Search: “context”

Split the Labor: Separating Evidence Interpretation from Decision Aggregation

arXiv:2608.14509v1 Announce Type: new Abstract: Systems that ask a language model to reach a conclusion from many sources usually concatenate them into one prompt. This conflates two operations with d

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TENET: One Step Toward Test-Driven Development for Repository-Level Code Generation

DGX agent

arXiv:2509.24148v4 Announce Type: replace-cross Abstract: Test-Driven Development (TDD) is a widely adopted practice that requires developers to create and execute tests alongside implementation. With

model-releasesarxiv-cs-ai

17 Aug 2026

Hardware

The conditional superiority of fast silicon sampling

arXiv:2608.14079v1 Announce Type: new Abstract: Silicon sampling can produce surprisingly good population estimates at times. Does doing it fast attenuate such fidelity? In this study, we extend and a

hardwarearxiv-cs-cl

TimeSage-EV: A Live Benchmark for Agentic Time Series Analysis in Evolving Environments

arXiv:2608.14270v1 Announce Type: new Abstract: Time series analysis in high-stakes domains relies on recurring data releases, where new observations can alter the evidence base and the validity of la

Trajectory Dynamics in Self-Supervised Learning Latent Space for Audio Deepfake Detection

arXiv:2608.13817v1 Announce Type: cross Abstract: Human speech production is constrained by physiology, giving rise to characteristic temporal structure on acoustic signals. We hypothesise that these

applicationsarxiv-cs-lg

TRIAGE: Risk-Controlled Pseudo-Label Admission for Annotation-Efficient Semi-Supervised Retinal OCT Classification

arXiv:2608.14321v1 Announce Type: new Abstract: The advanced retinal disease diagnosing imaging modality, optical coherence tomography (OCT), encounters a lack of automation because of the high expens

researcharxiv-cs-cv

Understanding and Mitigating Over-refusal for Large Language Models via Representation Intervention

arXiv:2511.19009v2 Announce Type: replace-cross Abstract: Large language models (LLMs) demonstrate powerful capabilities across various natural language processing tasks,yet their inherent safety vuln

safetyarxiv-cs-cl

Upped ChatGPT / Codex Subscription users limits to 900K in Hermes Agent, enjoy!

model-releasesnous-research--x

Upped ChatGPT / Codex Subscription users limits to 900K in Hermes Agent, enjoy! GPT-5.6 Sol 1M in Codex. This used to only work for API keys, but we just flipped the switch and works for usage through

Your Probabilistic JEPA Is Secretly a Hidden Markov Model: A State-Space Interpretation of Joint-Embedding Predictive Learning

arXiv:2608.13621v1 Announce Type: new Abstract: A hidden Markov model (HMM) combines three roles: inference of a hidden-state belief from observations, propagation through a Markov transition, and emi

5090: Windows or Linux for Qwen3.8.27b

I've got a dedicated AI rig sitting here with a RTX 5090 and 96GB RAM and for the past few years have been using Windows 11 and primarily LM Studio, but have also used vLLM, llama.cpp and Ollama. With

Huihui-ai Qwen 3.8 Ablit Available

At hugging face, this is the model I use for most of my analysis that most of my services have to not be refused. previous versions are quite good. It seems this might have dropped today and pulling r

Ideas are the new bottleneck @akshaynathan_, Core Product Engineering, @OpenAI, interviewed by @swyx and @Vibhu (@LatentSpacepod) Summary: A…

Ideas are the new bottleneck @akshaynathan_, Core Product Engineering, @OpenAI, interviewed by @swyx and @Vibhu (@LatentSpacepod) Summary: Akshay Nathan runs the productivity pillar at OpenAI, the tea

agentsswyx--x

Llama.cpp ROCm 7.2->7.14 upgrade, Radeon 780m iGPU benchmarks: ROCm vs Vulkan

With all the new models released recently one important upgrade went unnoticed: Llama.cpp bumped ROCm from 7.2 to 7.14. I was waiting for that because in 7.14 support for gfx1103 (Radeon 780m) was int

Mindblow with Qwen 3.8 (Cline + VSC on a 5090 mobile)

Honestly I am surprised at the speed and performance I am getting from the model, it does not allow for complete hands off like Claude 5.0 but that is not what I want, i want to be able to iterate and

model-releasesr-ollama

Ollama works locally, but my coding-agent integration does not

I’m running Ollama on an M4 Pro Mac with 48 GB unified memory and testing local coding models for repository work. Direct Ollama inference is fine. Qwen3.8 27B-MLX runs well enough for me, and the loc

model-releasesr-ollama

Qwen3.8 27B reasoning effort low/medium/xhigh comparison

I did a short test of the different reasoning efforts, since on default xhigh the model thinks a lot. Not very scientific, just a quick 'generate an SVG of a pelican on a bicycle' prompt with 3 differ

Show-off Saturday: Intel Arc B140 build.

