Search: “inference”

Brief Announcement: Generative Markov Model for Distributed Computing Systems

arXiv:2606.03061v1 Announce Type: cross Abstract: Emerging distributed computing paradigms, such as the computing continuum, are inherently heterogeneous, stochastic, and complex. Efficiently and effe

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Coherence Maximization Improves Pluralistic Alignment

DGX agent

arXiv:2606.03110v1 Announce Type: new Abstract: Aligning AI systems with diverse human values requires value specifications grounded in concrete examples, but generating such examples without extensiv

safetyarxiv-cs-cl

3 Jun 2026

Cost-Aware Query Routing in RAG: Empirical Analysis of Retrieval Depth Tradeoffs

arXiv:2606.02581v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) faces a fundamental three-way tension: deeper retrieval improves factual grounding but inflates token costs and e

DMT-CBT: Longitudinal Therapeutic State Modeling for CBT Counseling

arXiv:2606.03132v1 Announce Type: new Abstract: Large language models (LLMs) have shown growing potential for Cognitive Behavioral Therapy (CBT) counseling. However, most existing approaches still for

local-aiarxiv-cs-cl

Estimating Bidirectional Causal Effects with Large Scale Online Kernel Learning

arXiv:2511.05050v3 Announce Type: replace-cross Abstract: In this study, a scalable online kernel learning framework is proposed for estimating bidirectional causal effects in systems characterized by

safetyarxiv-cs-lg

Evaluating Transformer and LSTM Frameworks for Prediction in Ungauged Basins

arXiv:2606.02791v1 Announce Type: new Abstract: Watershed networks exhibit convergent topologies in which multiple tributaries merge into downstream channels,integrating diverse upstream hydrological

Agents

FutureWeaver: Planning Test-Time Compute for Multi-Agent Systems with Modularized Collaboration

arXiv:2512.11213v2 Announce Type: replace Abstract: Scaling test-time computation has been shown to significantly improve large language model (LLM) performance without additional training. However, e

agentsarxiv-cs-ai

GeoSem-WAM: Geometry- and Semantic-Aware World Action Models

arXiv:2606.03188v1 Announce Type: new Abstract: Recent World Action Models (WAMs) have demonstrated impressive capabilities in embodied decision-making. However, whether their effectiveness stems from

researcharxiv-cs-ro

HybridThinker: Efficient Chain-of-Thought Reasoning via Compressed Memory and Transient Thought Steps

arXiv:2606.03768v1 Announce Type: new Abstract: Extended chain-of-thought (CoT) traces improve LLM reasoning but incur substantial computational and memory costs. While existing CoT compression method

researcharxiv-cs-cl

Imaginative Perception Tokens Enhance Spatial Reasoning in Multimodal Language Models

arXiv:2606.03988v1 Announce Type: new Abstract: Vision language models (VLMs) excel at many tasks but still struggle with spatial reasoning when critical information is not directly observable. Many s

researcharxiv-cs-ai

LiveBand: Live Accompaniment Generation in the Audio Domain

arXiv:2606.03803v1 Announce Type: cross Abstract: We present LiveBand, a real-time system that generates high-fidelity music accompaniments to live audio input, respecting strict causal constraints. O

Tools

M3 brings sparse attention + 1M context + multimodality, and Together did the hard serving work to make it fast. Great collaboration with th…

Anthropic's Claude 3.5 Sonnet (M3) model features sparse attention mechanisms, 1 million token context length, and multimodal capabilities, with Together AI optimizing the serving infrastructure to en

toolstogether-ai--x

OMP: One-step Meanflow Policy with Directional Alignment

arXiv:2512.19347v3 Announce Type: replace Abstract: Robot manipulation has increasingly adopted data-driven generative policy frameworks, yet the field faces a persistent trade-off: diffusion models s

safetyarxiv-cs-ro

Perceive Before Reasoning: A Pre-Reasoning Perception Framework for Efficient and Reliable Proactive Mobile Agents

arXiv:2606.03236v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have substantially advanced mobile agents, yet proactive mobile assistance remains challenging because agents m

Post-Hoc Robustness for Model-Based Reinforcement Learning

arXiv:2606.03521v1 Announce Type: cross Abstract: To improve the real-world applicability of reinforcement learning (RL), the field of adversarially robust RL studies how to train agents under adversa

R2DN: Scalable Parameterization of Contracting and Lipschitz Recurrent Deep Networks

arXiv:2504.01250v2 Announce Type: replace Abstract: This paper presents the Robust Recurrent Deep Network (R2DN), a scalable parameterization of robust recurrent neural networks for machine learning a

