Search: “reasoning”

K-Bench: a clinically calibrated benchmark for evaluating large language models in high-risk mental health conversations

arXiv:2609.15855v1 Announce Type: cross Abstract: % !TEX root = ../main.tex People increasingly use large language models (LLMs) for mental health support, yet their safety in evolving, high-risk conv

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LabAgent: Customize Any Research Hubs for Scientific Discoveries Using AI Agents

DGX agent

arXiv:2609.13437v1 Announce Type: new Abstract: Scientific research is a continuous process that emphasizes inheritance. Methods developed by predecessors are often expanded upon by new researchers to

researcharxiv-cs-ai

15 Sept 2026

Learning the Intrinsic Dimensionality of Fermi-Pasta-Ulam-Tsingou Trajectories: A Nonlinear Approach using a Deep Autoencoder Model

arXiv:2601.19567v3 Announce Type: replace-cross Abstract: We address the intrinsic dimensionality (ID) of high-dimensional trajectories, comprising n_s = 4,000,000 data points, of the Fermi-Pasta-Ulam

researcharxiv-cs-lg

LIMBO: Lifelong Inference-Time Memory and Budget Optimization for LLM Agents

arXiv:2609.14138v1 Announce Type: cross Abstract: As LLM agents become integrated into increasingly complex workflows, they must continually acquire new capabilities while retaining competence on prev

LLM-Enhanced Multi-Agent Reinforcement Learning for Unified Electric Vehicles-Charging Station-Grid Optimization in Public Charging Systems

arXiv:2609.13805v1 Announce Type: new Abstract: In the era of the Internet of Things (IoT), coordinating connected electric vehicle (EV) charging scheduling to balance EV charging satisfaction, statio

LoRA Fine-Tuned Models for Control Systems Course Q&A: A Multidimensional Evaluation of Model Scale and Rank Effects

arXiv:2609.13918v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used in specialized university courses, but control-systems questions require coordinated terminology, not

Local Ai

MARC: Morphology-Aware Regression of Consensus for Cell Segmentation in Subcellular Spatial Transcriptomics

arXiv:2609.13665v1 Announce Type: new Abstract: Accurate cell segmentation remains a major bottleneck in subcellular spatial transcriptomics (SST), in which morphological images and spatially resolved

local-aiarxiv-cs-cv

MedSAM3: Delving into Segment Anything with Medical Concepts

arXiv:2511.19046v2 Announce Type: replace-cross Abstract: Medical image segmentation is fundamental for biomedical discovery. Existing methods lack generalizability and demand extensive, time-consumin

MessyMem: Learning-from-Doing Memory for Mobile Manipulation

arXiv:2609.15976v1 Announce Type: new Abstract: Mobile manipulators deployed across many rooms and visits should improve with experience: after discovering that a cabinet is locked or finding an objec

tutorialsarxiv-cs-ro

ModularRSI: Modular and Generalizable Recursive Harness Self-Improvement

model-releasesarxiv-cs-cl

arXiv:2609.14857v1 Announce Type: new Abstract: Recent work extends recursive self-improvement (RSI) to agent harnesses for long-horizon coding and terminal tasks, enabling agents to improve execution

Multi-Modal Tumor Survival Prediction via Graph-Guided Mixture of Experts

arXiv:2609.14072v1 Announce Type: new Abstract: Large Language Models (LLMs) have displayed impressive capabilities in handling tasks that require few demonstration examples, making them effective few

applicationsarxiv-cs-lg

Multilingual Agent System for Inclusive Wildfire Evacuation Guidance

arXiv:2609.03301v1 Announce Type: cross Abstract: Wildfire seasons have become 84 days longer in the current days than in the 1970s, causing enormous threats to one's financial status and short- and l

Natural Language Knowledge Graph Query Execution: Leveraging Controlled Semantics in the LLM Context Window

arXiv:2609.14652v1 Announce Type: cross Abstract: Large Language Model (LLM) applications often transfer domain concepts into the model's context informally, through prompt prose, schema dumps, and ex

Omni-Streaming Thinking

arXiv:2609.15128v1 Announce Type: new Abstract: Streaming omni-modal models must decide what and when to answer from the video chunks and synchronized audio observed so far. Visual cues often support

researcharxiv-cs-lg

OrchSLM: Probing the Dynamics of Small Language Model Orchestration

arXiv:2609.13470v1 Announce Type: new Abstract: Although large language models (LLMs) have demonstrated remarkable capabilities, their reliance on cloud-scale infrastructure poses fundamental challeng

Planning in the Backbone: DiffAdapterVLA for Native Continuous Trajectory Generation with Driving VLMs

arXiv:2609.15322v1 Announce Type: cross Abstract: Pretrained driving vision-language models (VLMs) integrate visual, route, language, and driving context into rich driving priors, yet their representa

