Search: “models”

Tight Sample Complexity for Low-Rank Adaptation: Matching Bounds and Rank Selection

arXiv:2607.27680v1 Announce Type: cross Abstract: Low-Rank Adaptation (LoRA) has become the standard mechanism for fine-tuning large pretrained models, yet its statistical properties remain only parti

31 Jul 2026

Model Releases

Using an AMD V620 workstation card for ComfyUI - success

DGX agent

A few weeks ago I posted about if it was worth using a V620 for Comfyui, and was told it likely wouldn't work, at least in Windows 11. And if it did, it would be far too slow and unusable. I decided t

model-releasesr-stablediffusion

31 Jul 2026

@ArtificialAnlys ok @openai gets it https://x.com/OpenAI/status/2082878156483219672

@ArtificialAnlys ok @openai gets it https://x.com/OpenAI/status/2082878156483219672 We are committed to pushing the model frontier across cost efficiency, capability, and speed. Starting today, we are

model-releasesswyx--x

b10188

model-releasesllama-cpp-releases

metal: fix memory unwire if model is freed without any GPU operations (#26082) metal: fix memory leak if model is freed without any GPU operations metal: run dummy work only if residency sets are used

Decoupled Visual Processing: Efficient Multimodal Adaptation via Modality-Specific Transformer Substitution

arXiv:2607.26596v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have demonstrated remarkable capabilities by integrating visual and textual understanding within a unified tran

Industry

Deploying Kimi K3 on AWS

Kimi K3 is a 2.8‑trillion‑parameter Mixture of Experts model released by Moonshot AI on July 27, 2026, with its weights publicly available for self-hosting. Its architecture—using Kimi Delta Attention

industryaws-ml-blog

Enhancing Generative Information Extraction with Two-step Validation: A Product Attribute Use Case

arXiv:2607.26780v1 Announce Type: new Abstract: The ability of large language models (LLMs) to process and generate text has introduced potential for applications in information extraction (IE). While

HiFloat4 Format for End-To-End Reinforcement Learning Post-Training of Large Language Models

arXiv:2607.26515v1 Announce Type: new Abstract: We present, to our knowledge, the first end-to-end FP4 RL post-training, in which both the rollout and training policies, including their forward and ba

safetyarxiv-cs-lg

Linguistic Monoculture in LLM-Assisted Language Use

arXiv:2607.27134v1 Announce Type: cross Abstract: Writing and communication are increasingly mediated by large language models (LLMs) that are being used to draft, revise and polish text. Although suc

researcharxiv-cs-cl

Position: Evaluation Scores Are Perishable Knowledge Claims

arXiv:2607.26191v1 Announce Type: cross Abstract: Evaluation methodologies for language models increasingly combine multiple signals, from automated metrics and LLM-as-judge ratings to human assessmen

RAGuard: A Layered Defense Framework for Retrieval-Augmented Generation Systems Against Data Poisoning

arXiv:2607.26339v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) systems ground large language models (LLMs) in external corpora, but this reliance exposes them to corpus poisoning

Self-Adaptive Learning and Model Predictive Control for Tracking Unknown Dynamics with No Regret

arXiv:2607.26370v1 Announce Type: cross Abstract: We propose a self-adaptive online learning for control method for tracking unknown target dynamics. The target dynamics can exhibit switching behavior

safetyarxiv-cs-lg

The Reliability of LLMs for Medical Diagnosis: An Examination of Consistency, Manipulation, and Contextual Awareness

arXiv:2503.10647v2 Announce Type: replace Abstract: This study evaluated the diagnostic reliability of two Large Language Models (LLMs), Google Gemini 2.0 Flash and OpenAI ChatGPT-4o, across three dim

Thinking Machines just released Inkling-Small: 276B total, 12B active. A faster Inkling that matches or beats its 975B big brother in many b…

model-releasessoumith-chintala--x

Thinking Machines just released Inkling-Small: 276B total, 12B active. A faster Inkling that matches or beats its 975B big brother in many benchmarks. To test its speed, we plugged it into HF's speech

b10174

model-releasesllama-cpp-releases

model: add NextN/MTP speculative decoding support for GLM_DSA (GLM-5.2) (#25980) model: add NextN/MTP speculative decoding support for GLM_DSA (GLM-5.2) Adds GLM-5.2 NextN/MTP as a --spec-type draft-m

Beyond Static Costs: Learning-Dynamics Aware Loss Functions for Long-Tailed Classification

arXiv:2607.25830v1 Announce Type: new Abstract: Deep learning models in computer vision face significant challenges when trained on long-tailed datasets, where a few majority classes dominate while ma

