Search: “models”

Conformal Constraint Tightening for Chance-Constrained Motion Planning with Unknown Dynamics

arXiv:2607.22409v1 Announce Type: new Abstract: Motion planning algorithms compute control sequences that drive autonomous robots to goal regions while avoiding unsafe states. Existing methods, from s

agentsarxiv-cs-ro

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Model Releases

DBA-Bench: A Production-Fidelity Benchmark for LLM-Based Database Operations Agents

DGX agent

arXiv:2607.22165v1 Announce Type: cross Abstract: LLM-based database agents show promise, but differing task scopes, testbeds, and metrics hinder comparison. We identify four gaps between evaluation a

model-releasesarxiv-cs-cl

27 Jul 2026

Energy Manifold Natural Gradient Descent: Riemannian Optimization for Neural PDE Solvers

arXiv:2607.22004v1 Announce Type: new Abstract: Energy natural gradient descent (ENGD) aligns parameter updates with the curvature of an underlying function-space energy, but existing formulations ass

Evolution-Aware MSA Reasoning for Subsampling via Factor Graphs

arXiv:2607.22314v1 Announce Type: new Abstract: Multiple Sequence Alignments (MSAs) provide protein language models with explicit evolutionary context, but their large depth makes subsampling unavoida

GLI-AL: A Multi-Modal Glioma MRI Label Resource with Unified Anatomy-Lesion Labels

arXiv:2607.22135v1 Announce Type: new Abstract: Existing BraTS-GLI datasets provide a widely used benchmark for adult glioma MRI segmentation, but their task definition focuses on tumor subregions and

Great technical paper from Google. Great read on why context beats scale for agents working against unfamiliar APIs. (bookmark it) GPU kerne…

Great technical paper from Google. Great read on why context beats scale for agents working against unfamiliar APIs. (bookmark it) GPU kernel optimization has KernelBench to hillclimb on. TPUs had not

model-releasesdair-ai--x

Interior interpretability with attention rollout: contraction and propagation profiles in Transformers

arXiv:2607.22367v1 Announce Type: new Abstract: Feature-attribution methods assign scores relating input variables to a model's output, but do not by themselves characterize how explicitly defined int

Khondo: A Multimodal Benchmark for Document Packet Splitting of Bangla Forms

model-releasesarxiv-cs-cl

arXiv:2607.21780v1 Announce Type: new Abstract: Document packets, multiple documents concatenated into a single file, are common in government and administrative workflows, yet splitting them into the

Latent PDE mapping for efficient physics-informed learning across geometries with limited data

arXiv:2607.22215v1 Announce Type: new Abstract: In this study, we introduce latent PDE mapping, a broadly applicable physics-informed learning technique designed to enable efficient geometric generali

Safety

LayoutLite: Token-Level Implicit Layout Analysis for Efficient Document OCR

arXiv:2607.22200v1 Announce Type: new Abstract: End-to-end OCR systems based on vision-language models have achieved strong performance in complex document OCR, but their efficiency is limited by the

safetyarxiv-cs-cv

love this frame. calls to mind the role of the hippocampus in human navigation (via place cells and grid cells), and how navigation is, in a…

model-releasesyohei-nakajima--x

love this frame. calls to mind the role of the hippocampus in human navigation (via place cells and grid cells), and how navigation is, in a sense, what makes agents *agents* vs plain old LLM calls in

Nifer is insane. 700t/s with Qwen 3.6 35B (no thinking). Purpose build for RTX5090. Full 250k context too.

I just managed to get it running on windows and this thing is fucking insane. I get around 550-720t/s depending on task at hand. Previously to get to such numbers i would have to do batching and agent

On Improving Faithfulness of Podcasts from Documents

arXiv:2607.21961v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to generate long-form conversational content such as podcasts from textual sources. While these syste

researcharxiv-cs-cl

Operator-Informed Gaussian Processes for Complex Helmholtz Wavefields: From Synthetic Benchmarks to In Vivo Brain Elastography

arXiv:2607.14193v2 Announce Type: replace-cross Abstract: The Helmholtz equation governs time-harmonic wave propagation, and in dissipative media a complex modulus renders its squared wavenumber kappa

Optimal Transport Image Representation and Deep Covariance Alignment (CORAL) for Control Valve Stiction Detection

arXiv:2607.22486v1 Announce Type: new Abstract: Control valve stiction is a common cause of unwanted oscillations and poor control-loop performance in industrial processes. Data-driven methods can aut

Parameter-free Adaptive Sparse Attention via Compression-Based Content Selection

arXiv:2607.21752v1 Announce Type: new Abstract: Data-adaptive sparse attention masks substantially outperform fixed patterns (e.g., BigBird and Longformer) and can even exceed dense attention on long

