Search: “inference”

The Silent Vote: Improving Zero-Shot LLM Reliability by Aggregating Semantic Neighborhoods

arXiv:2605.09739v1 Announce Type: cross Abstract: Large Language Models are increasingly used as zero-shot classifiers in complex reasoning tasks. However, standard constrained decoding suffers from a

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Thinking with Novel Views: A Systematic Analysis of Generative-Augmented Spatial Intelligence

DGX agent

arXiv:2605.10588v1 Announce Type: new Abstract: Current Large Multimodal Models (LMMs) struggle with spatial reasoning tasks requiring viewpoint-dependent understanding, largely because they are confi

researcharxiv-cs-cv

12 May 2026

TIDE-Bench: Task-Aware and Diagnostic Evaluation of Tool-Integrated Reasoning

arXiv:2605.09544v1 Announce Type: new Abstract: Tool-integrated reasoning has emerged as a promising paradigm for enhancing large language models with external computation, retrieval, and execution ca

Agents

TimeClaw: A Time-Series AI Agent with Exploratory Execution Learning

arXiv:2605.10038v1 Announce Type: new Abstract: Time series analysis underpins forecasting, monitoring, and decision making in domains such as finance and weather, where solving a task often requires

agentsarxiv-cs-ai

TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection

arXiv:2605.10756v1 Announce Type: new Abstract: Vision-language models enable OOD detection by comparing image alignment with ID labels and negative semantics. Existing negative-label-based methods ma

TinySSL: Distilled Self-Supervised Pretraining for Sub-Megabyte MCU Models

arXiv:2605.08241v1 Announce Type: cross Abstract: Self-supervised learning (SSL) has transformed representation learning for large models, yet remains unexplored for microcontroller (MCU)-class models

TodyComm: Task-Oriented Dynamic Communication for Multi-Round LLM-based Multi-Agent System

arXiv:2602.03688v2 Announce Type: replace Abstract: Multi-round LLM-based multi-agent systems rely on effective communication structures to support collaboration across rounds. However, most existing

TRACER: Verifiable Generative Provenance for Multimodal Tool-Using Agents

model-releasesarxiv-cs-cl

arXiv:2605.09934v1 Announce Type: new Abstract: Multimodal large language models increasingly solve vision-centric tasks by calling external tools for visual inspection, OCR, retrieval, calculation, a

TTCD:Transformer Integrated Temporal Causal Discovery from Non-Stationary Time Series Data

arXiv:2605.08111v1 Announce Type: cross Abstract: The widespread availability of complex time series data in various domains such as environmental science, epidemiology, and economics demands robust c

Universal Feature Selection with Noisy Observations and Weak Symmetry Conditions

arXiv:2605.09396v1 Announce Type: cross Abstract: This paper relaxes the restrictive symmetry conditions adopted in [4], [5] and extends their universal feature selection framework to accommodate nois

UPA: Unsupervised Prompt Agent via Tree-Based Search and Selection

arXiv:2601.23273v2 Announce Type: replace Abstract: Prompt agents have recently emerged as a promising paradigm for automated prompt optimization, framing prompt discovery as a sequential decision-mak

local-aiarxiv-cs-cl

Users as Annotators: LLM Preference Learning from Comparison Mode

arXiv:2510.13830v2 Announce Type: replace-cross Abstract: Pairwise preference data have played an important role in the alignment of large language models (LLMs). Each sample of such data consists of

VEGA: Visual Encoder Grounding Alignment for Spatially-Aware Vision-Language-Action Models

model-releasesarxiv-cs-ro

arXiv:2605.10485v1 Announce Type: new Abstract: Precise spatial reasoning is fundamental to robotic manipulation, yet the visual backbones of current vision-language-action (VLA) models are predominan

Verifiable Process Rewards for Agentic Reasoning

arXiv:2605.10325v1 Announce Type: new Abstract: Reinforcement learning from verifiable rewards (RLVR) has improved the reasoning abilities of large language models (LLMs), but most existing approaches

local-aiarxiv-cs-ai

VFM-SDM: A vision foundation model-based framework for training-free, marker-free, and calibration-free structural displacement measurement

arXiv:2605.09677v1 Announce Type: new Abstract: Reliable displacement measurement is fundamental for structural health monitoring and digital engineering workflows, as it provides direct structural re

