Search: “reasoning”

arXiv:2608.22176v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly applied to clinical prediction tasks such as in-hospital mortality and readmission from electronic health

local-aiarxiv-cs-ai

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Local Ai

Significant improvements to Row-Bot recently. Looking for feedback.

DGX agent

v4.5.0: Added native desktop control, agent execution budgets, concurrency limits, loop protection, and safer local embedding fallback. v4.6.0: Rebuilt agents around durable parent-led orchestration.

local-air-ollama

25 Aug 2026

SLogic: Subgraph-Informed Logical Rule Learning for Knowledge Graph Completion

arXiv:2510.00279v3 Announce Type: replace-cross Abstract: Logical rule-based methods offer an interpretable approach to knowledge graph completion (KGC) by capturing compositional relationships in the

Social Graph Mamba: Forecasting Pedestrian Movements Based on Social Context

arXiv:2608.21411v1 Announce Type: new Abstract: Forecasting pedestrian motion has always been fundamental for autonomous navigation in crowded environments. While attention-based methods achieve stron

agentsarxiv-cs-ro

Spent a day seeing how far extreme MoE models can be pushed on a 4070 Ti + 32GB RAM. Kimi K3, DeepSeek V4 Flash, and Qwen3.5-122B results + research paper🔧

model-releasesr-localllama

I’ve been experimenting with a custom inference/runtime research project called CRANE V2, mostly because I wanted to answer a stupid question: How far can you push absurdly large MoE models on an ordi

Tutorials

SPOC-SQL: Stage-wise Preference Optimization for Controllable Text-to-SQL

arXiv:2608.22772v1 Announce Type: new Abstract: Text-to-SQL aims to translate natural language questions into executable SQL queries over relational databases, requiring multi-stage structured reasoni

tutorialsarxiv-cs-cl

Sycophants in the Courtroom: Are LLMs Fragile to Juridical Authority and Evolving Legal Standards?

arXiv:2608.21409v1 Announce Type: cross Abstract: In medicine, claims remain valid when supported by empirical evidence grounded in stable biological reality. In law, by contrast, truth is contingent,

The Collaboration Tax: How Much LLM Multi-Agent Systems Pay to Coordinate

arXiv:2608.22152v1 Announce Type: new Abstract: Multi-agent systems built from large language models are deployed widely, yet how much performance is lost when two LLMs must coordinate rather than act

agentsarxiv-cs-cl

The geometry of AI validation: Exact certification limits for iid best-of-N search

arXiv:2608.21496v1 Announce Type: new Abstract: AI systems increasingly generate alternatives, inspect evidence, and deploy a selected output. Validation is therefore target-relative: evidence certifi

applicationsarxiv-cs-lg

The Measurement Revolution? Credible Measurement and Inference in the Age of AI

arXiv:2608.23524v1 Announce Type: cross Abstract: Artificial intelligence (AI) is transforming measurement in economics. AI models convert unstructured data, such as text and images, into structured v

TONAV: Task-Oriented Navigation and Action-Velocity Chunk Learning for Articulated Object Quadrupedal Mobile Manipulation

arXiv:2608.22296v1 Announce Type: cross Abstract: Quadruped mobile manipulation requires two tightly coupled capabilities: reaching manipulation-ready configurations and maintaining stable contact thr

applicationsarxiv-cs-cv

Walking on the DARKSIDE

arXiv:2608.23370v1 Announce Type: new Abstract: Large Language Models (LLMs) recognise patterns but do not natively track the path of exclusions that a coherent discourse demands. When an input rests

What's the Catch? Evaluating Temporal Consistency in Vision-Language Models

arXiv:2608.23474v1 Announce Type: cross Abstract: Vision-language models (VLMs) achieve strong performance on video and image-sequence benchmarks, yet it remains unclear whether they capture temporal

Whitewashing Hate, Smearing Harmless Content: Annotator-Style Rebuttal Attacks on LLM-Based Moderation

arXiv:2608.22230v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for hate speech moderation, often within human--AI workflows in which reviewers provide feedback befo

researcharxiv-cs-cl

WorldMind: Decoupled Game World Model for State-Aware NPC Behavior

arXiv:2608.21439v1 Announce Type: new Abstract: Game world models have recently demonstrated promising capabilities in generating visually coherent and action-controllable gameplay videos. However, no

agentsarxiv-cs-cv

AgentMercury: Your Agent Can Synthesize Verifiable Environments for Business Scenarios at scale

arXiv:2608.20634v1 Announce Type: cross Abstract: Agents learn to act through interaction with environments, yet the environments used for training are often manually constructed or synthesized around