Contrastive Weak-to-strong Generalization

arXiv:2510.07884v3 Announce Type: replace-cross Abstract: Weak-to-strong generalization provides a promising paradigm for scaling large language models (LLMs) by training stronger models on samples fr

safetyarxiv-cs-ai

HANDBOOK.md: A Benchmark for Long-Context Agentic Instruction Following

arXiv:2607.25398v1 Announce Type: new Abstract: Language-model agents are increasingly deployed under standing instructions: a system prompt, a policy file, or a skills document is placed in context,

KQFuzz: Knowledge-Guided Fuzzing for Quantum Libraries via Large Language Models

arXiv:2607.25647v1 Announce Type: cross Abstract: As quantum computing continually improves, ensuring the reliability and correctness of quantum libraries has become increasingly critical. To this end

researcharxiv-cs-ai

LaP-Forensics: Latent-Pixel Consistency Guided Multimodal Reasoning for Deepfake Detection

arXiv:2607.25962v1 Announce Type: new Abstract: Recent generative models can produce images with few obvious visual artifacts, weakening detectors and explanations that rely only on surface appearance

Localized Adaptation Reveals Distinct Learning Signatures in Transformers

arXiv:2607.25663v1 Announce Type: new Abstract: Transformer adaptation is typically distributed across model depth, even when the intended change is narrow. We investigate how adaptation site shapes w

M^2PO: Multi-Perspective Multi-Pair Preference Optimization for Machine Translation

arXiv:2510.13434v2 Announce Type: replace Abstract: Aligning Large Language Models (LLMs) with human preferences is pivotal for Machine Translation (MT), yet current approaches are often hindered by m

Multimodal Hybrid Retrieval-Augmented Generation for Scientific Document Understanding using Open-Source SLMs

arXiv:2607.24799v1 Announce Type: cross Abstract: Large Language Models tend to hallucinate when answering domain-specific ques tions from scientific documents without prior fine-tuning. Currently, me

Parallel Decoding Distillation for Fast Image and Video Generation

arXiv:2607.26004v1 Announce Type: new Abstract: Generation in video diffusion or flow models is computationally expensive due to the slow and iterative sampling process. Current state-of-the-art (SOTA

PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents

arXiv:2607.25485v1 Announce Type: new Abstract: Health AI is evolving from answering questions to agentic systems that converse with patients, reason about health records, and act on their behalf. Pri

Physics-Grounded Fluid Video Generation with a Simulation Dataset and Dual-Stream Optical-Flow Supervision

arXiv:2607.25321v1 Announce Type: new Abstract: Video diffusion models generate visually compelling content but routinely violate elementary physics when the subject involves fluids: liquid columns br

The borderless Lakehouse: Bring AWS, Databricks and Snowflake data to your AI agents

model-releasesgoogle-cloud-ai

Today’s data lakehouse is no longer mere data repository, but increasingly a system of action, actively executing tasks via always-on, autonomous AI agents. Rather than waiting for static reports, the

Local Ai

Athena-Brain Technical Report: An Efficient Robot Brain for General Intelligence and Embodied Interaction

arXiv:2607.18985v2 Announce Type: replace Abstract: Large language models (LLMs) have demonstrated remarkable capabilities in language understanding, reasoning, and world knowledge. As embodied agents

local-aiarxiv-cs-ai

Benchmarking LLMs for Verilog Design Flows

arXiv:2607.22759v1 Announce Type: cross Abstract: Large language models (LLMs) show promise in code generation, but their capabilities to produce correct, synthesizable hardware description language (

Beyond a Global Norm: Personalizing Toxicity Sensitivity in Language Models Without Retraining

arXiv:2607.23175v1 Announce Type: cross Abstract: Reducing toxicity is often framed as a global alignment problem, yet perceptions of harmful language are subjective and context-dependent. We present

safetyarxiv-cs-ai

Beyond ICA: Identifiability by Symmetry Breaking

arXiv:2607.23182v1 Announce Type: cross Abstract: We prove the identifiability of deep generative models (DGMs) with piecewise-affine (PWA) decoders and Gaussian mixture model (GMM) priors, in a purel

CausalGate: Causal Importance Distillation for Transformer Module Pruning

arXiv:2607.22720v1 Announce Type: cross Abstract: Existing adaptive inference methods for Large Language Models rely on observational heuristics, such as hidden-state similarity or activation magnitud