My local inference build, with: ASUS WS C422 PRO/SE 10-core Xeon W-2255 64GB ECC RAM 64GB VRAM Pimped case with TurboLEDz indicating the frequencies of the 10 xeon cores. Running llama.cpp with SYCL b

totally agree! here's how we architected deepagents to enable this deepagents runs connected to a 'backend'. this backend needs to expose fi…

totally agree! here's how we architected deepagents to enable this deepagents runs connected to a 'backend'. this backend needs to expose filesystem like operations, but it does not have to be a files

agentsharrison-chase--x

Agentic harness for small models

Hello; I'm a semi-beginner at local AI. I've been experimenting with this tech for a while, and I still haven't found a proper harness that fits my models, hardware, and needs. My use case is pretty s

@hwchase17 @LangChain I built an open-source CLI that scaffolds, runs, and deploys production LangChain agents — frontend and backend in one…

@hwchase17 @LangChain I built an open-source CLI that scaffolds, runs, and deploys production LangChain agents — frontend and backend in one command. Every agent project starts the same way: wire up a

agentsharrison-chase--x

llama.cpp Windows Manager

https://github.com/alekk89/llama-cpp-windows-manager It has been three months since I first shared my personal solution for running llama.cpp on Windows, and the project has evolved considerably since

You can literally run Opus 4.6 Max-level intelligence on a MacBook Pro. Locally.

applicationsclem-delangue--x

You can literally run Opus 4.6 Max-level intelligence on a MacBook Pro. Locally. We promised open weights for Qwen3.8. Now, time to meet them! 🎉 ⚡ Qwen3.8-27B: - A native multimodal dense model. With

A Cloud-Edge System for Multimodal Clinical Screening in Resource-Constrained Rural Settings

arXiv:2608.12745v1 Announce Type: new Abstract: Medical AI has demonstrated specialist-level diagnostic accuracy, yet these capabilities remain largely inaccessible in resource-constrained rural setti

researcharxiv-cs-lg

A Deep RL based Framework for Targeted White Matter Tractography

model-releasesarxiv-cs-cv

arXiv:2608.12960v1 Announce Type: new Abstract: Fiber tractography's ability to reconstruct the brain's structural pathways, has made it a crucial component of modern neuroimaging, enabling detailed,

A Hierarchical Energy-Based Model for Multimodal Cognition

arXiv:2608.12398v1 Announce Type: cross Abstract: We propose IM-LEPP (Integrated Multimodal Latent Energy-based Predictive Processing), a hierarchical, energy-based model of multimodal cognition that

A Local-Linearly Convergent Algorithm for Nonconvex Equality-Constrained Optimization

model-releasesarxiv-cs-lg

arXiv:2608.12665v1 Announce Type: cross Abstract: For solving nonconvex equality-constrained optimization problems, a recent Gradient-Eigenstep Algorithm by Goyens et al.~is an iteration-efficient app

A Unified Framework for Joint Detection of Lacunes and Enlarged Perivascular Spaces

model-releasesarxiv-cs-cv

arXiv:2603.04243v3 Announce Type: replace Abstract: Cerebral small vessel disease (CSVD) markers, specifically enlarged perivascular spaces (EPVS) and lacunae, present a unique challenge in medical im

Alibaba releases weights for Qwen3.8 models under Apache 2.0 license, including Qwen3.8-27B, which it says beats Qwen3.7-Plus and excels in real-world coding (@alibaba_qwen)

@alibaba_qwen: Alibaba releases weights for Qwen3.8 models under Apache 2.0 license, including Qwen3.8-27B, which it says beats Qwen3.7-Plus and excels in real-world coding — We promised open weights

applicationstechmeme

b10434

model-releasesllama-cpp-releases

chat : pass reasoning_effort to template chat: add reasoning_effort to common_chat_templates_inputs Store OpenAI Chat Completions reasoning_effort and make it available to jinja templates (with model

BrainWAM: Action-Space Coordination of Semantic Priors and Predictive Dynamics for Autonomous Driving

arXiv:2608.12854v1 Announce Type: cross Abstract: Autonomous driving requires planning under both semantic constraints and predictive dynamics. Existing end-to-end driving approaches, however, typical

agentsarxiv-cs-ai

CityRiSE: Reasoning Urban Socio-Economic Status in Large Vision-Language Models via Reinforcement Learning

arXiv:2510.22282v2 Announce Type: replace-cross Abstract: Urban socio-economic sensing plays a vital role in advancing global sustainable development goals. With the advent of Large Vision-Language Mo

