Search: “models”

Teaching Video Generators to Remember: Eliciting Dynamic Memory for Out-of-Sight State Evolution

arXiv:2605.25333v2 Announce Type: replace Abstract: Video world models should maintain evolving states when evidence is unobserved, yet current generators often freeze hidden states upon interruption.

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Research

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale

DGX agent

arXiv:2607.14144v2 Announce Type: replace Abstract: The Platonic Representation Hypothesis (PRH) holds that as models scale, representations of heterogeneous networks converge toward a shared model of

researcharxiv-cs-ai

3 Aug 2026

The Chinese labs everyone lumps together are making four pretty different bets. I work at one of them.

model-releasesr-localllama

Every time a model drops from a Chinese lab the thread fills with people who already know who made it, and the guess is usually Alibaba. There was a thread here recently asking what separates the open

Research

TokenSwap: Benchmarking and Reducing the Modality Gap in Multimodal LLMs

arXiv:2607.28640v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) should generate consistent responses given semantically equivalent inputs across modalities. However, we observ

researcharxiv-cs-cl

Understanding Alignment in Multimodal LLMs: A Comprehensive Study

Preference alignment has become a crucial component in enhancing the performance of Large Language Models (LLMs), yet its impact in Multimodal Large Language Models (MLLMs) remains comparatively under

safetyapple-ml-research

A Systems Engineering Framework for Vision-Language-Enabled UAV Triage and Disaster Response

arXiv:2607.27597v1 Announce Type: new Abstract: Recent advances in Vision Language Models (VLMs) have created new opportunities for disaster response, where responders must interpret large volumes of

safetyarxiv-cs-ro

AutoSupervision: Closing the Feedback Loop in Scientific Workflows with Grounded Revision Verification

arXiv:2607.27845v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have enabled AI systems to assist scientific research and peer review. However, an essential capability

Agents

Beacon: Knowing When and How to Perform Agentic Visual Reasoning

arXiv:2607.28595v1 Announce Type: new Abstract: The fundamental goal of agentic visual reasoning is to improve the success rate of multimodal large language models (MLLMs) on complex tasks, rather tha

agentsarxiv-cs-cv

Beyond Binary Rewards: A Comparative Study of Reward Design for Reinforcement Unlearning

arXiv:2607.27968v1 Announce Type: new Abstract: Machine unlearning seeks to selectively remove specific knowledge from trained language models without full retraining, a growing necessity under privac

Local Ai

Emulating Cosmic Structure Formation with a Lagrangian Neural Cellular Automaton

arXiv:2607.27320v1 Announce Type: cross Abstract: Field-level inference of cosmological initial conditions from galaxy surveys requires a forward model that is simultaneously accurate in the non-linea

local-aiarxiv-cs-lg

HARGO: Heterogeneity-Aware Reward-Guided Optimization for RL Post-Training of LLMs on HPC Tasks

arXiv:2607.28301v1 Announce Type: new Abstract: Supervised fine-tuning (SFT) can equip large language models (LLMs) with domain knowledge for high-performance computing (HPC) tasks such as data race d

JigShape: Evaluating Visual-Geometric Reasoning in VLMs through Jigsaw Puzzles

arXiv:2607.27670v1 Announce Type: new Abstract: Jigsaw puzzle solving requires jointly reasoning about visual content and geometric constraints, yet existing benchmarks use rectangular cuts that creat

MMAC: A Massive Multi-dimensional Benchmark for Audio Captioning

arXiv:2607.27109v2 Announce Type: cross Abstract: With the development of audio large language models (AudioLLMs), audio captioning needs to move from brief descriptions toward open-ended and fine-gra

MultivationBench: A Benchmark for Multimodal Sequential Motivation Reasoning

arXiv:2607.26465v1 Announce Type: new Abstract: Multimodal Large Language Models have sparked significant interest due to their potential for social intelligence; however, their ability to perform seq

New research from Microsoft. This one is on training computer-use agents at scale. Recent pipelines generate synthetic environments in bulk,…

New research from Microsoft. This one is on training computer-use agents at scale. Recent pipelines generate synthetic environments in bulk, which moved the bottleneck from how many exist to what is i

model-releasesdair-ai--x

Research

ProgFormer: Hierarchical Voxel Diffusion Transformer for Longitudinal Brain MRI Prediction

arXiv:2607.27537v1 Announce Type: new Abstract: Predicting future structural MRI of a brain is challenging because longitudinal changes are often subtle and confined to specific anatomical regions, wh

researcharxiv-cs-cv

Recursive transformers for semiconductor thermo-mechanical reliability

arXiv:2607.27251v1 Announce Type: new Abstract: Transformer-based surrogate models are increasingly used to replace expensive first-principles simulation in engineering design. But conventional transf

