Search: “reasoning”

The most important agentic workflows are the ones where you collaborate with the agent, verify its results, and encode them as a skill or ve…

The most important agentic workflows are the ones where you collaborate with the agent, verify its results, and encode them as a skill or verifier for reuse. This works for things like writing, resear

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Towards Reversible Forgetting: Managing Obsolete Knowledge in Continual Enterprise AI Agents

DGX agent

arXiv:2608.18177v1 Announce Type: new Abstract: Continual learning has traditionally treated forgetting as a failure, emphasizing preservation of previously acquired knowledge as environments evolve.

safetyarxiv-cs-lg

20 Aug 2026

Trust as a Field: A Macroscopic Representation for Vehicular Networks

arXiv:2608.18178v1 Announce Type: new Abstract: Trust assessment is a fundamental component of cooperative and connected vehicle systems. However, existing approaches operate primarily at the level of

researcharxiv-cs-ro

Verifiable abstention makes AI leak diagnosis accountable in water distribution networks

arXiv:2608.18836v1 Announce Type: new Abstract: Utilities lose a substantial share of treated water to leakage, yet rarely trust artificial-intelligence localizers to dispatch crews: guessing everywhe

When Readability and Source Retention Diverge: An Evaluability Gap in AI Translation

arXiv:2608.19083v1 Announce Type: cross Abstract: Readable AI output can leave an evaluability gap: even when the source is shown, an overall-quality judgment may not reflect what an output preserves.

researcharxiv-cs-cl

When Two Tracers Disagree: An Investigation of Multimodal Fusion for Clinical PET/CT Segmentation

arXiv:2608.19063v1 Announce Type: new Abstract: PSMA and FDG PET/CT visualise complementary biological information in prostate cancer. Combining both tracers could capture heterogeneous tumour phenoty

researcharxiv-cs-cv

A Theoretical Framework for Parallel Lifelong MAPF Using Group Decentralized Planning

arXiv:2608.17928v1 Announce Type: cross Abstract: In the Lifelong Multi-Agent Path Finding (L-MAPF) problem, agents must repeatedly move from one destination to another while avoiding obstacles and in

agentsarxiv-cs-ai

AdaLens: Interactive Storyline for Monitoring and Steering Long-Running Agentic Data Analysis

arXiv:2608.17834v1 Announce Type: cross Abstract: Large language models are pushing data science toward increasingly autonomous and agentic workflows, with recent systems already supporting multi-step

agentsarxiv-cs-ai

Adversarial Data Modeling in Epidemiology

arXiv:2602.20134v2 Announce Type: replace-cross Abstract: Epidemiological models increasingly rely on crowdsourced, self-reported behavioral data such as vaccination status, mask usage, and social dis

safetyarxiv-cs-ai

Aloha! 🌺Introducing Ornith-1.5, a family of open-source LLMs spanning 9B Dense, 35B MoE, and 397B MoE, trained with self-improving strategi…

model-releasesclem-delangue--x

Aloha! 🌺Introducing Ornith-1.5, a family of open-source LLMs spanning 9B Dense, 35B MoE, and 397B MoE, trained with self-improving strategies. It achieves state-of-the-art performance among open-sourc

Local Ai

AntLing’ve open-sourced 6 Base Model checkpoints for Ling-3.0-tiny & Ling-3.0-flash, covering pre-trained, mid-trained, and WSM-merged stages.

None has undergone post-training, giving researchers flexible starting points for continued pre-training, fine-tuning, and further research. Two key highlights: - They use WSM to replace LR decay with

local-air-localllama

ArborMem: Navigating Interaction States with Memory Forests

model-releasesarxiv-cs-cl

arXiv:2608.17534v1 Announce Type: new Abstract: Large language models increasingly serve as persistent conversational assistants, requiring memory that preserves relevant experience and maintains cont

Benchmarking the Benchmarks: Evaluating Automated Safety Benchmarks for Small Language Models

arXiv:2608.17183v1 Announce Type: new Abstract: Small Language Models (SLMs) are increasingly deployed in resource-constrained, privacy-sensitive settings, where safety and bias failures can cause sec

CABLE: Extending the Reach of Memory Retrieval via Complementary Antecedent-Based Linking and Expansion

model-releasesarxiv-cs-cl

arXiv:2608.17911v1 Announce Type: new Abstract: As LLM agents operate across structured workflows and sessions, preserving long-term history does not ensure that later contexts can recover relevant ev

Comparative Study of Out-of-the-Box Technology for Automatic Target Detection and Recognition

arXiv:2608.17917v1 Announce Type: cross Abstract: Automatic Target Detection and Recognition (ATD/R) is critical for military decision support and (semi-)autonomous operations. Recent advances in obje