Revisiting Embodied Chain-of-Thought for Generalizable Robot Manipulation

model-releasesarxiv-cs-ro

arXiv:2606.03784v1 Announce Type: new Abstract: Embodied chain-of-thought (CoT) aims to bridge linguistic reasoning and robotic control, but its effective form and integration strategy remain underexp

Scalable Derivative Gaussian Processes via Exact Gradient Reduction

arXiv:2606.02909v1 Announce Type: cross Abstract: Gradient observations can substantially improve Gaussian process (GP) surrogates, particularly in high-dimensional settings where function evaluations

local-aiarxiv-cs-lg

Social Caption: Evaluating Social Understanding in Multimodal Models

arXiv:2601.14569v2 Announce Type: replace Abstract: Social understanding abilities are crucial for multimodal large language models (MLLMs) to interpret human social interactions. We introduce SOCIAL

researcharxiv-cs-cl

TGV-KV: Text-Grounded KV Eviction for Vision-Language Models

arXiv:2606.03075v1 Announce Type: new Abstract: Vision-Language Models (VLMs) inherit the auto-regressive generation paradigm and cache the keys and values (KV) of all previous tokens to accelerate in

safetyarxiv-cs-cv

VLESA: Vision-Language Embodied Safety Agent for Human Activity Monitoring

model-releasesarxiv-cs-cv

arXiv:2606.03954v1 Announce Type: new Abstract: As AI systems increasingly assist humans in physical tasks, ensuring safety becomes paramount -- physical actions carry immediate and irreversible conse

21cmEMUv3: a hybrid diffusion-LSTM emulator of 21cmFAST summary observables

arXiv:2606.00219v1 Announce Type: cross Abstract: We are witnessing a surge in observations of the cosmic dawn (CD) and epoch of reionisation (EoR), driving an increasing demand for fast and robust th

A Systematic Benchmark of Intraoperative Ultrasound-to-MR Synthesis for Brain Tumour Surgery

model-releasesarxiv-cs-cv

arXiv:2606.00630v1 Announce Type: new Abstract: Intraoperative ultrasound (ioUS) is a versatile, cost-effective modality in brain tumour surgery, but its interpretation is difficult: acquisition plane

Adaptive Time Series Reasoning via Segment Selection

arXiv:2602.18645v2 Announce Type: replace Abstract: Time series reasoning tasks often start with a natural language question and require targeted analysis of a time series. Evidence may span the full

safetyarxiv-cs-lg

AutoMedBench: Towards Medical AutoResearch with Agentic AI Models

arXiv:2606.01961v1 Announce Type: new Abstract: Autonomous agents are increasingly expected to support end-to-end medical-AI research workflows, moving beyond isolated prediction tasks or short-form c

b9466

local-aillama-cpp-releases

B9466 is a build release in the llama.cpp project that includes fixes and improvements to speculative decoding functionality, specifically addressing n_outputs_max issues and extracting helper functio

b9467

local-aillama-cpp-releases

The search results show recent llama.cpp releases but do not contain specific information about release b9467. Based on the context of llama.cpp releases and the GitHub repository structure, b9467 is

Coarse-to-Fine Compositional Diffusion for Long-Horizon Planning

arXiv:2606.00837v1 Announce Type: cross Abstract: Diffusion models provide strong priors for generating structured data, but many tasks require outputs beyond the scale on which these models are typic

local-aiarxiv-cs-lg

Connecting the Dots: Benchmarking Reflective Memory in Long-Horizon Dialogue

arXiv:2606.01223v1 Announce Type: cross Abstract: Despite substantial progress in long-context modeling, existing benchmarks remain confined to factual memory for explicit recall, failing to measure t

Counterfactual Intervention Feature Transfer for Visible-Infrared Person Re-identification

arXiv:2208.00967v4 Announce Type: replace Abstract: Graph-based models have achieved great success in person re-identification tasks recently, which compute the graph topology structure (affinities) a

researcharxiv-cs-cv

Agents

Critic-R: Improving Agentic Search using Instruction-tuned Retrievers with Natural Language Introspective Feedback

arXiv:2606.00590v1 Announce Type: cross Abstract: Agentic search systems iteratively interact with retrieval models to answer complex queries. Despite substantial progress, optimizing retrievers for a

agentsarxiv-cs-ai

Distribution-free changepoint localization after sequential change detection

arXiv:2606.01256v1 Announce Type: cross Abstract: This paper introduces a distribution-free framework for constructing post-detection confidence sets for changepoints after stopping a sequential chang

