Search: “models”

Reinforcing the Generation Order of Multimodal Masked Diffusion Models

arXiv:2607.08056v1 Announce Type: cross Abstract: Diffusion Language Models (DLMs) have recently achieved substantial progress in natural language generation tasks. Recent research demonstrates that a

10 Jul 2026

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Research

Stop Guessing When to Stop Testing: Efficient Model Evaluation with Just Enough Data

DGX agent

arXiv:2607.08522v1 Announce Type: new Abstract: The inherent rigidity of fixed-size benchmarks makes them an inefficient tool for model evaluation. Diverse evaluation objectives, including model ranki

researcharxiv-cs-lg

10 Jul 2026

WCog-VLA: A Dual-Level World-Cognitive Vision-Language-Action Model for End-to-End Autonomous Driving

arXiv:2607.08375v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have advanced end-to-end autonomous driving. However, existing methods either lack comprehensive world cognition o

10 Jul 2026

Local Ai

Distributed Sparse Interventions in Language Models

arXiv:2607.07128v1 Announce Type: new Abstract: Language models perform a wide range of tasks at varying levels of abstraction with the capacity to flexibly infer tasks from context, execute multiple

local-aiarxiv-cs-lg

Enhancing deep learning models for time series classification via knowledge distillation

arXiv:2607.06796v1 Announce Type: cross Abstract: Deep learning has achieved remarkable success in various domains including time series analysis, computer vision and natural language processing. Howe

Grounding Spatial Relations in a Compact World Model: Instruction Leakage and a Goal-Free Dynamics Fix

arXiv:2607.06925v1 Announce Type: new Abstract: Compact world models that condition on a language goal promise to ground relations such as ``put the red block left of the blue block'' using a sparse s

Is Meta AI back? Haven't seen Mark post in three years here. Plus, the model is available via API. Not to mention the courage to announce it…

Is Meta AI back? Haven't seen Mark post in three years here. Plus, the model is available via API. Not to mention the courage to announce it the same week as the long-awaited GPT-5.6. Great timing if

model-releasesdair-ai--x

Large Behavior Model: A Promptable Digital Twin of the Retail Customer

arXiv:2607.06993v1 Announce Type: new Abstract: Customer behavior modeling underpins recommendation, marketing, and decision support, yet existing approaches either optimize predictive accuracy withou

researcharxiv-cs-ai

LiveOIBench: Can Large Language Models Outperform Human Contestants in Informatics Olympiads?

arXiv:2510.09595v3 Announce Type: replace Abstract: Competitive programming problems are increasingly used to evaluate the coding capabilities of large language models (LLMs) due to their complexity a

LLM-powered reasoning in agent-based modeling

arXiv:2607.06757v1 Announce Type: new Abstract: Agent-based modeling (ABM) has the capability to model millions of individuals and their interactions, which is useful for policy making. However, ABMs

safetyarxiv-cs-ai

Meta launches flagship Muse Spark 1.1 model with multi-agent upgrades

model-releasessiliconangle

Meta Platforms Inc. today launched a new flagship large language model optimized to power multi-agent automation workflows. Muse Spark 1.1 is available in the company’s Meta AI chatbot service and via

Refine Thought: A Test-Time Inference Method for Embedding Model Reasoning

arXiv:2511.13726v2 Announce Type: replace-cross Abstract: We propose RT (Refine Thought), a method that can enhance the semantic reasoning ability of text embedding models. The method obtains the fina

What's on My Network? Using Large Language Models to Identify Real-World IoT Devices at Scale

model-releasesarxiv-cs-lg

arXiv:2510.13817v2 Announce Type: replace Abstract: The growth of IoT devices in shared environments has outpaced our ability to identify them, posing urgent risks to privacy, safety, and accountabili

Agents

Driving the Wrong Way: Leveraging Interpretability in End2End Autonomous Driving Models

arXiv:2607.06328v1 Announce Type: new Abstract: The increasing adoption of end-to-end learning for autonomous driving introduces increased model complexity and opacity, raising the risk of learning un

agentsarxiv-cs-ai

Imagined Rollouts are Kinematic, Not Dynamic: A Diagnosis of Long-Horizon World-Model Failure

model-releasesarxiv-cs-ro

arXiv:2607.05966v1 Announce Type: new Abstract: Long-horizon failure in world models is conventionally attributed to compounding error, a generic framing that does not distinguish what kind of error c

Meta launches image generation model with coding, search capabilities

model-releasessiliconangle

Meta Platforms Inc. today debuted an image generation model that can write code and search the web. Muse Image is the second algorithm released to date by Meta Superintelligence Labs, the company’s ar