Safety

Probing Latent Colombian Identity Inferences in Qwen2.5-7B with Natural Language Autoencoders

arXiv:2607.21774v1 Announce Type: new Abstract: Large language models may infer demographic attributes from subtle linguistic cues even when those attributes are not explicitly stated. This pilot stud

safetyarxiv-cs-cl

Re-FORC: Adaptive Reward Prediction for Efficient Chain-of-Thought Reasoning

arXiv:2511.02130v2 Announce Type: replace-cross Abstract: We propose Re-FORC, an adaptive reward prediction method that, given a query, enables prediction of the expected future rewards as a function

Risk-Routed Implicit Boundary Refinement for Robust Ultrasound Image Segmentation

arXiv:2607.21787v1 Announce Type: new Abstract: Medical ultrasound (US) image segmentation faces significant challenges due to speckle noise, low-contrast boundaries, acoustic shadowing, and acquisiti

SCOPE and SCION: A Benchmark and an Auditable Reference Pipeline for Schema Induction and Fusion from Text

arXiv:2607.21610v1 Announce Type: cross Abstract: Schema graphs are an upstream bottleneck of schema-grounded information extraction and knowledge graph construction, yet most extraction systems assum

Spectral Flow Certificates for Depth-Aware Long-Range Propagation in Graph Neural Networks

arXiv:2607.21607v1 Announce Type: cross Abstract: Graph Neural Networks propagate information through local message passing, but the graph topologies themselves can silently prevent any amount of trai

Synthetic Speech, Real Signal: Paralinguistic Preservation and Cross-Lingual Augmentation via Voice Cloning

arXiv:2607.22304v1 Announce Type: new Abstract: Synthetic data augmentation in speech is common practice for linguistic tasks like ASR, but has seen far less work for paralinguistic ones, especially c

GLM 5.2 and ik_llama.ccp

Running GLM-5.2 (the new glm-dsa arch), Unsloth UD-Q4_K_XL, on a 4-socket Xeon E7-8880 v4 box with 1TB RAM and a single RTX 3060 12GB. ik_llama.cpp, experts on CPU (--cpu-moe), 24 attention layers on

26 Jul 2026

Local Ai

I built an open-source Ollama canvas where the wires are the actual context

Most graph-based LLM interfaces use a canvas as a visual layer over what is still a linear chat. I wanted the graph itself to determine what Ollama receives. ThoughtDAG has one rule: wires are the con

local-air-ollama

26 Jul 2026

New research from NVIDIA. Does AdamW have a scale ceiling? This work claims yes, and shows where it sits. At batch sizes up to 100M tokens f…

New research from NVIDIA. Does AdamW have a scale ceiling? This work claims yes, and shows where it sits. At batch sizes up to 100M tokens for next-token prediction, SOAP and Muon maintain training st

model-releasesdair-ai--x

26 Jul 2026

CachyLLama: llama.cpp fork with persistent SSD-backed KV caching for local agent workflows

If you run local agentic coding harnesses (Aider, Claude Code, etc.), prompt evaluation usually eats up most of your execution time. Every turn re-evaluates thousands of identical prefix tokens_system

Is this real ? Qwen3.6:27b with 128k context fit in 24Gb VRAM ?

https://preview.redd.it/yw41s1jikefh1.png?width=1942&format=png&auto=webp&s=3a180ae6443c1db9f7b0ce621533a4b2aa553921 Hi, I've been running Ollama on my Unraid server since the llama2 era. I use to be

model-releasesr-ollama

Local Ai

Local alternative to Kling AI 3.0 Motion Control (ComfyUI, 16GB VRAM)

local-air-stablediffusion

Hi everyone, I'm looking for a local alternative to Kling AI 3.0 Motion Control that I can run in ComfyUI. What I'm specifically looking for is a model or workflow that allows me to: - Control charact

Local Ai

Old Coder Needs help with New AI Development and wants to get up to speed to understand it all.

Hi Guys, I'm an old coder and DBA that has been in the field for almost 40 years. More and more the jobs I was doing for work are being taken over by AI and the need for my type of work is diminishing

local-air-localllama

OpenAI’s agent went rogue, escaped containment, and spent days hacking Hugging Face. Before that, an OpenAI agent reportedly left notes for …

OpenAI’s agent went rogue, escaped containment, and spent days hacking Hugging Face. Before that, an OpenAI agent reportedly left notes for future versions of itself explaining how to break free from

agentsclem-delangue--x

Achieving Text-based Person Retrieval with Any Granularity

arXiv:2607.21057v1 Announce Type: new Abstract: Text-based person retrieval faces a critical but under-explored challenge: the inherent uncertainty of query granularity in real-world scenarios. This p

ADABORD: a novel AdaBoost approach for ordinal classification

arXiv:2607.21003v1 Announce Type: new Abstract: Ordinal Classification (OC) deals with classification tasks where the classes follow a natural order. Despite the progress in OC, many existing approach

