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The Anatomy of a Prompt Injection: A Component Model for Structured Analysis

arXiv:2608.07808v1 Announce Type: cross Abstract: Four years after prompt injection was first identified in 2022, attacks are still predominantly documented as verbatim strings rather than structured

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The Announcement Carries the Cue: Markup, Boundaries, and the Notation of Pre-Training Corpora

DGX agent

arXiv:2608.09093v1 Announce Type: cross Abstract: How a document's arrangement is written down, its notation, is a training variable that no dataset card records. The field has established that text-e

researcharxiv-cs-ai

11 Aug 2026

The Authority Expectancy Effect in Multi-User Conflict

arXiv:2608.08026v1 Announce Type: new Abstract: We investigate how social authority (SA) signals interact with severity-based prioritization in large language models, operationalizing each axis as a m

The Belief-Desire-Intention Ontology for modelling mental reality and agency

arXiv:2511.17162v2 Announce Type: replace Abstract: The Belief-Desire-Intention (BDI) model is a cornerstone for representing rational agency in artificial intelligence and cognitive sciences. Yet, it

agentsarxiv-cs-ai

The Capability Ladder: A Curriculum-Modernization Framework for Workforce Readiness in the AI Era

arXiv:2608.07779v1 Announce Type: new Abstract: Artificial intelligence is changing the task composition of computing work faster than curricula and training typically adapt. This is a curriculum-fram

agentsarxiv-cs-ai

The Cell Must Go On: Agar.io for Continual Reinforcement Learning

arXiv:2505.18347v3 Announce Type: replace-cross Abstract: Continual reinforcement learning (RL) concerns agents that are expected to learn continually, rather than converge to a policy that is then fi

The ChatGPT desktop app is now available in preview for desktop variants of these Linux distributions: • Ubuntu 24.04 LTS and 26.04 LTS • De…

The ChatGPT desktop app is now available in preview for desktop variants of these Linux distributions: • Ubuntu 24.04 LTS and 26.04 LTS • Debian 13 • Fedora 43 and 44 Install with .deb or .rpm package

model-releasesopenai--x

The Collaboration Gap: Exploration and Benchmarking of Open-World Agentic Cooperation

arXiv:2511.02687v2 Announce Type: replace Abstract: The trajectory of AI development suggests that we will increasingly rely on agent-based systems powered by language models, composed of independentl

The Cost of Adaptivity: Matching Lower Bounds Across Learning Problems

model-releasesarxiv-cs-lg

arXiv:2608.08826v1 Announce Type: new Abstract: Adaptive procedures must work without nuisance information an oracle may use, such as a gradient scale or smoothness index, and robust procedures may ha

The Download: the next big thing in LLMs and how AI academic research is shifting

This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. These startups are chasing the next big thing in LLMs Nine yea

researchmit-tech-review

The Evolution of Mixture-of-Experts Architectures in Large Language Models: Routing, Topology, Load Balancing, and Expert Parallelism

arXiv:2608.08650v1 Announce Type: new Abstract: Mixture-of-Experts models increase parameter capacity while keeping the computation activated by each token bounded, but their architectural evolution c

The Field Knows: Cross-Dimensional Geometry from Navigation to Black Holes

arXiv:2608.07566v1 Announce Type: new Abstract: We introduce a continuous metric field framework trained by a single causal contrastive loss. The framework encodes a scene into coefficients of a fixed

The Judge Knows When It Knows: Calibrated Abstention for LLM-Based A/B-Test Prediction

arXiv:2608.07517v1 Announce Type: cross Abstract: Can a multimodal LLM predict which version of a web page will win a real A/B test from screenshots alone? We report the most complete answer we are aw

The Knowing-Saying Gap: When Probes See Errors that Confidence Misses

arXiv:2608.07528v1 Announce Type: new Abstract: Linear probes detect corrupted context in language models with near-perfect accuracy, yet this does not translate into reliable failure prediction. The

The Neural Division of Labor: Biologically-Inspired Modular Architectures for Robust Neuromorphic Computing

arXiv:2608.08317v1 Announce Type: new Abstract: Biological neural systems achieve high efficiency and robustness through compartmentalized architectures. In contrast, modern artificial neural networks

researcharxiv-cs-lg

The No-Meaning Falsity: The Structural Impossibility of the Arbitrary Sign in Classical Arabic

arXiv:2608.07737v1 Announce Type: new Abstract: This paper investigates whether the postmodern claim of unrestricted semantic indeterminacy, and its foundational Saussurean axiom of the arbitrary sign

researcharxiv-cs-cl

The Politician, the Liar, and the Obedient Worker: Emerging Behavior of LLM Agents in Hierarchical Games

arXiv:2608.09574v1 Announce Type: new Abstract: LLMs are rapidly embedding themselves into daily life: drafting our emails, managing our schedules, and making decisions on our behalf. As they move fro