ContactGuard: Pre-Contact Execution Monitoring with Action-Conditioned Latent World Models

arXiv:2608.13438v1 Announce Type: cross Abstract: Contact-rich manipulation failures are often detected only after the robot has committed to contact. This is especially limiting in wrist-camera setup

safetyarxiv-cs-ai

Correct Is Not Governed: Provenance Integrity in Agentic Workflows

arXiv:2608.12761v1 Announce Type: new Abstract: Agentic workflows are commonly evaluated by whether they reach the correct outcome. That is insufficient in institutional settings, where a correct acti

agentsarxiv-cs-ai

DiffGRM: Diffusion-based Generative Recommendation Model

arXiv:2510.21805v2 Announce Type: replace-cross Abstract: Generative recommendation (GR) is an emerging paradigm that represents each item via a tokenizer as an n-digit semantic ID (SID) and predicts

safetyarxiv-cs-ai

Discovering Persistent Behavioural Patterns for Interpretable Blockchain Forensics

arXiv:2608.12864v1 Announce Type: cross Abstract: Public blockchain data enables large-scale DeFi-related analysis, but many existing approaches are application-specific, difficult to scale, or hard t

researcharxiv-cs-lg

Local Ai

Fast A/B/n Testing: Exact Multi-Policy Comparison via Tree-Coupled Feedback Sharing

arXiv:2608.12831v1 Announce Type: cross Abstract: Online platforms increasingly compare many adaptive decision policies---ranking systems, recommendation algorithms, pricing rules, and language-model

local-aiarxiv-cs-ai

Fine-Grained Action Recognition with Cross-Attentive Latent Sparse Experts

arXiv:2608.13458v1 Announce Type: new Abstract: Fine-grained human action recognition (FHAR) must distinguish visually similar actions that differ mainly in body configuration, timing, or local appear

researcharxiv-cs-cv

FlashDrive: Flash Vision-Language-Action Inference for Autonomous Driving

arXiv:2608.12932v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models promise to bring end-to-end reasoning to autonomous driving, but their computational cost remains far too high for r

FluctlightDB: A Memory Model of Data for AI Agents

arXiv:2608.12365v1 Announce Type: cross Abstract: For fifty years, data systems have answered two questions. The relational model asked which records match a predicate; the vector model asked which ve

Local Ai

For local-model agents, what architecture checks do you run before granting tool access?

Ollama makes it easy to run a model locally, but the hard part for me starts after the model responds: what keeps an agent from having unclear tool permissions, unbounded loops, silent partial failure

local-air-ollama

From Observation to Intervention: Memory in Brains and Large Language Models

arXiv:2608.12377v1 Announce Type: cross Abstract: Brains and large language models (LLMs) are fundamentally different memory systems, but they can be compared through shared functional questions: wher

GEM: A Generative Embedding Model Bridging Reasoning and Retrieval

arXiv:2608.13200v1 Announce Type: cross Abstract: Modern LLMs excel at reasoning and instruction following, enabling users to express complex and diverse information needs. However, conventional retri

H-VAEP and H-xT: Valuing Offensive On-the-Ball Actions in Handball by Estimating Probabilities

arXiv:2608.12926v1 Announce Type: cross Abstract: Traditional player evaluation in professional handball relies on basic box-score metrics or heuristic indices, which fail to credit the multi-player b

applicationsarxiv-cs-ai

Have been thinking about building a custom harness because nothing out there quite meets my needs for scaling a fully hybrid human + AI comp…

Have been thinking about building a custom harness because nothing out there quite meets my needs for scaling a fully hybrid human + AI company, especially when it comes to compounding learning loops.

agentsharrison-chase--x

Local Ai

HIMEC: Directional Change Representation and Fixed-Interface Decoding for Remote Sensing Image Change Captioning

arXiv:2608.12502v1 Announce Type: new Abstract: Remote sensing image change captioning (RSICC) converts bitemporal imagery into a sentence describing semantic changes. Most RSICC methods condition cap

local-aiarxiv-cs-cv

How Do VLMs Behave When Blind or Misled? Behavioral Evaluation of VLMs on Scientific Figures

arXiv:2608.13267v1 Announce Type: cross Abstract: Existing vision-language model (VLM) benchmarks emphasize perception and reasoning accuracy (how well VLMs describe and reason about what they see in

Jagged Judges: Epistemic Stability Under Silence, Pressure, and Persistence

arXiv:2608.12645v1 Announce Type: new Abstract: LLM judges have become central infrastructure for model evaluations, online grading, and reward modeling. Judges are typically validated by accuracy on

safetyarxiv-cs-ai

LittleLearner: Language Models Under Pedagogically Controlled Knowledge Exposure

arXiv:2608.13545v1 Announce Type: cross Abstract: Modern language models are trained on heterogeneous web-scale text corpora. Consequently, studying knowledge and skill acquisition is difficult, as pr