Agents

ViSRA: A Video-based Spatial Reasoning Agent for Multi-modal Large Language Models

arXiv:2605.10106v1 Announce Type: cross Abstract: Recent advances in Multi-modal Large Language Models (MLLMs) target 3D spatial intelligence, yet the progress has been largely driven by post-training

agentsarxiv-cs-ai

WavesFM: Hierarchical Representation Learning for Longitudinal Wearable Sensor Waveforms

arXiv:2605.09173v1 Announce Type: cross Abstract: Wearable sensors enable the continuous acquisition of high-resolution physiological waveforms, such as photoplethysmography and accelerometry, under f

local-aiarxiv-cs-ai

Weighted Rules under the Stable Model Semantics

arXiv:2605.09519v1 Announce Type: new Abstract: We introduce the concept of weighted rules under the stable model semantics following the log-linear models of Markov Logic. This provides versatile met

what is happening with ollama cloud from last 2 days?

Recent posts on the r/ollama subreddit discuss Ollama Cloud service issues, with the platform experiencing request errors while handling demand and working to scale infrastructure further . Ollama Clo

local-air-ollama

When a Robot is More Capable than a Human: Learning from Constrained Demonstrators

arXiv:2510.09096v3 Announce Type: replace-cross Abstract: Learning from demonstrations enables experts to teach robots complex tasks using interfaces such as kinesthetic teaching, joystick control, an

When Attention Beats Fourier: Multi-Scale Transformers for PDE Solving on Irregular Domains

arXiv:2605.08318v1 Announce Type: cross Abstract: We study the problem of architecture selection for deep learning models trained to solve partial differential equations (PDEs), asking when transforme

When Language Overwrites Vision: Over-Alignment and Geometric Debiasing in Vision-Language Models

arXiv:2605.08245v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) increasingly power high-stakes applications, from medical imaging to autonomous systems, yet they routinely hallucinate,

Tutorials

When Large Vision-Language Models Meet Person Re-Identification

arXiv:2411.18111v2 Announce Type: replace Abstract: Large Vision-Language Models (LVLMs) that incorporate visual models and large language models have achieved impressive results across cross-modal un

tutorialsarxiv-cs-cv

When Reviews Disagree: Fine-Grained Contradiction Analysis in Scientific Peer Reviews

arXiv:2605.10171v1 Announce Type: cross Abstract: Scientific peer reviews frequently contain conflicting expert judgments, and the increasing scale of conference submissions makes it challenging for A

When Tables Leak: Attacking String Memorization in LLM-Based Tabular Data Generation

arXiv:2512.08875v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have recently demonstrated remarkable performance in generating high-quality tabular synthetic data. In practice,

When to Trust Imagination: Adaptive Action Execution for World Action Models

arXiv:2605.06222v2 Announce Type: replace-cross Abstract: World Action Models (WAMs) have recently emerged as a promising paradigm for robotic manipulation by jointly predicting future visual observat

Where Reliability Lives in Vision-Language Models: A Mechanistic Study of Attention, Hidden States, and Causal Circuits

arXiv:2605.08200v1 Announce Type: new Abstract: A pervasive intuition holds that vision-language models (VLMs) are most trustworthy when their attention maps look sharp: concentrated attention on the

XPERT: Expert Knowledge Transfer for Effective Training of Language Models

arXiv:2605.08842v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) language models organize knowledge into explicitly routed expert modules, making expert-level representations traceable and ana

researcharxiv-cs-cl

+1 to this. I was recently on a cross-continental flight without wifi, so I brought up Qwen3.6 & Gemma 4 (via @ollama) in Deep Agents on my …

model-releasesharrison-chase--x

+1 to this. I was recently on a cross-continental flight without wifi, so I brought up Qwen3.6 & Gemma 4 (via @ollama) in Deep Agents on my laptop. admittedly, they fell over on some more involved/com

A Causal Diffusion Model for Video Reconstruction from Ultra-Low-Bitrate Representations

arXiv:2602.13837v2 Announce Type: replace Abstract: We study video reconstruction from ultra-low-bitrate representations, where the primary challenge shifts from encoding to decoding. In this regime,

A lot of people are being deliberately obtuse about this tweet. Would it help if I said 'theory' instead of 'idea'? Because it would still m…

researchfrancois-chollet--x

A lot of people are being deliberately obtuse about this tweet. Would it help if I said 'theory' instead of 'idea'? Because it would still mean the exact same. FYI reading comprehension is about inter

A Unified and Controllable Framework for Layered Image Generation with Visual Effects

arXiv:2601.15507v2 Announce Type: replace Abstract: Recent image generation models produce impressive composites, but often fail to preserve the identity of user-provided content when editing specific

