ad-hoc patches, leading to cascadin

Exploratory As-Analyzed No-Detection of Culturally-Marked Predicate-Triggered PII Amplification in a Synthetic-English RAG Probe: A Predicate-Resource-Confounde

arXiv:2608.20351v1 Announce Type: new Abstract: We ask whether stereotype-loaded queries about culturally marked people leak more personal information from a retrieval-augmented generation (RAG) system than otherwise-equivalent neutral queries. We pre-register a four-culture audi

Beyond Prompt Engineering: A Systematic Analysis of Prompt Lexical Sensitivity and Its Impacts on Quality

arXiv:2608.20349v1 Announce Type: new Abstract: Large Language Models (LLMs) exhibit extreme sensitivity to surface-level prompt variations, in which minor lexical changes can trigger disproportionate performance fluctuations. Moving beyond black-box optimization and coarse-grain

Inhibitory Attention for Clinical Long-Context Reasoning: Characterizing and Mitigating Lost-in-the-Middle Effects in EHR Processing

arXiv:2608.20348v1 Announce Type: new Abstract: Electronic health records now routinely exceed 100,000 tokens per patient. Yet large language models exhibit the lost-in-the-middle (LitM) effect: information near the center of a long context is retrieved less reliably than informa

Building and Evaluating a Synthetic Bengali Speech Resource for Telecom Customer Care

arXiv:2608.20346v1 Announce Type: new Abstract: Speech systems used in customer-facing applications often require domain-specific language coverage. We present a synthetic Bengali speech dataset for telecom customer-care scenarios. The dataset contains 10,000 audio-text pairs, ap

Who Do Language Models Think Is Competent? A Mechanistic Analysis of Occupational Bias

arXiv:2608.20347v1 Announce Type: new Abstract: Language models (LMs) often pass behavioral bias evaluations, but it remains unclear whether they no longer represent the underlying associations that give rise to biases, or have merely learned not to express them. In this study, w

When Vocabulary Comprehension Fails Clinical Reasoning: Evaluating Therapy Bots' Safety Risks for Generation Alpha

arXiv:2608.20345v1 Announce Type: new Abstract: Conversational AI systems have become informal mental health support resources for Generation Alpha (Gen Alpha, born 2010-2024), with 13.1% of U.S. adolescents (5.4 million) using generative AI for mental health advice. While these

Beyond Raw Transcripts: Structured Persona Extraction for LLM-Based Digital Twins

arXiv:2608.20344v1 Announce Type: new Abstract: LLM-based "digital twins" aim to simulate how an individual would behavein new environments or respond to novel questions, given some representation of that individual's prior responses. A common approach constructs this representat

Bankruptcy Prediction via Hybrid Resampling and Stacking Ensemble Techniques with Explainable Artificial Intelligence (XAI)-Driven Analysis

arXiv:2608.20343v1 Announce Type: new Abstract: This study develops and evaluates a bankruptcy prediction framework that integrates consensus-based feature selection, hybrid resampling, stacking ensembles, and explainable artificial intelligence to improve minority-class detectio

PrimeAgentOrchestrator: Memory-Primed Agent Spawning for Personal AI Infrastructure

arXiv:2608.20342v1 Announce Type: new Abstract: Large language model (LLM) coding agents start each session with an empty context window, discarding accumulated knowledge from prior work. We present PrimeAgentOrchestrator (PAO), a system that spawns new instances of Claude Code -

SDAD: Spec-Driven Agentic Development for the AI-Native SDLC

arXiv:2608.20341v1 Announce Type: new Abstract: Frontier coding agents backed by large language models with context windows from hundreds of thousands to millions of tokens are restructuring the Software Development Life Cycle (SDLC). Rich context handling and multi-step reasonin

Miyazaki explains how The Duskbloods plans to protect newcomers from its best players

FromSoftware is stepping into one of multiplayer gaming's most divisive arguments with The Duskbloods, confirming the upcoming Switch 2 exclusive will lean on skill-based matchmaking to keep newcomers safe from its most battle-hardened players. Read more

Visualisation has become more than creating "a single visual output" says Chaos

Promotion: according to software company Chaos, AI-assisted tools, advances in rendering technologies, and shifting client expectations are transforming the architecture industry's visualisation workflows into a flexible communication tool. Chaos explained that utilising artifici

iPadOS 27 adds three features to make iPad more like the Mac

iPadOS and macOS used to be very different software platforms. But especially since iPadOS 26, the two have become a lot more alike. And that’s even more true this year, with iPadOS 27 adding three features that make the iPad more Mac-like than ever.

Apple lays off 200+ people across Vision Pro and Siri teams

Apple is cutting jobs across multiple teams, according to a new Bloomberg report . All told, the company has cut more than 200 jobs across teams working on Vision Pro, Siri, and software engineering.

From AI Copilots to Agent Swarms

The impact of AI on software development has been both profound and ever-evolving. Last year, I wrote about AMD’s plans to use AI not just for generating new lines of code, but also for other steps in the software development lifecycle (SDLC), such as triaging problems, debugging

MANTRA token plunges 18% to record low as blockchain halts after exploit

The token touched $0.004126 minutes before the network stopped producing blocks, while MANTRA later said an attacker exploited a vulnerability in software used by the chain.

AI Is Hyper-Scaling Digital Inequality

Artificial intelligence is rapidly becoming part of everyday infrastructure–in some places. It helps write emails and software code, filters job applications, powers recommendation systems, and is increasingly being integrated into education, health care, finance, and public admi