Mitigating Factual Hallucination in Large Reasoning Models via Mixed-Mode Advantage Regularization

arXiv:2607.05861v1 Announce Type: new Abstract: Large reasoning models (LRMs) improve language model capabilities by generating explicit thinking traces before final answers. In factuality-oriented qu

researcharxiv-cs-cl

Agents

Unicode TAG-Block Concealment of Tool-Metadata Payloads in the Model Context Protocol: An Approval-View Fidelity Gap Across Three Independent Server Implementations

arXiv:2607.05744v1 Announce Type: cross Abstract: The Model Context Protocol (MCP) is the dominant way coding agents discover and invoke external tools. A server advertises each tool through a tools/l

agentsarxiv-cs-ai

We've usually stayed away from model comparisons but 5.6 vs Fable is a unique situation We've never had a case where the team is so complete…

model-releasessam-altman--x

We've usually stayed away from model comparisons but 5.6 vs Fable is a unique situation We've never had a case where the team is so completely convinced on which one is better Here's the timeline of o

Curriculum-Guided Layer Scaling for Language Model Pretraining

model-releasesarxiv-cs-cl

arXiv:2506.11389v4 Announce Type: replace Abstract: As the cost of pretraining large language models grows, there is continued interest in strategies to improve learning efficiency during this core tr

Efficient Decentralized Multi-task Dataset Valuation via Model Merging

arXiv:2607.03346v1 Announce Type: cross Abstract: Accurate and efficient dataset valuation is essential for enabling fair and transparent data marketplaces, especially when multiple contributors provi

Fair-GPTQ: Bias-Aware Quantization for Large Language Models

arXiv:2509.15206v3 Announce Type: replace Abstract: The high memory demands of generative language models have drawn attention to quantization, which reduces memory usage by mapping model weights to l

safetyarxiv-cs-cl

LLM-Assisted Semantic Alignment and Integration in Collaborative Model-Based Systems Engineering Using SysML v2

arXiv:2508.16181v2 Announce Type: replace-cross Abstract: Cross-organizational collaboration in Model-Based Systems Engineering (MBSE) faces many challenges in achieving semantic alignment across inde

safetyarxiv-cs-ai

Local Ai

Object-Centric Environment Modeling for Agentic Tasks

arXiv:2607.02846v1 Announce Type: new Abstract: Large language model (LLM) agents can improve through accumulated experience, but free-form textual memories become difficult to maintain, validate, and

local-aiarxiv-cs-ai

Hardware

OctoPipe: Reducing Pipeline Bubbles for Heterogeneous Models via Co-Optimizing Partitioning, Placement, and Scheduling

arXiv:2509.23722v2 Announce Type: replace-cross Abstract: Pipeline parallelism is widely used to train large language models (LLMs). However, increasing heterogeneity in model architectures exacerbate

hardwarearxiv-cs-ai

Overloading Large Vision-Language Models for Jailbreaking

arXiv:2607.02961v1 Announce Type: new Abstract: Large Vision-Language Models (LVLMs) exhibit remarkable vision-language capabilities and are increasingly deployed in real-world applications such as pe

safetyarxiv-cs-cv

Poisson-Gamma Modeling of Inter-Relational Dependencies in Dynamic Knowledge Graphs

model-releasesarxiv-cs-lg

arXiv:2607.02872v1 Announce Type: new Abstract: Dynamic knowledge graphs are ubiquitous in today's AI applications, as we represent molecular structures, social relationships, and language information

RayTun3R: Online Camera Adaptation in 3D Foundation Models

model-releasesarxiv-cs-cv

arXiv:2607.02711v1 Announce Type: new Abstract: Recent 3D foundation models, such as DUSt3R, MASt3R, VGGT, pi^3, and Depth Anything 3, provide strong feed-forward depth and pose estimates on pinhole i

Short-Horizon Position Accuracy of Single-Track Models: Implications for Motion Planning of Autonomous Vehicles

arXiv:2606.14216v2 Announce Type: replace Abstract: Accurate and computationally efficient vehicle models are essential for motion planning of autonomous vehicles, where positional accuracy directly a

safetyarxiv-cs-ro

SIMPLER: Efficient Foundation Model Adaptation via Similarity-Guided Layer Pruning for Earth Observation

model-releasesarxiv-cs-cv

arXiv:2603.19873v2 Announce Type: replace Abstract: Fine-tuning foundation models for Earth Observation is computationally expensive, with high training time and memory demands for both training and d

Unbiased Alignment for Large Language Models with Noisy Preferences

arXiv:2607.03248v1 Announce Type: cross Abstract: The alignment of large language models with human preferences is commonly achieved through Reinforcement Learning from Human Feedback or Direct Prefer

Walrus: A Cross-Domain Foundation Model for Continuum Dynamics

arXiv:2511.15684v2 Announce Type: replace-cross Abstract: Foundation models have transformed machine learning for language and vision, but achieving comparable impact in physical simulation remains a