The Replay Gap: Static Evaluation of Model Switching in LLM Agents Scores the Wrong World

arXiv:2608.08239v1 Announce Type: cross Abstract: LLM routers promise efficiency by matching each request to the cheapest adequate model, and are increasingly applied per step inside multi-step agents

agentsarxiv-cs-cl

The Sample Complexity of Policy Learning with Mu-Resets

arXiv:2608.07772v1 Announce Type: new Abstract: We study policy-based reinforcement learning under the mu-resets interaction protocol of Kakade and Langford [KL02]. This interaction protocol enables t

safetyarxiv-cs-lg

The Scaffolding Matters More Than the Interface: A Controlled Comparison of MCP and CLI Tool Use Across Seven Agent Scaffoldings, Five Language Models, and One Software Task

arXiv:2608.08654v1 Announce Type: new Abstract: How much an AI coding agent costs to run can depend more on the agent scaffolding that drives it than on the interface through which it reaches its tool

The Scaling Paradox in Human-AI Collaboration

arXiv:2608.00818v2 Announce Type: replace Abstract: The discovery of scaling laws has highlighted the extraordinary potential of AI systems with a striking empirical pattern: as AI systems scale, thei

The small open weight models are scarier in AI development

model-releasesr-localllama

Imagine if your everyday laptop could run an AI model smart enough to take care of 90% of your work—totally private, lightning fast, and completely free of monthly fees. That is the exact tipping poin

Local Ai

The Spectral Neuron

arXiv:2608.08003v1 Announce Type: cross Abstract: As machine learned models increase in complexity and expressive power, features of simpler models, such as interpretability and control over the shape

local-aiarxiv-cs-lg

The Theory of Strategic Evolution: Games with Endogenous Players and the Seven Laws of Strategic Replicators

arXiv:2512.07901v4 Announce Type: replace-cross Abstract: Von Neumann founded both game theory and the theory of self-reproducing automata, but the two programs never merged. Rational players do not c

The Transparency Trap: How AI Disclaimers Create Overconfidence in High-Stakes Decisions

arXiv:2608.07493v1 Announce Type: cross Abstract: Current AI disclaimers often fail to function as intended due to warning habituation and a transparency paradox. As AI-generated information becomes p

safetyarxiv-cs-cl

The Voiceprint Fallacy: Why Voices Are Not Unique Biometric Imprints

arXiv:2608.07980v1 Announce Type: cross Abstract: In recent years, the term voiceprint has regained attention, particularly in technological applications and policy-making contexts, often carrying the

safetyarxiv-cs-cl

The Watermark Shortcut: How Provenance Marking Sabotages Audio Deepfake Detection

arXiv:2606.23335v2 Announce Type: replace-cross Abstract: Provenance watermarking is increasingly treated as a safeguard for synthetic speech, whether built directly into speech-generation models such

💡The world needs an open-source platform, and that’s exactly what we’re building to give our customers more choice and the flexibility to c…

model-releasesmistral-ai--x

💡The world needs an open-source platform, and that’s exactly what we’re building to give our customers more choice and the flexibility to choose the right model for the right task. As part of this, we

Theory-Guided Deception Detection: A RAG-Based Artificial Intelligence Exploration

arXiv:2608.08881v1 Announce Type: new Abstract: The current work developed seven Retrieval-Augmented Generation (RAG) models based on leading deception theories and compared how deception judgments we

There are no lossless transformations of natural-language text

There are no lossless transformations of natural-language text Sophie Alpert shares her 'internal policy on acceptable use of AI writing by engineers'. It's a short read (supporting its own recommenda

safetysimon-willison

Think Deep, Speak Once: Relit, A Recursive Latent Implicit Transformer Framework

arXiv:2608.08113v1 Announce Type: new Abstract: Chain-of-Thought (CoT) prompting has become the dominant paradigm for eliciting reasoning in Large Language Models (LLMs), yet it creates substantial co

