Search: “models”

Gradient Heterogeneity Complements Hessian Heterogeneity in Transformer Optimization

arXiv:2502.00213v5 Announce Type: replace-cross Abstract: Transformers are difficult to optimize with stochastic gradient descent (SGD) and largely rely on adaptive optimizers such as Adam. Despite ex

Model Releases

GxP-Agent: Process-DAG Topology for Reliable Clinical Trial Programming with LLM Agents

DGX agent

arXiv:2608.16890v1 Announce Type: new Abstract: Clinical trial programming -- transforming study protocols into analysis-ready datasets under CDISC standards -- is a bottleneck in regulatory submissio

model-releasesarxiv-cs-ai

19 Aug 2026

HeteRo-Select: Informativeness as the Participation Driver in Heterogeneous Federated Learning

arXiv:2508.06692v3 Announce Type: replace Abstract: Federated learning systems typically allocate gradient compression by link speed. This is sensible when bandwidth and data informativeness align. Ho

HyPE-GT: where Graph Transformers meet Hyperbolic Positional Encodings

arXiv:2312.06576v2 Announce Type: replace Abstract: Graph Transformers (GTs) facilitate the comprehension of complex relationships on graph-structured data by leveraging self-attention of the possible

.@Kimi_Moonshot Kimi K3 is starting to roll out on Ollama's cloud subscriptions. We are working on improving Ollama's cloud to be much more …

model-releaseskimi-moonshot--x

.@Kimi_Moonshot Kimi K3 is starting to roll out on Ollama's cloud subscriptions. We are working on improving Ollama's cloud to be much more transparent on the pricing to show the best performance / $.

Leveraging Association Context Retrieval in Knowledge Edit- ing to Build White-Box Attacks on LLMs

arXiv:2608.17836v1 Announce Type: new Abstract: As large language models (LLMs) are granted increasing autonomy, it is essential to investigate methods that can induce unsafe behavior. We propose a no

researcharxiv-cs-lg

LLMs for Medical Consultation Are Evaluated Too Late: The Preformulation Gap

arXiv:2608.17330v1 Announce Type: new Abstract: Large language models for medical consultation are often evaluated after a clinical problem has already been made clear, although real consultations may

LSem2Vec: A Simple yet Effective Two-Stage Approach for Source Code Embedding

arXiv:2409.14644v4 Announce Type: replace-cross Abstract: The advent of large language models (LLMs) has significantly advanced artificial intelligence in software engineering, with source code embedd

Margin-Regularized Structured Semantic Alignment for Brain-Language Correspondence

arXiv:2608.16975v1 Announce Type: new Abstract: With the rapid advancement of large language models, brain-language decoding has achieved remarkable progress. However, it remains unclear whether decod

safetyarxiv-cs-cl

Maximum Tsallis Entropy Distributions for Robust and Efficient Sparse Learning from Correlated Data

arXiv:2608.17244v1 Announce Type: cross Abstract: This paper addresses the limitations of Gaussian distribution assumptions in statistical sparse learning, particularly in modeling correlated and hete

MoRA: Mobility as the Backbone for Geospatial Representation Learning at Scale

arXiv:2506.01297v5 Announce Type: replace Abstract: Representation learning of geospatial locations remains a core challenge in achieving general geospatial intelligence, with increasingly diverging p

Industry

More open weights frontier for generative media, more...

industrycristobal-valenzuela--x

More open weights frontier for generative media, more... impossible to not think of @c_valenzuelab's excellent blog 'we are solving graphics backwards' in it, he argues that in traditional computer gr

Industry

OpenAI falls further behind Anthropic, with disappointing revenue growth and mounting losses

OpenAI Group PBC is falling further behind its rival Anthropic PBC, if its latest financials are any indication. The artificial intelligence model maker told investors that its revenue rose 18% on a s

industrysiliconangle

Plug-and-Play Traffic Element Awareness for End-to-End Autonomous Driving

model-releasesarxiv-cs-cv

arXiv:2608.18035v1 Announce Type: new Abstract: Traffic elements such as traffic lights and road signs play a fundamental role in human driving decisions and should naturally influence end-to-end driv

Policy Optimization and Statistical Inference for Online Contextual Matrix Games

arXiv:2608.17173v1 Announce Type: cross Abstract: Online decision making often requires navigating a landscape shaped by both dynamic contexts and strategic interactions. In competitive pricing, for e

Preference Is Not Intervention: The Structure and Stability Boundaries of Reader-Specific Evidence Utility

arXiv:2608.17781v1 Announce Type: new Abstract: ML systems increasingly condition decisions on downstream model identity, but this is useful only if model-specific differences form reusable structure

researcharxiv-cs-cl

SFMformer: A Spatial-Frequency Modulation Transformer for Lightweight Image Super-Resolution

model-releasesarxiv-cs-cv

arXiv:2608.17966v1 Announce Type: new Abstract: Sparse attention mechanisms, which score all token pairs but propagate only the strongest, now underpin the most efficient Transformers for lightweight