DataSTORM: Deep Research on Large-Scale Databases using Exploratory Data Analysis and Data Storytelling

arXiv:2604.06474v2 Announce Type: replace Abstract: Deep research with Large Language Model (LLM) agents is emerging as a powerful paradigm for multi-step information discovery, synthesis, and analysi

agentsarxiv-cs-cl

DFlash2 speeds Qwen 3.8 27B up to 4 times

model-releasesr-localllama

llama.cpp pr #27342 adds dflash2, so i rented an rtx 6000 and ran the same four prompts through four decoding setups on qwen3.8 27B median results over the four tasks: baseline 47.4 tok/s mtp 114.7 to

Domain-Adapted Molecular Language Models for Efficient Search of Make-on-Demand Libraries

arXiv:2608.17567v1 Announce Type: cross Abstract: Pretrained molecular language models are increasingly used as molecular encoders for learning structure-property relationships. However, their practic

Dripper: Token-Efficient Main HTML Extraction with a Lightweight LM

model-releasesarxiv-cs-cl

arXiv:2511.23119v3 Announce Type: replace Abstract: High-quality main content extraction from web pages is a critical prerequisite for constructing large-scale training corpora. While traditional heur

Eval4Sim: An Evaluation Framework for Persona Simulation

arXiv:2603.02876v2 Announce Type: replace Abstract: Large Language Model personas, explicit profiles specifying a user's attributes, preferences, and behavioural tendencies, are increasingly used to s

safetyarxiv-cs-cl

GADR: Gathering Architecture Decision Records from Meeting Transcriptions

arXiv:2608.17694v1 Announce Type: cross Abstract: Existing LLM-based approaches to Architecture Decision Record (ADR) generation share a critical and largely unexamined assumption: that input is alrea

agentsarxiv-cs-ai

GazeXPErT: An Expert Eye-tracking Dataset for Interpretable and Explainable AI in Oncologic FDG-PET/CT Scans

arXiv:2603.00162v2 Announce Type: replace-cross Abstract: [18F]FDG-PET/CT is a cornerstone imaging modality for guiding oncology therapies, yet human expert shortages necessitate more efficient diagno

researcharxiv-cs-cv

GxP-Agent: Process-DAG Topology for Reliable Clinical Trial Programming with LLM Agents

arXiv:2608.16890v1 Announce Type: new Abstract: Clinical trial programming -- transforming study protocols into analysis-ready datasets under CDISC standards -- is a bottleneck in regulatory submissio

HarnessRisk: A Lifecycle-Oriented Benchmark for Agent Harness Safety

arXiv:2608.17597v1 Announce Type: cross Abstract: Large language models are increasingly deployed through agent harnesses that manage tools, extensions, persistent state, permissions, and external act

It was great to be back at @bloomberg studios to chat with @TimStenove1g. We covered quite a bit, but there's one thread worth amplifying fo…

It was great to be back at @bloomberg studios to chat with @TimStenove1g. We covered quite a bit, but there's one thread worth amplifying for founders: the growing importance of having a non-consensus

researchyann-lecun--x

Leveraging Association Context Retrieval in Knowledge Edit- ing to Build White-Box Attacks on LLMs

arXiv:2608.17836v1 Announce Type: new Abstract: As large language models (LLMs) are granted increasing autonomy, it is essential to investigate methods that can induce unsafe behavior. We propose a no

researcharxiv-cs-lg

LZ Penalty: An information-theoretic repetition penalty for autoregressive language models

arXiv:2504.20131v4 Announce Type: replace-cross Abstract: We introduce the LZ penalty, a penalty specialized for reducing degenerate repetitions in autoregressive language models without loss of capab

researcharxiv-cs-ai

Make an instant one-person company with @Grok @Bot

Make an instant one-person company with @Grok @Bot Grok Bot is the best AI agent right now It gives you an army of agents that can do work for you 24/7 If you set it up correctly, you gain super power

agentselon-musk--x

MaLViL: Multi-axis Low-rank Vision-LSTM for Medical Image Segmentation

arXiv:2608.17635v1 Announce Type: new Abstract: Vision-LSTM (ViL) enables efficient global modeling, but its cost still scales with the number of spatial tokens, so existing segmenters confine ViL to

researcharxiv-cs-cv

Local Ai

MotoSafety: Edge-AI with Learned Temporal Importance for Two-Wheeler Collision Risk Assessment Under Time Pressure

arXiv:2608.17823v1 Announce Type: cross Abstract: Powered two-wheeler riders face critical safety challenges in low- and middle-income countries, yet limited studies exist on how cognitive stressors s

local-aiarxiv-cs-ai

NVFP4 on VOLTA! Despite being built for Blackwell, I made four 2017 V100s run Qwen 3.8 NVFP4 natively and match my $6000 RTX 5090.

model-releasesr-localllama

Four Tesla V100s from 2017 matched my RTX 5090 on single-request Qwen 3.8 decode. Repo: https://github.com/dnv2003/v100-skinny https://i.redd.it/5ws2ak3uqckh1.gif The 5090 was not being held back. It