Positioning manuscripts in the scientific landscape with agentic AI

arXiv:2609.13760v1 Announce Type: new Abstract: Publishing a research manuscript is a routine yet demanding part of scientific life: time-consuming, stressful, and often uncertain in outcome. Recent a

Positive Topology and Feasible Refinement: Forcing Matrices, Positivity, and Information

arXiv:2609.13523v1 Announce Type: cross Abstract: We develop a conceptual and operational account of Positive Topology starting from a basic relation between points or models and observable properties

applicationsarxiv-cs-ai

Predictive audio representations for early detection and tracking of hidden dynamic objects

arXiv:2609.13595v1 Announce Type: cross Abstract: Predicting potential dangers is core to safety. Forecasting the presence of other traffic agents is core to danger prediction. Occluded traffic agents

Preserving Guidance in Cost-Volume Retrieval under Extreme LiDAR Sparsity in Iterative Stereo

arXiv:2507.19738v2 Announce Type: replace Abstract: While accurate LiDAR depth has been shown to improve stereo matching, high-end LiDAR remains costly and difficult to deploy at scale, motivating gui

tutorialsarxiv-cs-cv

Local Ai

Qwen3.8-27B-NVFP4 1M context. So far so good.

I am a beginner, Took a while to get started, get everything right. This setup is native not container. Still not sure if I did this right, or if I can tune this more. Environment=HF_HUB_OFFLINE=1 Env

local-air-localllama

Realtime-Venus: A full-duplex interaction system with asynchronous delegation

model-releasesarxiv-cs-cv

arXiv:2609.13814v1 Announce Type: new Abstract: Natural interaction in digital and physical environments requires continuous perception and timely responses. Spoken dialogue relies on acoustic and lin

Recoverability as a System Primitive for Long-Horizon AI Agents

arXiv:2609.13672v1 Announce Type: new Abstract: AI agents can be interrupted while editing files, calling tools, or carrying out multi-step tasks. Restarting repeats completed work, but continuing fro

Refusal Reads Only a Slice of What the Model Knows: Harm-Keyed Routing and Its Exceptions Across Model Families

arXiv:2609.14759v1 Announce Type: cross Abstract: Alignment applied after pretraining is shallow in a measurable way: a single direction in a model's residual stream can be edited out, and the model s

ReMemNav: Memory-Based Decision Correction and Target Verification for Zero-Shot Object Navigation

arXiv:2603.26788v3 Announce Type: replace-cross Abstract: Zero-shot object navigation requires agents to locate unseen targets in unfamiliar environments without prior maps or task-specific training.

tutorialsarxiv-cs-cv

Rethinking Camouflage Image Generation towards a Training-Free Paradigm

model-releasesarxiv-cs-cv

arXiv:2609.14377v1 Announce Type: new Abstract: Camouflage image generation (CIG) aims to synthesize realistic camouflaged images by blending foreground objects into concealment-compatible background

Rethinking the Implications of Human Feedback for Preference Learning in Human-Robot Collaboration

arXiv:2609.13982v1 Announce Type: cross Abstract: In Human-Robot Interaction, the standard approach to learn a reward model that represents human preferences for robot behavior consists of three steps

tutorialsarxiv-cs-ai

Route, Don't Fix: Regime-Dependent Decoding Correction and a Trajectory-Gated Router for Reliable Clinical LLM Answer Selection

arXiv:2609.14825v1 Announce Type: cross Abstract: Large language models (LLMs) are often deemed unsafe for clinical question answering because of their tendency to hallucinate. Retrieval augmentation,

Safe Meta-Reinforcement Learning via Information Space Reachability

arXiv:2609.15915v1 Announce Type: new Abstract: Meta-reinforcement learning (meta-RL) enables agents to adapt to unseen tasks with limited experience. Despite its promise, the application of meta-RL i

safetyarxiv-cs-lg

Semantic-TVM: Structure-Preserving Trustworthy Virtual Memory for Memory-Augmented and Tool-Using Agents

arXiv:2609.15011v1 Announce Type: new Abstract: Memory-augmented and tool-using agents expose exact private values when remote LLMs process retrieved memory, tool actions, and intermediate observation

SparseTalk - Sparsifying 3D Gaussian Language Fields for Efficient 3D Visual Question Answering

arXiv:2609.15137v1 Announce Type: new Abstract: 3D Gaussian language fields provide an explicit, spatially grounded representation for 3D visual question answering (VQA), but their dense semantic feat

researcharxiv-cs-cv

Sparsity-Adaptive Sharpness-Aware Minimization

arXiv:2609.14274v1 Announce Type: new Abstract: Deploying deep neural networks in real-world settings requires models that are both compact and robust to common corruptions. However, at deployment-rel

applicationsarxiv-cs-cv

Talking to Me or Someone Else? Rethinking Talk-to-Me Detection in Egocentric Videos

arXiv:2609.14118v1 Announce Type: cross Abstract: Online understanding of who is talking to the camera wearer is a key capability for egocentric social interaction. However, existing talk-to-me (TTM)