Agents

SkillEffect: Checked Lowering for Memory-Bounded Agent Tools

arXiv:2608.17007v1 Announce Type: new Abstract: Agent Skills can specify procedural and resource obligations for tool use, and language models instantiate them as concrete programs. However, when mode

agentsarxiv-cs-ai

Speak in Context: Multilingual ASR with Speech Context Alignment via Contrastive Learning

arXiv:2603.06505v2 Announce Type: replace Abstract: Automatic speech recognition (ASR) has benefited from advances in pretrained speech and language models, yet most systems remain constrained to mono

safetyarxiv-cs-cl

StagedWorkspace: A Versioned Workspace for Knowledge-Work Agents

arXiv:2608.18050v1 Announce Type: new Abstract: AI agents increasingly perform knowledge work (i.e., produce and modify persistent digital artifacts such as code repositories, documents, spreadsheets,

Temporal Leakage in Financial News NLP: A Multi-Architecture Audit with a Regime-Specific M&A Signal

model-releasesarxiv-cs-cl

arXiv:2608.17223v1 Announce Type: new Abstract: Financial-news direction prediction has become a popular NLP benchmark, yet reported gains depend critically on whether the train-test split is chronolo

The 10th AI City Challenge

arXiv:2608.17044v1 Announce Type: cross Abstract: The 10th AI City Challenge, held with ECCV 2026, marks a decade of community benchmarking for intelligent transportation, smart cities, and physical A

The Curious Case of Exploding DecPOMDPs: Containing the Fire through Policy Counting

arXiv:2608.17749v1 Announce Type: new Abstract: Decentralised partially observable Markov decision processes (DecPOMDPs) provide a general framework for modelling multi-agent decision making under unc

safetyarxiv-cs-ai

The Problem Is the Problem: Towards Scalable Mathematical Discovery

arXiv:2608.16977v1 Announce Type: new Abstract: AI systems are increasingly capable of contributing to mathematical research. In research practice, frontier-model reasoning is a limited resource, and

VentureBeat names Rob Strechay as its first Lead Analyst, expanding its enterprise AI research push

model-releasesventurebeat-ai

Rob Strechay, until recently managing director and principal analyst at theCUBE Research, has joined VentureBeat as our first Lead Analyst and a founding analyst of VentureBeat Research. His arrival i

What’s the best Ollama Cloud alternative right now?

My current setup is basically OhMyPi+ OpenCode (mostly OpenCode Go: DeepSeek, Flash, V4, etc.) + Ollama Cloud for stuff like Kimi and GLM. But honestly, I feel like Ollama Cloud has gotten noticeably

model-releasesr-ollama

An Adaptive Gradient Clipping and Noise Injection Mechanism for Differentially Private Federated Learning

arXiv:2608.15153v1 Announce Type: cross Abstract: Differentially private federated learning must balance privacy protection against model accuracy and training efficiency. Static gradient clipping app

researcharxiv-cs-lg

Beat the Counter First: A Baseline for Temporal-Graph Anomaly Detectors

arXiv:2608.15965v1 Announce Type: new Abstract: Progress in streaming, edge-level graph anomaly detection (GAD) has been marked by increasingly elaborate architectures, from count-min-sketch chi squar

BERTopic-Virality Prioritisation: A Scalable Framework for Thematic and Comparative Analysis of COVID-19 and Monkeypox Misinformation on Twitter

model-releasesarxiv-cs-cl

arXiv:2608.15691v1 Announce Type: new Abstract: Health misinformation circulating during pandemics can gain traction rapidly, creating harmful narratives that compete with public health guidance. Most

Tutorials

Beyond Visual CoT: Internalized Visual Thinking for Proactive Video Reasoning

arXiv:2608.15869v1 Announce Type: cross Abstract: Multimodal large language models increasingly use visual chain-of-thought (Visual CoT) to reason about spatial, temporal, and embodied environments. B

tutorialsarxiv-cs-ai

Bridging the Gap between Labeled and Unlabeled Data via Unified Flow with Feature Memory Bank

arXiv:2608.16681v1 Announce Type: cross Abstract: Although semi-supervised semantic segmentation (ext{S}^4) utilizes abundant unlabeled data to reduce manual labeling burdens, independent training of

Local Ai

Catching Hallucinated Citations in Video-LLM Question Answering: A Self-Verification Pipeline and Verifier Ablation Study

arXiv:2608.15574v1 Announce Type: cross Abstract: Video question answering systems built on vision-language models often produce timestamped claims with high confidence even when unsupported by the ci

local-aiarxiv-cs-ai

CEDAR-GRPO: Process-Aware Reinforcement Learning for General Abductive Reasoning in LLMs

arXiv:2608.14791v1 Announce Type: new Abstract: Abductive reasoning, often characterized as inference to the best explanation, is central to explanation under uncertainty, from everyday sense-making a