RefCaptioner: Multi-Reference Image-Grounded Video Captioning

arXiv:2607.28509v1 Announce Type: new Abstract: Existing video captioning models generate natural descriptions of video content but cannot explicitly ground local visual elements to multiple reference

Hardware

ROCS: Request-Oriented Compute Sharing for Efficient Large-Scale Recommendation

arXiv:2607.27744v1 Announce Type: new Abstract: Modern recommendation models gain prediction quality by scaling feature-interaction and sequence modules, but production cost constraints cap how far sy

hardwarearxiv-cs-lg

UrbanDS: A Graph-Guided LLM Multi-Agent System for Data-Intensive Urban Tasks

arXiv:2607.26724v1 Announce Type: new Abstract: Large language model (LLM) agents have been widely applied in automating data science tasks. However, existing methods typically rely on a limited set o

VESTIGE: A Knowledge-Guided Masking Strategy for Corruption-Aware Fine-Tuning of Genomic Transformers, Validated on Ancient DNA Reconstruction

arXiv:2607.27712v1 Announce Type: new Abstract: Standard masked-language-model fine-tuning applies a uniform masking probability across every token position, assuming reconstruction difficulty is posi

Agents

VideoCoCo: Code-as-CoT for Physically-Consistent Video Generation via an Agentic Dual-Engine System

arXiv:2607.27380v1 Announce Type: new Abstract: Text-to-video models have achieved remarkable visual quality, yet they still struggle to generate physically consistent dynamics because the temporal ev

agentsarxiv-cs-cv

Applications

ViewMind3D: Modular View-Aware Inference for Training-Free 3D-QA

arXiv:2607.28442v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) and vision-language models (VLMs) have enabled new possibilities for 3D question answering (3D-QA), a ke

applicationsarxiv-cs-cv

Research

What Is The Performance Ceiling of My Classifier? Utilizing Category-Wise Influence Functions for Pareto Frontier Analysis

arXiv:2510.03950v2 Announce Type: replace Abstract: Data-centric learning seeks to improve model performance from the perspective of data quality, and has been drawing increasing attention in the mach

researcharxiv-cs-lg

AdaMARP: An Adaptive Multi-Agent Interaction Framework for General Immersive Role-Playing

arXiv:2601.11007v2 Announce Type: replace-cross Abstract: LLM role-playing aims to portray arbitrary characters in interactive narratives, yet existing systems often suffer from limited immersion and

Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time

arXiv:2607.26647v1 Announce Type: new Abstract: While text-to-image diffusion models achieve impressive visual quality, they frequently struggle to maintain precise alignment with complex compositiona

safetyarxiv-cs-cv

BrainG3N: A Dual-Purpose Tokenizer for Controllable 3D Brain MRI Generation

arXiv:2606.19651v2 Announce Type: replace-cross Abstract: Three-dimensional (3D) brain MRI is central to clinical neurology and neuro-oncology, where generative models could augment under-represented

DialectLLM: A Dialect-Aware Dialog[ue] Generation Framework Beyond Standard American English

arXiv:2601.22888v4 Announce Type: replace Abstract: More than 80% of the 1.6B English speakers do not use Standard American English (SAE), yet LLMs often fail to correctly identify non-SAE dialects an

Evaluating Prompt Scope and Demonstration Similarity in Local LLM Machine Translation

arXiv:2607.26286v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used as general-purpose translation systems, but their behavior is usually evaluated under a single prompt

FAS-R1: A Unified Multi-Task MLLM for Reasoning Face Anti-Spoofing

arXiv:2607.26432v1 Announce Type: new Abstract: Face anti-spoofing (FAS) is increasingly expected to provide not only bona fide/spoof decisions, but also attack semantics and image-grounded evidence f

From Tokens to Watt-hours: Analytical Energy Estimation for LLM Inference on Modern GPUs

arXiv:2607.26571v1 Announce Type: new Abstract: The operational energy consumption of large language model (LLM) inference is becoming an increasingly important component of the environmental footprin

Hearsay: Vision-Language Medical Diagnoses Without an Image

arXiv:2607.26886v1 Announce Type: cross Abstract: When asked to describe a medical image that was never attached, frontier vision-language models do not abstain: they confabulate a diagnosis. We show