Ornith-1.5 (397B [DeepSWE 56], 35B-A3B, 9B)

model-releasesr-localllama

PDDL-ART: Autonomous Symbolic Abstraction From Demonstration For Long-Horizon Robotic Manipulation Using Vision-Language Models

arXiv:2608.17146v1 Announce Type: new Abstract: Symbolic planning with PDDL offers a principled framework for long-horizon robot manipulation, but constructing accurate PDDL domain and problem descrip

agentsarxiv-cs-ro

Policy-Invariant Reward Shaping from LLM Feedback: A Framework for Hybrid RL Agents

arXiv:2608.18008v1 Announce Type: cross Abstract: Combining large language models with reinforcement learning is increasingly explored, yet the theoretical status of LLM-derived reward signals is ofte

safetyarxiv-cs-ai

Position: Fairness Failure in Generative Models is an Evaluation Problem

arXiv:2608.16974v1 Announce Type: cross Abstract: Despite groundbreaking advancements in generative models during the last decade, concerns about their lack of fairness, reinforcing societal inequalit

safetyarxiv-cs-ai

PTXBench: Benchmark and Adapt LLMs for GPU Kernel Optimization with Architecture-specific PTX

arXiv:2608.17379v1 Announce Type: cross Abstract: We introduce PTXBench, a benchmark for evaluating and adapting large language models (LLMs) to use architecture-specific PTX for GPU kernel optimizati

Recirculation

arXiv:2608.17981v1 Announce Type: new Abstract: We describe an inference-time architectural enhancement for off-the-shelf foundation models that markedly reduces perplexity and boosts accuracy across

researcharxiv-cs-lg

Reinforcing Consistency in Video MLLMs with Structured Rewards

arXiv:2604.01460v2 Announce Type: replace Abstract: Multimodal large language models (MLLMs) have achieved remarkable progress in video understanding. However, seemingly plausible outputs often suffer

safetyarxiv-cs-cv

Replit Free Mode, powered by @OpenAI GPT-5.6 Luna. Let’s make intelligence accessible to everyone.

Replit has introduced a free mode powered by OpenAI’s GPT‑5.6 Luna model, announced on 19 August 2026. The service offers real‑time AI assistance for coding and collaboration at no cost, aiming to bro

model-releasesopenai--x

SCENARIODIFF: A Scenario-level Guidance Framework for Multimodal Time Series Forecasting--Extended Version

model-releasesarxiv-cs-lg

arXiv:2608.17164v1 Announce Type: new Abstract: Textual context such as news, reports, and logs can provide valuable signals for time series forecasting, especially when future dynamics are driven by

SeqFeed: Improving Agentic RTL Code Generation with Sequential Behavior Feedback

arXiv:2608.16934v1 Announce Type: cross Abstract: RTL code generation is a critical stage in hardware design, and the emergence of agentic systems offers new opportunities to automate this process. To

agentsarxiv-cs-cl

Serverless Apache Spark on Google Cloud: Architecture Choices & AI Troubleshooting

model-releasesgoogle-cloud-ai

In modern enterprise data engineering, Apache Spark remains a cornerstone framework for processing massive datasets at scale. However, managing infrastructure such as provisioning clusters, tuning YAR

Local Ai

SGHA: Evidence-Grounded Research Problem Discovery with Local Language Models

arXiv:2608.17501v1 Announce Type: new Abstract: Recent efforts toward fully automated AI scientists have demonstrated that language-model agents can generate hypotheses, execute experiments, and draft

local-aiarxiv-cs-ai

TiMi: Empower Time Series Transformers with Multimodal Mixture of Experts

arXiv:2602.21693v2 Announce Type: replace Abstract: Multimodal time series forecasting has garnered significant attention for its potential to provide more accurate predictions than traditional single

safetyarxiv-cs-lg

TokEval: A Tokenizer Evaluation Suite

arXiv:2608.18062v1 Announce Type: new Abstract: Language model tokenizers are typically selected with minimal evaluation, despite the fact that their design choices directly impact model capabilities.

safetyarxiv-cs-cl

Toward Personal Intelligence Through Cooperative Observation

arXiv:2608.17128v1 Announce Type: new Abstract: A personal AI system needs a model of the user's goals, constraints, and ongoing commitments to plan and act on their behalf, and the quality of that mo

researcharxiv-cs-ai

Towards Unified World Models for Visual Navigation via Memory-Augmented Planning and Foresight

arXiv:2510.08713v3 Announce Type: replace Abstract: Enabling embodied agents to imagine future states is essential for robust and generalizable visual navigation. Yet, state-of-the-art systems typical

researcharxiv-cs-ai

Uncertainty-Aware Decision Making in Multimodal Large Language Models

arXiv:2608.17084v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) increasingly answer questions whose correctness depends on visual, textual, temporal, acoustic, document, chart

safetyarxiv-cs-cl