Active Embodiment Identification with Reinforcement Learning for Legged Robots

arXiv:2605.08020v1 Announce Type: new Abstract: We present an active embodiment identification method for legged robots that jointly learns information-seeking behavior and explicit embodiment predict

researcharxiv-cs-ro

AgentEscapeBench: Evaluating Out-of-Domain Tool-Grounded Reasoning in LLM Agents

arXiv:2605.07926v1 Announce Type: new Abstract: As LLM-based agents increasingly rely on external tools, it is important to evaluate their ability to sustain tool-grounded reasoning beyond familiar wo

Architecting a resilient, scalable and secure foundation for the agentic era

model-releasesgoogle-cloud-ai

Across the public sector, the conversation has shifted; we are no longer just talking about the potential of AI, we are already seeing the impact. While visionary leadership and cultural buy-in are cr

Arrow: A Foundation Model for Causal Discovery

arXiv:2605.07204v1 Announce Type: new Abstract: We introduce Arrow, a foundation model for zero-shot causal discovery on observational tabular data. Arrow factorizes a directed acyclic graph into an u

ART for Diffusion Sampling: A Reinforcement Learning Approach to Timestep Schedule

arXiv:2601.18681v2 Announce Type: replace-cross Abstract: We consider time discretization for score-based diffusion models to generate samples from a learned reverse-time dynamic on a finite grid. Uni

Asymptotically Log-Optimal Bayes-Assisted Confidence Sequences for Bounded Means

arXiv:2605.07964v1 Announce Type: cross Abstract: Confidence sequences based on test martingales provide time-uniform uncertainty quantification for the mean of bounded IID observations without parame

Applications

AT-VLA: Adaptive Tactile Injection for Enhanced Feedback Reaction in Vision-Language-Action Models

arXiv:2605.07308v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have significantly advanced the capabilities of robotic agents in executing diverse tasks; however, they still face

applicationsarxiv-cs-ro

b9110

local-aillama-cpp-releases

The search results show recent llama.cpp releases and general information but don't contain specific details about the b9110 release. Based on the search patterns and similar recent releases documente

Agents

Belief Memory: Agent Memory Under Partial Observability

arXiv:2605.05583v2 Announce Type: replace Abstract: LLM agents that operate over long context depend on external memory to accumulate knowledge over time. However, existing methods typically store eac

agentsarxiv-cs-ai

Beyond 'I cannot fulfill this request': Alleviating Rigid Rejection in LLMs via Label Enhancement

arXiv:2605.07883v1 Announce Type: new Abstract: Large Language Models (LLMs) rely on safety alignment to obey safe requests while refusing harmful ones. However, traditional refusal mechanisms often l

safetyarxiv-cs-cl

Beyond Reasoning: Reinforcement Learning Unlocks Parametric Knowledge in LLMs

arXiv:2605.07153v1 Announce Type: new Abstract: Reinforcement learning (RL) has achieved remarkable success in LLM reasoning, but whether it can also improve direct recall of parametric knowledge rema

researcharxiv-cs-cl

Beyond the Black Box: Interpretability of Agentic AI Tool Use

arXiv:2605.06890v1 Announce Type: new Abstract: AI agents are promising for high-stakes enterprise workflows, but dependable deployment remains limited because tool-use failures are difficult to diagn

BoHA: Blockwise Hadamard Product Adaptation for Parameter-Efficient Fine-Tuning

model-releasesarxiv-cs-lg

arXiv:2509.21637v2 Announce Type: replace Abstract: Parameter-efficient fine-tuning (PEFT) of large language models trains a small task-specific parameter set while keeping the pretrained model frozen

Breaking the Illusion: When Positive Meets Negative in Multimodal Decoding

arXiv:2605.06679v1 Announce Type: new Abstract: Vision-Language Models (VLMs) are frequently undermined by object hallucination, generating content that contradicts visual reality, due to an over-reli

Applications

Causal-Aware Foundation-Model for Bilevel Optimization in Discrete Choice Settings

arXiv:2605.06941v1 Announce Type: new Abstract: We introduce a causal aware foundation-model framework for real time optimal decision making in discrete choice environments. We propose a constrained t

applicationsarxiv-cs-lg

Causal EpiNets: Precision-corrected Bounds on Individual Treatment Effects using Epistemic Neural Networks

arXiv:2605.07065v1 Announce Type: cross Abstract: Individual treatment effects are not point-identified from data. The Probability of Necessity and Sufficiency (PNS) circumvents this limitation by cha