Search: “model-releases”

SwissCrop25: A National Multi-Year Benchmark for Operational Crop Mapping

arXiv:2608.09497v1 Announce Type: new Abstract: Operational crop mapping requires models that generalise across years, resolve fine-grained crop taxonomies, and distinguish cropland from surrounding l

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Tabular Numeric Stretch Transformation

DGX agent

arXiv:2608.09162v1 Announce Type: cross Abstract: Tabular data presents unique challenges for deep learning due to its heterogeneous nature, where numeric features exhibit diverse distributions, scale

model-releasesarxiv-cs-ai

11 Aug 2026

take away the symbolic part of this and it just would not have worked. Claude on Riemann is yet another victory for hybrid, neurosymbolic AI…

model-releasesgary-marcus--x

On August 11 2026, Gary Marcus commented that if the symbolic components were removed from Claude’s Riemann implementation it would fail to work, highlighting a concrete win for hybrid neurosymbolic A

Task-Oriented Formation Decision via Reinforcement Learning: Herding an Attacking Swarm

model-releasesarxiv-cs-ro

arXiv:2608.09258v1 Announce Type: new Abstract: Multi-robot systems can accomplish tasks that are difficult for a single robot by organizing into task-specific formations. Different from existing stud

Task-to-Model Optimization for Enterprise LLM Coding Assistants: A Data-Driven Framework for Cost-Optimal Routing

arXiv:2608.08528v1 Announce Type: new Abstract: Enterprise AI coding assistants incur substantial inference spend, and naive token-cost minimization often fails to reduce end-to-end cost once retries,

TCS-BENCH: Benchmarking State-of-the-Art Generative AI Theoretical Computer Science Research Ability

arXiv:2608.09538v1 Announce Type: cross Abstract: We introduce TCS-Bench, a benchmark for evaluating Large Language Models (LLMs) on research-level Theoretical Computer Science (TCS) proof generation.

TelemetrySuffBench: Is Agent Telemetry Sufficient for Failure-Origin Diagnosis?

arXiv:2608.07899v1 Announce Type: new Abstract: Agent systems increasingly expose execution traces, yet telemetry that reveals a failure may still be inadequate for identifying where that failure orig

TEMPER: Tensorized Efficient Manifold-constrained Parameterization for Expressive Residual Routing

arXiv:2608.07851v1 Announce Type: cross Abstract: Residual connections rely on a static residual pathway, and are essential for training deep neural networks. Hyper-connections (HC) increase the expre

Temporal Generalization in fNIRS-Based Autism Classification: A Cross-Time-Window Transfer Benchmark

arXiv:2608.07567v1 Announce Type: cross Abstract: Functional near-infrared spectroscopy (fNIRS) is a promising modality for autism spectrum disorder (ASD) classification, yet existing approaches assum

Temporal Misgrounding in Legal RAG: A Versioned-Corpus Benchmark for French Tax Law

arXiv:2608.09393v1 Announce Type: cross Abstract: We identify and quantify temporal misgrounding: the systematic retrieval and citation of the currently in-force version of a legal article when the ap

Test-time Generalization for Physics through Neural Operator Splitting

arXiv:2602.00884v2 Announce Type: replace Abstract: Neural operators have shown promise in learning solution maps of partial differential equations (PDEs), but they often struggle to generalize when t

Test-Time Prototype Adaptation for Open-Vocabulary Semantic Segmentation

arXiv:2608.08290v1 Announce Type: new Abstract: Open-vocabulary semantic segmentation (OVSS) repurposes a pretrained CLIP encoder for dense prediction without additional labeled supervision. Existing

Tested in Coding: BF16 Muse Glimmer vs BF16 Qwen3.6 27B

model-releasesr-localllama

I'm guessing that many people have been waiting for this comparison. For clarity, both models are running at full FP16 KV-cache. Due to VRAM limitations, Muse Glimmer is running full 262,144 context,

Tevatron-Elastic: A Unified Abstraction for Training Elastic Retrievers and Rerankers

arXiv:2608.08809v1 Announce Type: new Abstract: A single model scale challenges the flexibility of a production retrieval system: some settings need it faster, others need a smaller index, and the rig

