Search: “reasoning”

From Caveman to Expert Analyst: Energy Consumption of Variable LLM Tasks

arXiv:2608.12350v1 Announce Type: cross Abstract: The energy demand growth and environmental impacts of artificial intelligence (AI) have generated substantial interest in supplying sufficient low-cos

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HybridRAG-BN: A Retrieval-Augmented Framework with Fine-Tuned Verification for Bangla KBQA

DGX agent

arXiv:2608.13004v1 Announce Type: new Abstract: Knowledge-base question answering (KBQA) systems rely on effective retrieval and reasoning mechanisms to generate accurate answers from external knowled

model-releasesarxiv-cs-cl

14 Aug 2026

Large Language Models Persuade Without Planning Theory of Mind

arXiv:2602.17045v2 Announce Type: replace Abstract: A growing body of work attempts to evaluate the theory of mind (ToM) abilities of humans and large language models (LLMs) using static, non-interact

safetyarxiv-cs-cl

Learning Latency-Aware Orchestration for Multi-Agent Systems

arXiv:2601.10560v2 Announce Type: replace-cross Abstract: Multi-agent systems (MAS) coordinate multiple LLM-powered agents through structured workflows, gaining reasoning power but incurring high infe

agentsarxiv-cs-ai

Tutorials

New Terms, New Toxicity: Consensus-based Chinese Neologism Toxicity Detection via Search-Augmented LLMs

arXiv:2608.12361v1 Announce Type: new Abstract: Neologisms, emerging terms in meaning or form, can serve as new vehicles for toxic expression, like 'country girl' as a stigmatizing label targeting fem

tutorialsarxiv-cs-cl

RippleMem: From Isolated Retrieval to Associative Recollection for Long-Term Agent Memory

arXiv:2608.13334v1 Announce Type: new Abstract: LLM-based agents increasingly rely on external memory to support long-horizon reasoning and interaction. However, the main bottleneck is not simply stor

agentsarxiv-cs-cl

Scaling Representation Diversity: Modulated Attention and Reconstructive Regularization for Visual Grounding

arXiv:2608.12748v1 Announce Type: new Abstract: Referring Expression Comprehension (REC) is commonly studied under dataset-specific fine-tuning, resulting in specialist models with limited cross-datas

Training and Benchmarking Code Generation for Physics-Inspired Animations

arXiv:2602.10840v2 Announce Type: replace Abstract: Large language models (LLMs) have been widely studied in areas such as mathematical reasoning, complex coding, and scientific problem solving. Howev

researcharxiv-cs-lg

v0.32.11

model-releasesollama-releases

What's Changed launch: add Muse Code integration by @dhiltgen in #17594 model/renderers: match Muse Glimmer reasoning template by @dhiltgen in #17732 launch: add DeepSeek Harness integration by @Parth

A great read if you an AI dev. Current context compactors retain 17% of the standing rules users give them. Session Constraints are instruct…

A great read if you an AI dev. Current context compactors retain 17% of the standing rules users give them. Session Constraints are instructions like 'do not delete any emails until I confirm' that bi

agentsdair-ai--x

AgenticTwin: An Agentic LLM Framework Integrated with Digital Twin for Anomaly Detection

arXiv:2608.11679v1 Announce Type: new Abstract: Digital twins are increasingly used to monitor and simulate the behavior of cyber-physical systems. Even with skilled operators, interpreting anomalies

AI4AI at Test-Time: Strong-to-Weak Capability Transfer via Harnesses

arXiv:2608.12307v1 Announce Type: cross Abstract: Recent work on distillation transfers the capabilities of large models to smaller ones often by updating the latter's parameters, through teacher forc

anthropic’s best hope is that OpenAI falls apart. which it might.

anthropic’s best hope is that OpenAI falls apart. which it might. NEW from Ramp AI Index: disappointing adoption of Fable 5 We've heard several reasons from businesses...mainly Fable 5 is just too exp

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AWARe: Mitigating Catastrophic Forgetting via Activation-Weighted Adaptive REtention

model-releasesarxiv-cs-cl

arXiv:2608.11758v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) exhibit strong generalization and reasoning abilities due to large-scale multimodal pre-training. However, fine

Grok 4.6 ranks #1 on the GPQA Diamond leaderboard 🧠 Grok 4.6 (high) scores 95% - the highest score on the chart for graduate-level scientif…

model-releaseselon-musk--x

Grok 4.6 ranks #1 on the GPQA Diamond leaderboard 🧠 Grok 4.6 (high) scores 95% - the highest score on the chart for graduate-level scientific reasoning It outperforms Claude Fable 5, Opus 5, GPT-5.6 S