TATK: Triple-Aware Top-K Learning with Knowledge-Grounded Verification for LLM-based Sequential Recommendation

model-releasesarxiv-cs-cl

arXiv:2609.14565v1 Announce Type: new Abstract: LLM-based sequential recommenders usually cast next-item prediction as text generation, but this interface is poorly matched to full-catalog top-K ranki

Testing the Limits of Truth Directions in LLMs

arXiv:2604.03754v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have been shown to encode truth of statements in their activation space along a linear truth direction. Previous

The Garden of Forking Prompts: How Users Explore Narrative Space in Story Generation

arXiv:2609.14677v1 Announce Type: new Abstract: Large language models (LLMs) have changed the way people engage with stories. Drawing on public chatbot logs, we can see that when users generate storie

researcharxiv-cs-cl

The Language-Energy Divide: Measuring Energy Costs of Multilingual LLM Inference

arXiv:2606.21869v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly deployed in multilingual settings, yet the energy costs of serving these models across different

The Universe of Universes: Benefit Yield Functions, Implosion Thresholds, and Infrastructure-Aware Optimization in Multi-LLM Systems

arXiv:2609.15314v1 Announce Type: cross Abstract: We introduce the Universe of Universes (UoU) framework, which treats the full ecosystem of major large language models (LLMs) as a structured retrieva

Towards Foundation Models for 3D Scene Understanding: Instance-Aware Self-Supervised Learning for Point Clouds

arXiv:2603.25165v3 Announce Type: replace Abstract: Recent advances in self-supervised learning (SSL) for point clouds have substantially improved 3D scene understanding without human annotations. Exi

tutorialsarxiv-cs-cv

Translating the Translator: Decomposing the Cost of English-Forced Inter-Agent Communication

arXiv:2609.15079v1 Announce Type: cross Abstract: Multi-agent LLM architectures, such as LangChain and AutoGen, largely assume English as the lingua franca for internal inter-agent communication, even

Trustworthy Agentic AI: A Comprehensive Cybersecurity and Systems Survey on Threat Landscapes, Defense Architectures, and Open Challenges

arXiv:2609.13731v1 Announce Type: new Abstract: The transition from passive foundation models to autonomous, goal-directed agentic AI systems has introduced unprecedented capabilities by coupling recu

TwinICL: Diagnosing Multimodal In-Context Learning through Paired Counterfactuals

model-releasesarxiv-cs-cv

arXiv:2609.15028v1 Announce Type: new Abstract: In-context learning (ICL) enables models to infer tasks from demonstrations, but existing benchmarks generally lack matched text and image versions need

unfairly-maligned symbolic AI is about to have its big moment - without formal verification we are screwed.

applicationsgary-marcus--x

unfairly-maligned symbolic AI is about to have its big moment - without formal verification we are screwed. Greg Brockman says OpenAI pointed Astra at its own systems until it ran out of vulnerabiliti

Utility-Guided Agent Orchestration for Efficient LLM Tool Use

arXiv:2603.19896v2 Announce Type: replace Abstract: Tool-using large language model (LLM) agents often face a fundamental tension between answer quality and execution cost. Fixed workflows are stable

Voodoo Dynamic Quant - Now MIT Licensed

model-releasesr-localllama

Two months ago I announced I had found a new dynamic quant method called Voodoo Quant which was SOTA for the most aggressive quant levels on some smaller Qwen3.5 GGUF models. I kept the methodology pr

When Consistency Does Not Mean Reliability: Evaluating Local LLM Judges Against Human Ratings

model-releasesarxiv-cs-cl

arXiv:2609.13824v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to evaluate the responses of other language models. This approach, known as LLM-as-a-Judge, is faster

Where are you running DeepSeek V4.1 Flash reliably? I can't get it to finish a single 2-hour benchmark run

model-releasesr-localllama

I reallise this is not exactly a locally hostable model, at least definitly not on my hardware. But I figured some of you might have some insight on this. I run an agentic coding benchmark. The model

Local Ai

Where to Look and What to Use: Retrieve-Localize-Generate for Long-Term Conversational Memory Question Answering

arXiv:2609.07093v2 Announce Type: replace Abstract: Retrieval-augmented generation (RAG) enables large language models (LLMs) to answer questions by accessing external knowledge and has been widely ad

local-aiarxiv-cs-cl