Tutorials

Thinking Hard, Not Smart: Reasoning Models Fail to Ration Test-Time Compute Across Questions

arXiv:2608.07968v1 Announce Type: cross Abstract: Reasoning language models increasingly use test-time compute to improve performance, but existing evaluations typically study this compute one questio

tutorialsarxiv-cs-ai

Thinking Is Not Telling: Information Disclosure in User-Service LLM Agents

arXiv:2602.07796v2 Announce Type: replace Abstract: User-engaged LLM agents increasingly operate in service scenarios where task success depends on coordination between the agent, the user, and a stat

agentsarxiv-cs-cl

Thinking vs. NoThinking: Towards Interpreting Reasoning Mechanisms of Large Language Models via Sparse Autoencoders

arXiv:2608.08168v1 Announce Type: new Abstract: While Large Language Models (LLMs) employing Chain-of-Thought (CoT) exhibit superior reasoning capabilities, the neural mechanisms distinguishing this e

Thinking With Tools, Not With Pixels: Tool Calls as Text Scaffolds for Visual Reasoning

arXiv:2608.09682v1 Announce Type: new Abstract: Tool-augmented vision-language models increasingly 'think with images': they call crop, zoom, or code tools and reason over the returned pixels. However

agentsarxiv-cs-cv

This is part of working with the EU AI Act, other labs are adding similar watermarking. It’s hard to identify AI-generated text, and this gi…

This is part of working with the EU AI Act, other labs are adding similar watermarking. It’s hard to identify AI-generated text, and this gives people better tools to do that. We’ll also be a shipping

model-releasesthariq--x

Thought-Level Beam Search for Reasoning

arXiv:2608.08020v1 Announce Type: new Abstract: Test-time compute scaling is a primary driver of performance in large reasoning models (LRMs), but extreme inefficiency bounds current approaches, shift

Applications

Three Generations of Healthcare IT: From the Digital Record to the Computable Care Process

arXiv:2608.08806v1 Announce Type: new Abstract: Objective. Healthcare IT is usually organized by the technologies it adopts. We instead organize it by the unit of information a system makes computable

applicationsarxiv-cs-ai

Three Necessary Principles for Self-Supervised Visual Representation Learning

arXiv:2608.08309v1 Announce Type: cross Abstract: We argue that learning visual representations without labels requires a training signal jointly complete across three non-overlapping objectives: sema

Tied Trit-Planes: Constraining PTQTP to a Uniform Nine-Level Quantizer, with a Persistent Folded Format for Disk-Streamed Mixture-of-Experts Serving

arXiv:2608.08910v1 Announce Type: new Abstract: PTQTP decomposes LLM weight matrices into two ternary (trit) planes with two free per-group scales. Tying the scales to a fixed ratio of three collapses

Time Present and Time Past: Benchmarking Large Language Models on Temporally Evolving Document Understanding

arXiv:2608.08512v1 Announce Type: new Abstract: Evolving documents, such as laws, tax codes, and software documentation, are amended, replaced, and sometimes reverted over time, so a question has diff

Tutorials

TLDChoiceNet: Quantitatively Choosing a Transfer Learning Dataset

arXiv:2608.09091v1 Announce Type: cross Abstract: Transfer learning is particularly useful in settings with limited training data, and within image classification it is common to transfer learn upon m

tutorialsarxiv-cs-ai

To Memorize or to Retrieve: Scaling the Interaction Between Pretraining and Retrieval

arXiv:2604.00715v2 Announce Type: replace-cross Abstract: Retrieval-augmented generation (RAG) improves language model (LM) performance by providing relevant context at test time for knowledge-intensi

Today it was apparently my turn

I’ve been using ChatGPT for about two months now after giving up on Claude and Gemini and I became a true zealot. I’m now using Pro, and despite having the personality, set to default, never had any p

model-releasesr-chatgpt

Hardware

Together AI is teaming up with @IBM and @nvidia to bring enterprise-grade AI inference to IBM Cloud. A dedicated NVIDIA B300 cluster. Spectr…

Together AI is teaming up with @IBM and @nvidia to bring enterprise-grade AI inference to IBM Cloud. A dedicated NVIDIA B300 cluster. Spectrum-X networking. First of its kind on IBM Cloud, powered by

hardwaretogether-ai--x

Tokenisation over Bounded Alphabets is Hard

arXiv:2511.15709v2 Announce Type: replace Abstract: Recent works have shown that tokenisation is NP-complete. However, these works assume tokenisation is applied to inputs with unboundedly large alpha

researcharxiv-cs-cl

Tokenizer Generator Coupling in Medical Image Generation

arXiv:2608.07713v1 Announce Type: new Abstract: Latent medical image generators usually treat the tokenizer as fixed preprocessing. We test whether this separation is valid in a controlled ChestMNIST

researcharxiv-cs-cv

TokenPrint: A Calibrated Token-Space Fingerprint for Language-Model Provenance

arXiv:2608.08139v1 Announce Type: new Abstract: Establishing the provenance of a language model---including its base checkpoint and possible overlap in training distributions---is a governance challen