GRPO for Financial Advice Generation: Outperforming Commercial LLMs under CATE Evaluation

arXiv:2608.11787v1 Announce Type: cross Abstract: Generating actionable financial advice from business records demands that models integrate numerical reasoning, domain knowledge, and sound judgment,

safetyarxiv-cs-ai

Inverse Theory of Mind Modeling for Content Recommendation: From Web Browsing to Dynamic Intelligent Interfaces

arXiv:2608.11354v1 Announce Type: new Abstract: Modern recommender systems treat observed actions as reliable proxies for user preferences, yet interactions often reflect exploration or comparison rat

safetyarxiv-cs-ai

MaSRead: Content-Addressed Reading of Replicated Latent Stores

arXiv:2608.11218v1 Announce Type: new Abstract: Independent agents that reason in latent space can share computed state as key-value cache fragments rather than text. Merged by a conflict-free replica

PAIR: Pairwise-Aware Inclusion Reweighting for Adaptive Rollout Allocation in RLVR

arXiv:2608.11368v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) spends most of its compute generating groups of long reasoning trajectories. Recent allocators red

safetyarxiv-cs-lg

Proportional Analogies on Probability Distributions via Bayesian Updating

arXiv:2608.11724v1 Announce Type: new Abstract: Analogies are quaternary relations of the form 'A is to B as C is to D'. Among the various formalizations of analogical reasoning, proportional analogie

SAG: SQL-Retrieval Augmented Generation with Query-Time Dynamic Hyperedges

model-releasesarxiv-cs-cl

arXiv:2608.12129v1 Announce Type: new Abstract: While retrieval-augmented generation (RAG) has proven effective at giving LLMs access to external knowledge, mainstream dense-retrieval implementations

Self-evolving network verifiers

arXiv:2608.11340v1 Announce Type: cross Abstract: Symbolic network verifiers can reason about correctness across vast spaces of routing inputs and failures, but only for the protocols and features an

agentsarxiv-cs-ai

The top 10% of enterprises use plugins twice as often and skills six times as often as typical firms. These frontier firms are not ahead by …

According to a Twitter post by OpenAI on August 13, 2026, the top 10% of enterprises adopt AI plugins twice as frequently and leverage skills—such as model‐based knowledge and reasoning—six times more

model-releasesopenai--x

Local Ai

UniGround: Universal 3D Visual Grounding via Training-Free Scene Parsing

arXiv:2603.08131v2 Announce Type: replace-cross Abstract: 3D Visual Grounding (3DVG) localizes objects from natural-language descriptions in 3D scenes and is fundamental to embodied AI applications. A

local-aiarxiv-cs-cv

Benchmarking LLM-Guided Control-Plane Policies for Backend Fault Isolation in HAProxy

model-releasesarxiv-cs-lg

arXiv:2608.10532v1 Announce Type: cross Abstract: Static load balancers cannot mitigate a backend that is degraded rather than down: round-robin and least-connections keep routing traffic to a server

CapProbe: Evaluating Detailed Image Captions via Full-Scene Dense Question Answering

arXiv:2608.11074v1 Announce Type: new Abstract: Evaluating detailed image captions from Vision-Language Models (VLMs) requires going beyond surface-level semantic similarity. Reference-based metrics (

Chartography: A Benchmark for Professional Chart Understanding

arXiv:2608.10677v1 Announce Type: new Abstract: Professionals across medicine, engineering, finance, manufacturing, and the sciences often make consequential decisions from charts. Existing chart benc

Decodable But Not Detachable: Training Data Granularity Determines Parametric Modularity in Large Language Models

arXiv:2608.10214v1 Announce Type: new Abstract: Do large language models contain domain-specific parametric shells: concentrated, causally necessary neuron populations whose removal selectively degrad

Detecting an Effect Is Not Learning to Act on It: A Reward-SNR Floor for LLM Acquisition Agents

arXiv:2608.10441v1 Announce Type: cross Abstract: Many pipelines can pay a per-example cost to acquire an auxiliary, model-derived observation -- an LLM's structured reasoning, a slow oracle, an expen

safetyarxiv-cs-cl

DriveVLA-M0: Failure-Aware Memory Augmentation for Autonomous Driving

arXiv:2608.10413v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have recently emerged as a promising paradigm for end-to-end autonomous driving by enabling unified reasoning across

Efficient Reinforcement Learning for Long-Horizon Tool-Use Agentic Tasks

arXiv:2608.10357v1 Announce Type: cross Abstract: Long-horizon tool-using agents must reason over user goals, domain policies, tool calls, simulator state, and delayed verifiable rewards. Reinforcemen

HoosierHelp: Benchmarking LLM Agents for Social Service Navigation

arXiv:2608.09946v1 Announce Type: cross Abstract: Social service navigation requires connecting help-seeking individuals to resources that satisfy their needs and specific constraints. Although LLM ag

