Search: “inference”

Investigating the Role of Reasoning-Language Alignment in Monolingual Retrieval-Augmented Generation

model-releasesarxiv-cs-cl

arXiv:2610.03136v1 Announce Type: new Abstract: Reasoning traces improve large language models (LLMs), but current models are trained to reason mostly in English. It has been shown that forcing a mode

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Model Releases

Kinematics-Induced Multimodal 3D Human Pose Estimation with Subject-Level Privacy

DGX agent

arXiv:2610.02943v1 Announce Type: new Abstract: Multimodal 3D Human Pose Estimation (3D HPE) combines complementary information from RGB, LiDAR, and mmWave radar, but models trained on correlated obse

model-releasesarxiv-cs-cv

5 Oct 2026

Large Language Continuous Diffusion Models

arXiv:2610.02665v1 Announce Type: cross Abstract: Despite the success of discrete diffusion language models (dLMs) for fast parallel decoding, their non-smooth, high-dimensional space hinders trajecto

Less Talk. More Breakout: Kolibri-1 Turns Probabilities into Actions, Playing Breakout - With under 25ms latency per move.

Got Kolibri-1 to play Breakout completely on its own, no fine-tuning. The more we explore u/Aleph__Alpha’s Kolibri the more it get's exciting and its potential. Less talk. More Breakout is one such ex

local-air-localllama

LiteEMG-FM: An Efficient and Deployable Foundation Model for Robust EMG Sensing

arXiv:2610.02497v1 Announce Type: new Abstract: Electromyography (EMG) signals vary substantially across individuals, body regions, recording sessions, and sensing hardware, limiting the generalizatio

local-aiarxiv-cs-lg

Native Action-Prior Learning from Videos for World Action Models

arXiv:2610.03391v1 Announce Type: new Abstract: World action models integrate future visual dynamics with robot action prediction, but their scalability remains limited by the need for action-annotate

safetyarxiv-cs-cv

Hardware

NetApp’s Novus tackles metadata bottlenecks in AI data infrastructure

AI data infrastructure must support growing GPU clusters while making enterprise data usable for models and agents. NetApp Inc. is tying intelligent data infrastructure to production AI through a unif

hardwaresiliconangle

Post-Training Quantization of Autoregressive Weather Models

model-releasesarxiv-cs-lg

arXiv:2610.02511v1 Announce Type: new Abstract: Advancements in high-resolution numerical weather prediction (NWP) and data assimilation (DA) have shaped the developments in deep learning (DL) archite

PsyEvo: A Personalized Counseling Agent That Self-Evolves at Test Time

arXiv:2610.02885v1 Announce Type: new Abstract: Mental health disorders affect a substantial proportion of the global population, yet a persistent shortage of trained practitioners leaves the majority

Qwen3.8-Flash-Next (125B) on a single Strix Halo mini PC: 44-59 tok/s with speculative decoding, ~1,400 tok/s prefill, engine is open

Hey all. We've spent the last weeks getting Qwen3.8-Flash-Next (125B MoE, 6B active) to run properly on one AMD Strix Halo box (Ryzen AI Max+ 395, 128 GB). Tonight we're releasing both the 95 GB EXL3

Recursive Agent Optimization

arXiv:2605.06639v2 Announce Type: replace-cross Abstract: We introduce Recursive Agent Optimization (RAO), a reinforcement learning approach for training recursive agents: agents that can spawn and de

Relevant Evidence Decoding for Audio-Visual Hallucination Mitigation

arXiv:2610.02976v1 Announce Type: new Abstract: Audio-Visual Large Language Models (AV-LLMs) remain prone to cross-modal hallucinations, where one modality incorrectly affects predictions about anothe

Reliability of Probabilistic Emulation of Physical Systems

arXiv:2606.12997v2 Announce Type: replace Abstract: Two dominant approaches have emerged for generating probabilistic forecasts of physical systems: generative models, such as diffusion or flow matchi

researcharxiv-cs-lg

Applications

ReSCUE: Re-translation with Sentence Commitment for Unsegmented Long-Form Simultaneous Sign Language Translation

arXiv:2610.03022v1 Announce Type: cross Abstract: Simultaneous Sign Language Translation (SLT) is critical for real-time communication, yet existing methods remain largely confined to sentence-level,

applicationsarxiv-cs-cl

Rethinking What to Cache in Few-Step Diffusion Transformers: Solver-Aware Target Selection

arXiv:2610.03577v1 Announce Type: cross Abstract: Diffusion Transformers (DiTs) can generate high-quality images and videos, but generating each sample requires multiple costly DiT forward passes. Two