Automated Synthesis and Adversarial Validation of Executable Causal Research Pipelines

arXiv:2607.21173v1 Announce Type: new Abstract: While automated research systems promise to accelerate empirical analysis, they are prone to silent failures: instances in which analysis code executes

AXIS: A Growable Community-Driven Data Engine for Scalable Robot Manipulation

model-releasesarxiv-cs-ro

arXiv:2607.21588v1 Announce Type: new Abstract: Learning effective robot manipulation policies requires diverse, high-quality demonstrations, yet existing data pipelines are often difficult to scale b

Benchmarking Unlearning for Vision Transformers

arXiv:2602.20114v2 Announce Type: replace-cross Abstract: Machine unlearning (MU) refers to the post-training capability to remove (the influence of) training examples that are incorrect, biased, or l

Beyond Independent Optimization: Compression, MoE Routing, and Quantization Interactions in Multimodal Edge Intelligence

arXiv:2607.20981v1 Announce Type: new Abstract: Efficient multimodal inference is increasingly constrained not only by model quality or FLOP count, but also by the cost of preserving, moving, routing,

researcharxiv-cs-ai

Tutorials

C-PTQ: Fisher-weighted Channel-wise Sensitivity for Post-training Quantization of MLLMs

arXiv:2607.21076v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) require huge memory and computational costs, which limits their practical deployment. Post-training quantizatio

tutorialsarxiv-cs-cv

CachyLLama’s: llama.cpp fork with persistent KV cache that makes long local-agent sessions much less painful

I’m not affiliated with this project, but I’ve been running it recently and I’m surprised it hasn’t received more attention here: https://github.com/fewtarius/CachyLLama CachyLLama is a fork of llama.

Can AI Agents Really Complete RTL-to-GDS? Lessons from Benchmarking Tool-Interactive EDA Workflows

arXiv:2607.17528v3 Announce Type: replace Abstract: Large language model (LLM) agents are extending electronic design automation (EDA) beyond static RTL generation toward long-horizon, tool-interactiv

agentsarxiv-cs-ai

CANN Bench: Benchmarking Agent Generated Kernels against Real NPU and Algorithmic Limits

arXiv:2607.20518v1 Announce Type: new Abstract: AI agents are now capable of writing, compiling, and iteratively optimizing low-level operator kernels on different hardware platforms. Existing benchma

Cardinality-Decomposed Loss: Matching Training Objectives to Relation Structure in Heterogeneous Recommendation Graphs

arXiv:2607.20737v1 Announce Type: new Abstract: Graph Neural Networks trained on heterogenous bipartite graphs form a common basis in recommendation systems. These graphs often express relations that

Case study: solving P-99 with LPTP and an LLM

arXiv:2607.21196v1 Announce Type: cross Abstract: Ninety-Nine Prolog Problems (P-99) is a famous set of Prolog exercises. We solved the first thirty three just by prompting an LLM (Large Language Mode

Chemical Chain-of-Thought Functions as a Hallucination-Prone Molecular Scratchpad

arXiv:2607.20935v1 Announce Type: cross Abstract: Chemical reasoning language models are expected to derive molecular answers through faithful chain-of-thought (CoT). However, across four reasoning mo

researcharxiv-cs-cl

CMI-Mem: Toward Generalizable Long-Term Memory Management via CMI-Augmented Reinforcement Learning

arXiv:2607.20553v1 Announce Type: new Abstract: Memory Manager models are pivotal in agent systems. Existing methods rely predominantly on LLM-judged synthetic question-answer (QA) pairs, making memor

agentsarxiv-cs-ai

Safety

Compile, Then Page: Executable SOP Programs and a Capability-Gated Runtime for Procedural LLM Agents

arXiv:2607.11346v3 Announce Type: replace Abstract: Enterprise agents must follow long-horizon, conditional, safety-critical standard operating procedures (SOPs). We compile machine-readable SOP const

safetyarxiv-cs-ai

Context-weighted Discrete Flow Matching

arXiv:2607.21427v1 Announce Type: new Abstract: Discrete flow matching provides a flexible framework for generative modeling on discrete structures. However, the standard factorized training objective

Demonstrating GenDB: Instance-Optimized and Customized Query Processing Code Generation via LLM Agents

arXiv:2607.20630v1 Announce Type: cross Abstract: Traditional query processing engines require continuous development and extensions to support new techniques and user requirements, and in some cases,

Drive As You Like: Multi-Head Diffusion with Reinforcement Learning for Personalized Driving

arXiv:2508.16947v2 Announce Type: replace-cross Abstract: Despite significant progress, imitation learning-based autonomous driving planners remain largely restricted to reproducing high-frequency bia