MERA: Model Evolution and Routing with Skill Adaptation for Agentic Systems at Scale

arXiv:2608.10333v1 Announce Type: new Abstract: LLM agents execute heterogeneous sequences of model calls within a single task: some invocations require careful reasoning, while others are structured

safetyarxiv-cs-lg

Multi-Granular Rationale-Guided Molecular LLM for Property Prediction

arXiv:2608.10480v1 Announce Type: new Abstract: Large language models (LLMs) are widely applied across chemical tasks, such as molecular property prediction, which underpins drug discovery. Molecular

Muse Glimmer is live on Fireworks. The new open-weight model from Meta Superintelligence Labs is a 30B dense model built for always-on agent…

Muse Glimmer is live on Fireworks. The new open-weight model from Meta Superintelligence Labs is a 30B dense model built for always-on agents that reason across many sequential tool calls and can reco

agentsfireworks-ai--x

Patients With Personality: Realistic Patient Simulation through Controlled Diversity and Selective Disclosure

arXiv:2606.17441v2 Announce Type: replace-cross Abstract: Simulating realistic patient interactions is a key requirement to testing clinical applications of LLMs at scale without time-consuming and ex

Post-Hoc Sparse Coding of Latent Communication Between Vision-Language Model Agents

arXiv:2608.10198v1 Announce Type: new Abstract: Latent-space communication allows heterogeneous vision-language model agents to exchange continuous representations without serializing visual and reaso

Predicting Space Groups of Double Perovskites by LLM with Dynamic Few-Shot Learning

arXiv:2608.10483v1 Announce Type: new Abstract: Double perovskites (DPs) offer broad compositional tunability, but predicting the space groups (SGs) of stable structures remains difficult because avai

safetyarxiv-cs-ai

Local Ai

RAG for regular users?

One of the reasons I got into local LLMs was the possibility of getting answers using my own documents and books (a few hundreds) instead of having to search through them manually. However since I'm n

local-air-localllama

REDAgentBench: Executable Red Teaming and Faithful Measurement of LLM Agent Systems

arXiv:2608.10669v1 Announce Type: new Abstract: Large language model (LLM) agents combine language-based reasoning with external tools to perform complex tasks. Adversarial inputs can exploit interact

Self-Correcting Long-Horizon Search Agents via Tree-Structured Memory

arXiv:2608.10676v1 Announce Type: new Abstract: Large language model (LLM)-based search agents answer questions through multi-step interactions with external environments. However, providing complete

sLTN: Structural Logic Tensor Networks

arXiv:2608.11136v1 Announce Type: new Abstract: Logic Tensor Networks (LTN) provide a neurosymbolic framework in which first-order logic is interpreted through tensor operations, enabling logical cons

Local Ai

UniProbe: A Learnable Token-Level Hallucination Detector for Large VLMs using Multi-Structural Internal Representations

arXiv:2608.10835v1 Announce Type: new Abstract: Large Vision-Language Models (LVLMs) achieve impressive visual reasoning and dialogue capabilities, yet frequently hallucinate content unsupported by th

local-aiarxiv-cs-cv

1 Day in and I feel okay saying Muse-Glimmer-30B finally beats 3.6-27B for the size in some use-cases

model-releasesr-localllama

A few things right off the bat: it reasons very efficiently. Like Grok 4.5 levels of efficient thinking it quantizes very well. My first few tests with iq3_xxs were better than Qwen/Gemma behaved at t

AdaDINO: Pair-Aware In-Backbone Adaptation of Frozen DINO for Efficient Remote Sensing Change Detection

arXiv:2608.07982v1 Announce Type: new Abstract: Vision foundation models (VFMs) such as DINO are pretrained for single-image representation, whereas remote sensing change detection requires reasoning

An Agentic Generative Large Language Model for Treatment Planning of Colorectal Cancer

arXiv:2608.09142v1 Announce Type: new Abstract: Treatment planning in precision oncology requires synthesizing heterogeneous patient information with rapidly evolving clinical guidelines to ensure gui

safetyarxiv-cs-cl

Beyond Global Editing: Per-Instance Disentangled Subspaces for Training-Free Hallucination Mitigation in LVLMs

arXiv:2608.09344v1 Announce Type: new Abstract: Recent advances in large vision-language models (LVLMs) have enabled powerful multimodal reasoning by integrating visual encoders with large language mo

researcharxiv-cs-cv

Can Open-Weight Models Compete on Financial Text Comprehension?

arXiv:2608.08634v1 Announce Type: new Abstract: Open-weight language models from Chinese AI labs caught up on benchmarks relative to proprietary frontier models in recent months. Yet their reliability