AI-driven Prices for Externalities and Sustainability in Production Markets

arXiv:2106.06060v4 Announce Type: replace-cross Abstract: Traditional competitive markets do not account for negative externalities; indirect costs that some participants impose on others, such as the

Applying Anthropic Primitives at Large Enterprises: Harness Paradigm for Knowledge Work

arXiv:2608.20622v1 Announce Type: new Abstract: Frontier models have collapsed the cost of writing custom code: a niche problem a specialist sees in their own domain now costs an afternoon. The cost o

ARGUS: Theory-of-Mind Guided Argument Generation with Strategy-Aware Planning and Knowledge Grounding

arXiv:2608.20405v1 Announce Type: new Abstract: Persuasive argument generation requires modeling audience beliefs, rhetorical strategies, and factual grounding. Despite recent advancements, existing m

agentsarxiv-cs-cl

ArtiMo: Agent-Driven Articulated Mesh Animation

model-releasesarxiv-cs-cv

arXiv:2608.20699v1 Announce Type: new Abstract: Animating articulated 3D meshes via text requires satisfying strict kinematic constraints, modeling causal interactions between parts, and achieving ins

Beyond Endpoint Gains: A Weight-Delta Audit of Medical Specialization

arXiv:2608.20768v1 Announce Type: new Abstract: Specialist language models are usually understood through endpoint gains: the generalist scores lower, the specialist scores higher, and the difference

Beyond Prompt Engineering: A Systematic Analysis of Prompt Lexical Sensitivity and Its Impacts on Quality

arXiv:2608.20349v1 Announce Type: cross Abstract: Large Language Models (LLMs) exhibit extreme sensitivity to surface-level prompt variations, in which minor lexical changes can trigger disproportiona

Building a restaurant telephony AI host with Amazon Connect

Learn how to build a voice ordering system for restaurants that answers a phone call and takes an order end to end, with no app, no website, and no sign-in. It uses Amazon Connect for telephony, Amazo

agentsaws-ml-blog

Can Scientific Claims Be Removed from Large Language Models? A Systematic Evaluation of Claim-Level Unlearning

arXiv:2608.20960v1 Announce Type: new Abstract: Language models (LMs) are trained on static scientific corpora, whereas scientific knowledge continuously evolves through correction and revision. Scien

CAS: Conformalized Agentic Search via Adaptive Retrieval and Policy Weighting

arXiv:2608.20771v1 Announce Type: new Abstract: Search Agents face a severe reliability crisis during reinforcement learning (RL) fine-tuning. Heuristic Top-K retrieval often causes critical evidence

CoAnchor: Robust Collaborative Perception under Spatio-Temporal Misalignment via Object-Level Anchors

arXiv:2608.21055v1 Announce Type: cross Abstract: Collaborative perception extends the sensing range of a single vehicle by fusing observations from nearby agents, which improves the robustness of aut

Dynamic Context Scheduling: Learning Beyond the Static Universe

arXiv:2608.20799v1 Announce Type: new Abstract: We study dynamic context scheduling as a training instrument for contextual re- inforcement learning. Rather than treating intra-episode context variati

Enhancing LLMs in Predictive Political QA with Semi-Structured Data

arXiv:2608.21218v1 Announce Type: new Abstract: Predictive political question answering (QA), such as predicting how a political actor will vote, goes beyond factual lookup. External political resourc

applicationsarxiv-cs-ai

EnSI-RAG: Entity-Structure-Indexed Retrieval-Augmented Generation for Long-Document Question Answering

arXiv:2608.21252v1 Announce Type: cross Abstract: Question answering (QA) over long, connected documents remains challenging because relevant evidence may span multiple entities and their relationship

Evaluation-as-Search: Adaptive Discovery of Grounding Failures in Meeting Assistants

arXiv:2608.20392v1 Announce Type: cross Abstract: LLM-powered meeting assistants are deployed at scale, yet systematic evaluation of their grounding fidelity remains limited to static benchmarks that

Explaining Intrinsic Moral Self-Correction with Mechanistic Interpretability

arXiv:2505.11924v4 Announce Type: replace-cross Abstract: Intrinsic moral self-correction refers to the phenomenon where a language model refines its ethical judgments or aligns its outputs purely thr

ExploraTwin, a Non-Profit Research Platform for Digital Twin Simulations

arXiv:2608.20539v1 Announce Type: cross Abstract: Digital twin simulations show promise, but current empirical evidence suggests that the approach should be tested before being deployed in any particu

applicationsarxiv-cs-ai

Extractive Summarization for Arabic Documents Using SAraBERT with a Semantic Siamese Similarity Evaluation Metric

arXiv:2608.20964v1 Announce Type: cross Abstract: In this research, we introduce SAraBERT, an enhanced version of AraBERT which proposes inter-sentence transformer layers for extractive summarization