Differencing the Diffusion Trajectory toward Uncertain Components for Time Series Forecasting

arXiv:2607.22599v1 Announce Type: new Abstract: Diffusion models have become a widely used framework for probabilistic time series forecasting, modeling the distribution of future values given an obse

researcharxiv-cs-ai

DuoAD: Leveraging [CLS] Dual Characteristics for Training-Free Few-Shot Anomaly Detection

arXiv:2607.23924v1 Announce Type: cross Abstract: Vision foundation models have enabled strong training-free anomaly detection (AD). However, most existing approaches rely primarily on independent loc

DynaCalKV: Key-Value Cache Compression via Head Grouping and Adaptive Rank Allocation

arXiv:2607.24331v1 Announce Type: new Abstract: As the inference phase of Large Language Models (LLMs) requires handling long context windows, the Key-Value (KV) cache initially appears to address thi

E-Bench: Benchmarking Multi-Step Tool-Use Agents in Real-World Product Scenarios

arXiv:2607.23722v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed as agents that interact with stateful environments over multiple steps: gathering hidden informat

Evidence Attribution in Visual Document Understanding without Coordinates or Region Labels

arXiv:2607.24651v1 Announce Type: cross Abstract: Reliable visual document understanding requires a model to attribute each answer to the evidence regions that support it. Recent benchmarks and system

researcharxiv-cs-cl

Harmonized Interpretable ECG Waveform Features for Robust Cross-Dataset Clinical Prediction

arXiv:2607.23412v1 Announce Type: new Abstract: Electrocardiograms (ECGs) are widely used for cardiovascular risk prediction, yet models often fail to transfer across hospitals because of protocol, po

INSIGHT: Spatially resolved survival modelling from routine histology crosslinked with molecular profiling reveals prognostic epithelial-immune axes in stage II/III colorectal cancer

arXiv:2512.22262v2 Announce Type: replace-cross Abstract: Routine histology contains rich prognostic information in stage II/III colorectal cancer, much of which is embedded in complex spatial tissue

researcharxiv-cs-lg

LFM2.5-Encoders: Fast at Long Context, Even on CPU

model-releasesr-localllama

LFM2.5-Encoder is a family of multilingual bidirectional encoders built on the LFM2 architecture, available in two sizes: LFM2.5-Encoder-230M — a lightweight encoder for tight latency and memory budge

Tutorials

Like a Baby: Visually Situated Neural Language Acquisition

arXiv:1805.11546v3 Announce Type: replace-cross Abstract: We examine the benefits of visual context in training neural language models to perform next-word prediction. A multi-modal neural architectur

tutorialsarxiv-cs-ai

Not Forgotten: Implementation and Evaluation of a Personalized Episodic Memory for the Humanoid Robot Head Kim

arXiv:2607.24190v1 Announce Type: cross Abstract: Social robots that rely on large language models for conversation are unable to retain information across sessions. This absence of memory violates so

researcharxiv-cs-ai

Nova3D: Code-Native Generation of Programmable 3D Assets

arXiv:2607.22738v1 Announce Type: cross Abstract: Current 3D generative models mostly produce a final surface: a visually strong but largely opaque mesh. Interactive 3D worlds need more than a surface

ObsDriveBench: Benchmarking Multimodal Understanding under Adverse Weather with Observability Awareness

arXiv:2607.23537v1 Announce Type: new Abstract: Autonomous driving under adverse weather remains a critical challenge, yet existing vision-language benchmarks mainly evaluate under standard conditions

PANOPTICON: A PII-Based Assemblage of Naturalistic Output Tokens for Investigating Privacy Leakage Within LLM Context Window

arXiv:2607.22695v1 Announce Type: new Abstract: Large Language Models (LLMs) are capable of generalizing human language for the completion of never-before-seen tasks, leading to widespread deployment.

Scale Weight Decay and Train Better

arXiv:2607.23777v1 Announce Type: cross Abstract: The discovery of scaling laws has motivated training neural networks on ever increasing quantities of data. This is typically done with a constant dec

Seesaw: Accelerating Training by Balancing Learning Rate and Batch Size Scheduling

arXiv:2510.14717v2 Announce Type: replace-cross Abstract: Increasing the batch size during training -- a ''batch ramp'' -- is a promising strategy to accelerate large language model pretraining. While

Spatial Reasoning in LLM Game Agents: Impact of Causal Context and Multi-Step Planning

arXiv:2607.22732v1 Announce Type: new Abstract: LLM-based game agents often perform poorly on more complex tasks. This work examines whether these failures are linked to limited spatial reasoning and