SecJev: Bringing Security Expertise to System One Decision Models

arXiv:2610.03073v1 Announce Type: cross Abstract: Security workflows need models that turn complex observations and explicit policies into decisions. System One models introduced by Jev return typed p

safetyarxiv-cs-cl

SlimKV: Joint Token-Feature KV Cache Compression with Reconstruction-Free Beacon Attention

arXiv:2610.02953v1 Announce Type: new Abstract: Long-context LLM serving is increasingly bottlenecked by KV-cache memory, especially in resource-constrained scenarios. Among existing KV-cache compress

researcharxiv-cs-lg

T3lescope: Arbitrary-Resolution High-Fidelity Generative Surface Reconstruction from Images

arXiv:2610.03308v1 Announce Type: new Abstract: We reconstruct high-fidelity 3D scene meshes from posed multi-view images without per-scene optimization, across scales ranging from single objects to l

local-aiarxiv-cs-cv

Tangent Schrodinger Bridge Matching: Learning Stochastic Transport with Mechanistic Sensitivities

model-releasesarxiv-cs-lg

arXiv:2610.02906v1 Announce Type: new Abstract: Predicting how stochastic systems respond to changes in viscosity, reaction rates, or external forces requires costly simulations, motivating reusable l

Transcriptome-informed multi-modal AI for predicting neoadjuvant therapy response from breast cancer biopsies

arXiv:2610.03693v1 Announce Type: new Abstract: Scarcity of labeled data limits development of deep learning biomarkers in oncology. We develop a two-stage AI model predicting pathological complete re

Y'all this is a sexy paper; context language models

Paper linky - Context Language Models The central idea of the paper is incredibly simple. Give a model the ability to edit its context on-the-go like a file has major benefits on task performance, con

ZeroMAG: Zero-Shot Multimodal Adapter Generation for Plug-and-Play EEG Foundation Models

arXiv:2610.03546v1 Announce Type: new Abstract: EEG foundation models (EFMs) capture reusable knowledge from large-scale EEG data, while many EEG recordings also include companion physiological signal

researcharxiv-cs-lg

I Distilled an LLM into two 287M encoders (GLiNER + multiple choice) for document extraction, can't match teacher. did i do something wrong?

A while ago I asked here how to turn ~5 million court decisions into structured graphs without running an expensive LLM on every document thanks for the advice . I went with the 'small extractor + cla

Is Strix Halo (GMKtec EVO-X2, etc.) the closest thing we have to a 'dream' local LLM box?

I've been looking at the <32B model space and keep coming back to an interesting question. A few years ago, projects like Hummingbird+ suggested that cheap custom accelerators (FPGA-based) might becom

local-air-localllama

Syntheses

Synthesis: Arxiv-Cs-Ai

synthesisarxiv-cs-aiauto-generated

Auto-generated synthesis of 29846 entries about arxiv-cs-ai

driver-assistanceteslaelectric-vehicles

Syntheses

US family SUVs: Tesla FSD, Super Cruise, BlueCruise and Rivian Autonomy+

Human

US three-row SUV options distinguish Tesla's supervised route driving from rivals' hands-free assistance, with current six-seat options and child-seat fit limits.

I built Ninfer 4080 for 16GB class GPUs

Hi everyone, TL/DR I created NInfer 4080 to run ISTA-DASLab-Qwen-3.8-27B-GSQ at 100k context on an RTX 4080 16GB GPU using way more of the hardware capabilities (max overall: 2720 tok/s prefill, 262 t

3 Oct 2026

Running Qwen3.8 Flash Next 176B on a 16GB RTX 3080 Laptop + 32GB RAM + SSD

I wanted to see how far I could push a fairly ordinary laptop with a huge MoE model. Turns out, Qwen3.8 Flash Next 176B can run on: RTX 3080 Laptop — 16GB VRAM 32GB system RAM SSD No 128GB/256GB RAM w

3 Oct 2026

Hardware

Banger paper from NVIDIA on long running agents. A model can accept 128K tokens of context and still make more mistakes the longer it works …

Banger paper from NVIDIA on long running agents. A model can accept 128K tokens of context and still make more mistakes the longer it works through a task. If your agent loses its place partway throug

hardwaredair-ai--x

Beyond Final Accuracy: Auditing Communication in LLM Multi-Agent Systems

arXiv:2610.01042v1 Announce Type: new Abstract: Multi-agent communication aims to help agents benefit from one another's information. Yet improvements in system performance leave a fundamental ambigui

Bootstrapping Video Interaction Generation with Synthetic State Transitions

arXiv:2610.01039v1 Announce Type: new Abstract: While recent video generative models can synthesize high-fidelity videos, they struggle to portray plausible physical interactions and the resulting sta

researcharxiv-cs-cv

CARM: Cancellation-Aware Response Masking for LLM Reinforcement Learning

arXiv:2610.02039v1 Announce Type: cross Abstract: Recent years have witnessed the rapid adoption of reinforcement learning (RL) in large language model (LLM) post-training, with substantial gains in m