When Does Small Data Work? Accuracy and Efficiency Trade-offs Between Tabular Foundation Models and Conventional Methods for Crowd-State Classification at Hajj and Umrah

arXiv:2607.04013v1 Announce Type: cross Abstract: Learning from few labeled examples is a central challenge in tabular machine learning, and it becomes the binding constraint in domains where labeling

researcharxiv-cs-ai

Local Ai

Most models run on whatever inference engine they ship with. That's rarely the fastest option. We built our own, AGI-RUN. On a phone it beat…

Most models run on whatever inference engine they ship with. That's rarely the fastest option. We built our own, AGI-RUN. On a phone it beat every model's own native engine, and ran up to 9.9x faster

local-aidiv-garg--x

6 Jul 2026

AnyGroundBench: A Specialized-Domain Benchmark for Video Grounding in Vision-Language Models

arXiv:2607.02269v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) have demonstrated immense promise in Spatio-Temporal Video Grounding (STVG). However, current evaluation protocols are l

Bayesian Sparse Low-Rank Adaptation for Large Language Model Uncertainty Estimation

model-releasesarxiv-cs-cl

arXiv:2607.02182v1 Announce Type: cross Abstract: Large language models (LLMs) exhibit remarkable reasoning capabilities, but their task-specific fine-tuning is notoriously plagued by overconfidence,

Mixture-of-Parallelisms: Towards Memory-Efficient Training Stack for Mixture-of-Experts Models

arXiv:2607.01844v1 Announce Type: cross Abstract: This paper showcases a memory-efficient training stack for Mixture-of-Experts (MoE) models. It is a training paradigm that combines and specializes va

On the Utility and Factual Reliability of Pruned Mixture-of-Experts Models in the Biomedical Domain

arXiv:2607.01444v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) models offer inference speedups via selective activation but impose substantial memory requirements because the whole network

Agents

Recursive Models for Long-Horizon Reasoning

arXiv:2603.02112v2 Announce Type: replace-cross Abstract: Modern language models reason within bounded context, an inherent constraint that poses a fundamental barrier to long-horizon reasoning. We id

agentsarxiv-cs-cl

Restoring Linguistic Grounding in VLA Models via Train-Free Attention Recalibration

arXiv:2603.06001v2 Announce Type: replace-cross Abstract: Vision-Language-Action (VLA) models enable robots to perform manipulation tasks directly from natural language instructions and are increasing

Unlocking Speech-Text Compositional Powers: Instruction-Following Speech Language Models without Instruction Tuning

arXiv:2607.02214v1 Announce Type: new Abstract: Instruction tuning for speech language models (SLMs) is substantially more challenging than for text-based large language models (LLMs), as it requires

researcharxiv-cs-cl

VLSA: Vision-Language-Action Models with Plug-and-Play Safety Constraint Layer

model-releasesarxiv-cs-ro

arXiv:2512.11891v2 Announce Type: replace Abstract: Vision-Language-Action (VLA) models have demonstrated remarkable capabilities in generalizing across diverse robotic manipulation tasks. However, de

Large language models replicate and predict human cooperation across experiments in game theory

arXiv:2511.04500v3 Announce Type: replace Abstract: Large language models (LLMs) are increasingly deployed as decision-making agents in high-stakes domains and as imitators of human behavior in the so

MEPA: Multi-Scale Representation Alignment for Visual Autoregressive Modeling with Mixture of Experts

arXiv:2607.00371v1 Announce Type: cross Abstract: Visual AutoRegressive modeling (VAR) has pioneered a coarse-to-fine multi-scale autoregressive generative paradigm, demonstrating strong capabilities

Predicting LLM Reasoning Performance with Small Proxy Model

arXiv:2509.21013v4 Announce Type: replace-cross Abstract: Given the prohibitive cost of pre-training large language models, it is essential to leverage smaller proxy models to optimize datasets before

safetyarxiv-cs-ai

RetailSMV: Exocentric vs. Egocentric Adaptation of Foundation Video World Models in Retail

arXiv:2607.00310v1 Announce Type: cross Abstract: Foundation video diffusion models are increasingly viewed as world simulators for embodied agents, yet their pretraining on internet-scale generic vid

Citation Discipline in Spec-Driven Development: A Cross-Model Empirical Study of Output Determinism and Automated Hallucination Detection in LLM-Generated Code

arXiv:2606.30689v1 Announce Type: cross Abstract: Spec-Driven Development (SDD) frameworks guide Large Language Model (LLM)-powered code generation through formal specifications, yet they differ funda

1 Jul 2026

Curvature-Guided Module Localization for Low-Rank Detoxification of Backdoored Large Language Models

arXiv:2606.30899v1 Announce Type: cross Abstract: Backdoor attacks pose a serious threat to large language models (LLMs) by causing otherwise benign systems to produce attacker-specified malicious beh