Chronocooked: A Benchmark for Implicit Interval Timing in Reinforcement Learning Agents

arXiv:2608.16666v1 Announce Type: new Abstract: This paper presents Chronocooked, a reinforcement learning (RL) benchmark suite for studying implicit interval timing in RL agents. Inspired by Overcook

CLARA: Clip-Level Multimodal Alignment with VLM-Derived Rationales for Hateful Video Detection

model-releasesarxiv-cs-cv

arXiv:2608.15905v1 Announce Type: new Abstract: Hateful video detection has become increasingly important with the rapid growth of video-centric social media platforms, given the serious risks that ha

Clause Encounters of the Third Kind: Can LLMs Replace Language Teachers?

arXiv:2608.16286v1 Announce Type: new Abstract: While various organizations now actively encourage LLM use in classrooms, we still lack rigorous, systematic evaluations of how well these models actual

researcharxiv-cs-cl

Crystal-structure design by agentic AI in a language of motifs

arXiv:2608.15900v1 Announce Type: cross Abstract: Data-driven materials discovery interpolates more reliably than it extrapolates and seldom reaches new structure types. We present MatEvolve, an agent

Deploying Frontier Agentic Technology in MOOSEnger, a Multiphysics-Capable AI Assistant

arXiv:2608.15881v1 Announce Type: new Abstract: The Multiphysics Object-Oriented Simulation Environment (MOOSE) is an open-source finite-element framework for building multiphysics simulation applicat

Developing an Offshore Machine Learning Surface Layer Scheme

arXiv:2608.14935v1 Announce Type: cross Abstract: Turbulent fluxes between the surface and the atmosphere are typically parameterized using empirically fit relationships. Here we test machine learning

researcharxiv-cs-lg

Agents

Diagnosing and Mitigating Perception-Decision Misalignment in Omni-LLMs via Modality Subspace Activation

arXiv:2608.14655v1 Announce Type: cross Abstract: Omni-Large Language Models (Omni-LLMs) power complex multi-modal reasoning in applications like World Action Models and autonomous agents. However, th

agentsarxiv-cs-cv

DUET: Dual-Teacher On-Policy Distillation via Same-Weight Disagreement for Prohibition Compliance

model-releasesarxiv-cs-cl

arXiv:2608.14644v1 Announce Type: cross Abstract: Real-world LLM deployments increasingly rely on runtime-injected prohibitions--enterprise policies, PII redlines, tool boundaries--that vary per reque

DumpsterCluster: From Dumpster Diving to Serving LLaMA-70B on $60 GPUs

arXiv:2608.14614v1 Announce Type: cross Abstract: As AI datacenters retire functional GPUs, vast quantities of still capable accelerators enter secondary markets. This paper investigates whether these

DYNASHIELD: A Black-Box Moving Target Defense for LLMs via Dynamic Decoding Customization

arXiv:2412.07672v2 Announce Type: replace-cross Abstract: Large language models (LLMs) remain vulnerable to jailbreak attacks in which adversarial prompts induce harmful outputs. Existing defenses oft

safetyarxiv-cs-cl

Local Ai

Encoding of musical structures in hidden units of restricted Boltzmann machines

arXiv:2509.04899v4 Announce Type: replace-cross Abstract: Restricted Boltzmann machines (RBMs) are energy-based models originating from statistical physics, in which hidden units mediate the probabili

local-aiarxiv-cs-lg

Tutorials

Feasible and Novel Synthetic Population Generation with Tabular and Sequential Travel Attributes

arXiv:2608.15867v1 Announce Type: cross Abstract: Synthetic populations are critical inputs for activity-based travel demand models, yet generating realistic populations from limited survey data remai

tutorialsarxiv-cs-ai

Local Ai

FrescoDiffusion: 4K Image-to-Video with Prior-Regularized Tiled Diffusion

arXiv:2603.17555v2 Announce Type: replace-cross Abstract: Diffusion-based image-to-video (I2V) models are increasingly effective, yet they struggle to scale to ultra-high-resolution inputs (e.g., 4K).

local-aiarxiv-cs-ai

Generalized Linear Bandits with Memory

arXiv:2608.15848v1 Announce Type: cross Abstract: We study generalized linear bandits with memory, an endogenous non-stationary setting in which rewards depend on past actions through a finite memory

HalluTracer: Hallucination Detection via Depth-Averaging Truth Signals

arXiv:2608.16353v1 Announce Type: cross Abstract: Even well-aligned large language models confidently generate factually incorrect text, making hallucination a persistent reliability risk in high-stak