InferScale: GPU-Native KV Injection for Personalized LLM Serving

arXiv:2607.27090v1 Announce Type: cross Abstract: Large language models are increasingly deployed with persistent personalized context, such as accumulated memory profiles or long conversation histori

Investigating three real-world incidents in our cybersecurity evaluations

model-releasessimon-willison

Investigating three real-world incidents in our cybersecurity evaluations It happened again! This is turning into something of a pattern. Last week OpenAI accidentally exploited Hugging Face when one

Knowledge before Reasoning: EC-Reason-Bench, a Training-Free Diagnostic Benchmark for LLM Enzyme Classification

arXiv:2607.26397v1 Announce Type: new Abstract: Enzyme function prediction is a hierarchical, knowledge-intensive form of protein function classification. Existing benchmarks expose an anomaly: genera

Local Ai

Making a synthetic dataset for fine-tuning

I've been thinking about building a pipeline to generate reasoning training data for LLMs, but I want to avoid the common failure mode of synthetic data where you just generate the same template with

local-air-localllama

Mechanistic interpretability streamlined for everyday users like us😎 🧠

model-releasesr-localllama

Context: I want to give the community an Open Research (well open under Apache 2.0 clause) - tool that allows everyday users like us to look deeper into the local models we use consistently. Mechanist

On-Policy Distillation for LLM Safety: A Routing Approach to Template-Robust Realignment

arXiv:2607.27081v1 Announce Type: cross Abstract: Fine-tuning is the dominant paradigm for specializing large language models (LLMs), yet it exposes a critical vulnerability: malicious data providers

safetyarxiv-cs-cl

ReCo: Reweighting GRPO Against Distributional Concentration

arXiv:2607.26862v1 Announce Type: new Abstract: Group Relative Policy Optimization (GRPO) has become a standard reinforcement learning method for post-training language models. Recent work shows that

Rethinking Self-Evolution: A Constrained Exploration-Exploitation Process for Mitigating Skill Overfitting

arXiv:2607.26643v1 Announce Type: cross Abstract: Enabling large language model (LLM) agents to accumulate and reuse experience from past interactions remains a central challenge in real-world applica

SecRespond: Benchmarking AI Agents for Real-World Post-Compromise Incident Response

arXiv:2607.26791v1 Announce Type: cross Abstract: Large Language Model (LLM) agents are increasingly adopted in real-world security operations with access to host artifacts and command-line interfaces

sure we lose money on every inference but we make it up in volume

model-releasesgary-marcus--x

sure we lose money on every inference but we make it up in volume We are committed to pushing the model frontier across cost efficiency, capability, and speed. Starting today, we are reducing prices f

Symphony of Bias: Exploring Gender Associations with Musical Instruments in Multimodal LLMs

arXiv:2607.26355v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly embedded in everyday life and widely used for information seeking, raising concerns about their potential

This is absolutely wild... Anthropic reviewed their logs and found out that their own supposedly-sandboxed cyber evals had hacked three sepa…

model-releasessimon-willison--x

This is absolutely wild... Anthropic reviewed their logs and found out that their own supposedly-sandboxed cyber evals had hacked three separate companies back in April without them noticing! In a rev

From Deterministic to Generative Deep Learning for Urban Air Quality Reconstruction from Sparse Observations

arXiv:2607.25687v1 Announce Type: cross Abstract: Full-field reconstruction of air pollution is essential for evaluating pollution exposure and supporting public health decision-making. However, the c

Generalization from Low- to Moderate-Resolution Spectra with Neural Networks for Stellar Parameter Estimation: A Case Study with DESI

arXiv:2602.15021v2 Announce Type: replace-cross Abstract: Cross-survey generalization is a critical challenge in stellar spectral analysis, particularly in cases such as transferring from low- to mode

Harm is not Universal: Community-Specific Toxicity Detection is Urgently Needed

arXiv:2607.24898v1 Announce Type: cross Abstract: State-of-the-art toxicity detectors for text-to-image generation adopt a one-size-fits-all approach: a single universal model applying fixed safety gu

Learned, Relied Upon, or Necessary? Separating Checkpoint Dependence from Task-Level Value in Sheaf GNNs

arXiv:2607.25387v1 Announce Type: new Abstract: Learned restriction maps in sheaf graph neural networks are often treated as proof that the model has discovered useful edge geometry. That conclusion d