Fine-tuning LLMs for Tourist Trajectory Prediction using Field Experiment Data

model-releasesarxiv-cs-lg

arXiv:2608.20830v1 Announce Type: cross Abstract: Evaluating mobility interventions at tourist destinations requires predicting visitor behavior under varying conditions. Traditional methods struggle

Free-Text Evaluation of LLMs for 5G Domain Knowledge and Fault Analysis using LLM-as-Judge

arXiv:2608.21021v1 Announce Type: cross Abstract: Real-world fault analysis in 5G and emerging 6G networks demands domain expertise to analyze free-text diagnostics, including root-cause explanations

From Regulation to Implementation: A Critical Evaluation of LLM-Assisted Regulatory Compliance in Industry

arXiv:2608.21317v1 Announce Type: new Abstract: The European Union (EU) has emerged as a leading regulatory body in the development of sustainability and privacy regulations. While new regulation requ

Tutorials

How to encourage smarter AI use in the classroom

This article is from Making AI Work, MIT Technology Review’s limited-run newsletter examining how to apply LLMs across industries. To receive it in your inbox, sign up here. Chatbots took many schools

tutorialsmit-tech-review

Hardware

How to Train a Real-World Silicon Concierge? Internalizing Complex Business Workflow to Only OneModel

arXiv:2608.20350v1 Announce Type: cross Abstract: Traditional industrial agents rely on modular pipelines, including Router, Retriever, Planner, Executor, Responder, Reviewer, and other components. Th

hardwarearxiv-cs-ai

I developed my own quantized LLM from scratch, trained on 30B tokens, deploys in 60 MB

model-releasesr-localllama

Reposting here after sharing this on [r/MachineLearning](r/MachineLearning) a few days ago, where it got a much better response than I expected (300+ upvotes, great questions, zero roasting) GitHub is

Local Ai

Keep Your Friends Close, and the Right Neighbours Closer: Disaster-Conditioned Kernel-Regularized Graph Attention for Building Damage Classification

arXiv:2608.20548v1 Announce Type: new Abstract: Disaster damage is spatial: buildings rarely fail in isolation. Yet using spatial context for damage classification remains surprisingly underexplored,

local-aiarxiv-cs-cv

LingShu: A Large-Scale Symptom-Centric Contextualized Knowledge Graph Bridging Traditional Chinese Medicine and Modern Biomedicine

arXiv:2608.20402v1 Announce Type: cross Abstract: Biomedical knowledge graphs (KGs) are pivotal for knowledge organization, yet traditional binary relations often struggle to represent the conditional

Masking Is Not Enough: Generative Restoration for Multimodal De-Identification in Medical AI

arXiv:2608.21133v1 Announce Type: new Abstract: Medical image-text data can expose protected health information (PHI) through both visible image content as well as accompanying text, creating a barrie

researcharxiv-cs-cv

MedRAGChecker: Claim-Level Verification for Biomedical Retrieval-Augmented Generation

arXiv:2601.06519v2 Announce Type: replace Abstract: Biomedical retrieval-augmented generation (RAG) can ground LLM answers in medical literature, yet long-form outputs often contain isolated unsupport

safetyarxiv-cs-cl

Move by Move: Measuring and Steering How LLMs Conduct Psychotherapy

arXiv:2608.21325v1 Announce Type: new Abstract: Users increasingly turn to large language models for emotional support, yet little is known about how these models actually conduct a psychotherapy inte

safetyarxiv-cs-cl

Quantization-Aware Healing: A Practical Recipe for Recovering Compressed, 4-Bit LLMs

arXiv:2608.20953v1 Announce Type: cross Abstract: Serving large language models cheaply increasingly means shipping models that are both structurally compressed to a fraction of their parameters and q

SDAD: Spec-Driven Agentic Development for the AI-Native SDLC

arXiv:2608.20341v1 Announce Type: new Abstract: Frontier coding agents backed by large language models with context windows from hundreds of thousands to millions of tokens are restructuring the Softw

SEISMO: Explanation-Aware, Trajectory-Conditioned LLM Agents for Sample-Efficient Molecular Optimisation

arXiv:2602.00663v3 Announce Type: replace Abstract: Optimizing molecules to achieve desired properties is a central bottleneck across the chemical sciences, particularly in the pharmaceutical industry

SKILL-RAG: Self-Knowledge Induced Learning and Filtering for Retrieval-Augmented Generation

arXiv:2509.20377v2 Announce Type: replace-cross Abstract: Retrieval-Augmented Generation (RAG) has significantly improved the performance of large language models (LLMs) on knowledge-intensive tasks i