Applications

ChunkVLA-AM: Parallel Action Chunking for Vision-Language-Action Robot Control in Additive Manufacturing

arXiv:2610.01856v1 Announce Type: new Abstract: Vision-language-action (VLA) models unify visual perception, language understanding, and action generation, offering new opportunities for automation in

applicationsarxiv-cs-ro

Agents

Counting Moves, Weighing Voices: Bayesian Dialectical Argumentation for Calibrated Multi-LLM Councils under Persistent Adversaries

arXiv:2610.02005v1 Announce Type: new Abstract: A multi-LLM council lets several large language models (LLMs) deliberate on a question and return an answer together with a confidence estimate. As thes

agentsarxiv-cs-ai

Cross-Lingual Alignment for Decoder-Only Models using MoE Routers

arXiv:2610.01921v1 Announce Type: cross Abstract: Cross-lingual contrastive learning has been a core component of multilingual encoder training, but the ability to explicitly align representations is

Hardware

DRelay: Global Draft Context for Prefix-Aware Parallel Speculative Decoding Repair

arXiv:2610.01439v1 Announce Type: new Abstract: Parallel drafting reduces the drafting overhead of speculative decoding for large language models (LLMs), but its gains remain limited by the accepted p

hardwarearxiv-cs-ai

Emergent Unfaithfulness: How Alignment Training Causes Language Models to Silently Override Task Faithfulness

arXiv:2610.00568v1 Announce Type: cross Abstract: Large language models are characterized by three key properties: capability, alignment, and faithfulness. Prior work studies the tradeoffs between cap

Tutorials

Exploring More, Reasoning Better: Stepwise Risk-Sensitive GRPO for Diffusion Language Models

arXiv:2610.00661v1 Announce Type: cross Abstract: Diffusion large language models (dLLMs) generate text by denoising a sequence or successive blocks, allowing several tokens to be revealed in parallel

tutorialsarxiv-cs-ai

Fewer Tokens, Better Action: GPT-6 Astra Robot Agents with 14% Higher Success Rate but 65% Fewer Tokens

arXiv:2610.01939v1 Announce Type: new Abstract: Vision language model (VLM) agents can control robots through visual feedback and action primitives, but repeated model invocations and redundant observ

local-aiarxiv-cs-cv

Tutorials

FlashBack: Knowing When to Remember in Streaming Vision-Language Models

arXiv:2610.01192v1 Announce Type: new Abstract: Streaming vision-language models must process continuously growing video streams under a bounded compute budget, creating a persistent tension between r

tutorialsarxiv-cs-cv

GKE CPU startup boost: Accelerate app starts without over-provisioning

model-releasesgoogle-cloud-ai

Whether you’re launching microservices in response to sudden traffic spikes, deploying new software releases, or scaling up application replicas, pod startup time is critical to maintaining a fast, re

Hardware-Algorithm Co-Optimization of Early-Exit Neural Networks for Multi-Core Edge Accelerators

arXiv:2512.04705v3 Announce Type: replace-cross Abstract: The deployment of Early-Exiting Neural Networks (EENNs) on edge accelerators requires optimizing not only the network architecture but also it

researcharxiv-cs-cv

Harnessing Domain Specialists in Multimodal Mixture-of-Experts for Efficient Adaptation

arXiv:2610.02123v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) architectures scale model capacity through sparse computation, routing each token through only a small subset of experts. In th

researcharxiv-cs-cv

Homomorphic Advantage Operator: Stabilizing Reinforcement Learning Under Fully Homomorphic Encryption Constraints

arXiv:2610.02074v1 Announce Type: new Abstract: Privacy-preserving machine learning presents significant deployment challenges on the cloud for intelligent systems with confidential data. Fully Homomo

I benchmarked Qwen 3.8 27B on my M4 Max — here's what I learned about local models, context, and coding performance

I've been experimenting with running larger models locally with Ollama, mainly because I'm interested in using them for agentic coding. I kept seeing benchmarks expressed as something like: 40 tokens/

model-releasesr-ollama

ITC-MoE: Importance-guided Token-aware Compression for MoE Diffusion Language Models

arXiv:2610.01296v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) Diffusion Language Models (DLMs) offer flexible parallel decoding and increased model capacity, but their large number of exper

Iterative Policy Refinement through Semantic Rollout Analysis

arXiv:2610.01652v1 Announce Type: cross Abstract: Structured policies improve efficiency, robustness, and interpretability in imitation learning by introducing task-specific inductive bias, but existi

LabBook: Harnessing Experimental History for Efficient LLM-Driven Discovery

arXiv:2610.00675v1 Announce Type: cross Abstract: Evolutionary approaches to LLM-driven discovery often generate new programs from a small set of selected ancestors. This keeps contexts manageable but