TeXFix-Bench: An Empirically Grounded Multi-Format Benchmark for LLM-Based Document Source Repair

arXiv:2608.07617v1 Announce Type: new Abstract: Scientific and technical writing depends on markup sources that must compile: LaTeX, Typst, and Markdown pipelines fail on missing delimiters, mismatche

⚙️That is the framework Mistral is building toward: one in which enterprises, governments, and startups can use the best AI available, shape…

model-releasesmistral-ai--x

⚙️That is the framework Mistral is building toward: one in which enterprises, governments, and startups can use the best AI available, shape it around their own knowledge, and retain the value it crea

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 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

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 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 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 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 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 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

💡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

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

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

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

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

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

TomaMMU: A Comprehensive Multimodal Understanding Benchmark for Tomato Leaf Diseases

arXiv:2608.08727v1 Announce Type: cross Abstract: To address this gap, we introduce TomaMMU, a large-scale Tomato leaf disease MultiModal Understanding dataset, alongside TomaBench, a benchmark for ev

TongGuOCR: A Layout-Aware and Token-Augmented OCR Framework for Chinese Historical Documents

arXiv:2608.07917v1 Announce Type: new Abstract: Chinese historical documents preserve valuable cultural heritage, but many collections remain accessible only as scanned page images, preventing full-te

Topology-Aware Global-Local Mamba Networks for Palm Vein Biometrics

arXiv:2608.08951v1 Announce Type: new Abstract: Palm-vein recognition is a fine-grained biometric task in which both local vascular texture and the global layout of the vessel tree carry discriminativ

Toward Mask Annotation-Free Surgical Instrument Segmentation from Endoscopic Images Using Text-Prompted Segment Anything Model 3 (SAM3)

arXiv:2608.08844v1 Announce Type: new Abstract: Surgical instrument segmentation is a fundamental task for computer-assisted interventions, yet most existing methods rely on pixel-level annotations or

Toward Metacognitive One-Shot Indirect Prompt Injection: Strategy Abstraction Via Outcome-Conditioned Reflection

arXiv:2608.08795v1 Announce Type: cross Abstract: Tool-using large language model (LLM) agents are vulnerable to indirect prompt injection (IPI), in which malicious instructions embedded in external o

Towards an LLM-based method for quantifying the sexual content in song lyrics

arXiv:2608.08885v1 Announce Type: cross Abstract: Reggaeton is one of the most widely consumed music genres in the world, and its lyrics are commonly regarded as highly sexualized. This claim rests mo

Towards Expert-level Medical AI for Real-time Video Consultations

arXiv:2608.09861v1 Announce Type: new Abstract: Audio-visual interaction is the standard for patient-physician consultations, enabling natural communication and effective assessment of illness through

Towards Researcher Agents for Knowledge-Graph Question Answering

arXiv:2608.07700v1 Announce Type: new Abstract: Translating a natural-language question into a SPARQL query that can be executed against a large knowledge graph requires resolving lexical ambiguity, g

Toy project: a chat title model that fits in 5 MiB of ram

model-releasesr-localllama

Not even sure if I'm allowed to post this, what with the 'completely/primarily LLM generated copy' rule (the post itself is fine, but the repo/model I'm sharing definitely is, whoops) and the whole li

TRACE: TRajectory Attribution for Automated Context Engineering

arXiv:2608.09153v1 Announce Type: new Abstract: Production AI agents fail when their context sources -- system prompts, knowledge bases, tool descriptions, and procedural skills -- contain errors or g

Tracking the Best Strategy in an Extensive-Form Game

arXiv:2608.09501v1 Announce Type: new Abstract: We consider the extensive-form bandit problem where on each trial the learner plays an extensive-form game against an oblivious adversary. We focus on t

Trajectory Design and Budgeted Querying for Digital Twin Calibration

arXiv:2608.08631v1 Announce Type: new Abstract: Digital-twin calibration requires interaction data that is expensive to collect. We study two acquisition decisions: which trajectories to generate, and