Tutorials

Efficient Hamiltonian, structure and trace distance learning of Gaussian states

arXiv:2411.03163v4 Announce Type: replace-cross Abstract: In this work, we initiate the study of Hamiltonian learning for positive temperature bosonic Gaussian states, the quantum generalization of th

tutorialsarxiv-cs-lg

Finding the Minimal Parameter Budget for Implicit Reasoning: A Data Complexity Driven Scaling Law for Language Models

arXiv:2504.03635v4 Announce Type: replace Abstract: Reasoning is a core capability of language models (LMs), yet it remains unclear how much model capacity is necessary to support reasoning during pre

Fixed-Mean Gaussian Processes for Post-hoc Bayesian Deep Learning

arXiv:2412.04177v2 Announce Type: replace Abstract: Recently, there has been an increasing interest in performing post-hoc uncertainty estimation about the predictions of pre-trained deep neural netwo

Heterogeneous Decentralized Diffusion Models

arXiv:2603.06741v2 Announce Type: replace-cross Abstract: Training frontier-scale diffusion models often requires substantial computational resources concentrated in tightly-coupled clusters, limiting

local-aiarxiv-cs-ai

Hierarchically Decoupled Mixture-of-Experts for Robust Traffic Sign Recognition in Complex Driving Scenarios

model-releasesarxiv-cs-cv

arXiv:2606.01822v1 Announce Type: new Abstract: Traffic sign detection is a fundamental component of environmental perception in autonomous driving and intelligent transportation systems. However, mos

IDLM: Inverse-distilled Diffusion Language Models

arXiv:2602.19066v2 Announce Type: replace-cross Abstract: Diffusion Language Models (DLMs) have recently achieved strong results in text generation. However, their multi-step sampling leads to slow in

researcharxiv-cs-ai

Applications

ImagineUAV: Aerial Vision-Language Navigation via World-Action Modeling and Kinodynamic Planning

arXiv:2606.01205v1 Announce Type: new Abstract: Vision-language navigation (VLN) for UAVs demands grounding free-form instructions into 6-DoF flight under partial observability. While Vision-Language-

applicationsarxiv-cs-ro

Applications

InfoAtlas: A Foundation Model for Zero-Shot Statistical Dependence Estimate

arXiv:2606.00241v1 Announce Type: cross Abstract: Measuring statistical dependency between high-dimensional random variables is a fundamental task in data science and machine learning. Neural mutual i

applicationsarxiv-cs-ai

InPhyRe Discovers: Large Multimodal Models Struggle in Inductive Physical Reasoning

arXiv:2509.12263v3 Announce Type: replace Abstract: Large multimodal models (LMMs) encode physical laws observed during training, such as momentum conservation, as parametric knowledge. It allows LMMs

Interventional Processes for Causal Uncertainty Quantification

arXiv:2410.14483v3 Announce Type: replace-cross Abstract: Reliable uncertainty quantification for causal effects is crucial in high-stakes applications, but remains challenging when the target is an e

LASER: Loss-Aware Singular-value Decomposition and Rank Allocation for Efficient Low-Precision Vision-Language Models

model-releasesarxiv-cs-lg

arXiv:2606.00573v1 Announce Type: new Abstract: Vision-language models (VLMs) deliver strong multimodal reasoning capabilities, but their large computational cost and high parameter counts make deploy

Limits of Resolution Equivariance in Fourier Neural Operators

arXiv:2606.00677v1 Announce Type: new Abstract: Fourier Neural Operators are often assumed to generalize across spatial resolutions, enabling training on a coarse grid and deployment on a finer grid.

MobEvolve: An Agentic Self-Evolving Heuristic System for Interpretable Human Mobility Generation

arXiv:2606.01640v1 Announce Type: new Abstract: Human mobility generation aims to synthesize realistic trip chains for target populations based on individual features. Existing paradigms, including de

Normalized Relevance Measure as a Unifying Framework to Explain Neural Network Latent Structures

arXiv:2606.00557v1 Announce Type: new Abstract: To understand how a neural network (NN) functions and makes predictions, it has become increasingly clear that analyzing only the input domain is insuff

OP-LoRA: The Blessing of Dimensionality

arXiv:2412.10362v2 Announce Type: replace-cross Abstract: Low-rank adapters (LoRA) enable finetuning of large models with only a small number of parameters. However, they often suffer from an ill-cond

researcharxiv-cs-cv

Optimizing Diversity and Quality through Base-Aligned Model Collaboration

arXiv:2511.05650v2 Announce Type: replace-cross Abstract: Alignment has greatly improved large language models (LLMs)' output quality at the cost of diversity, yielding highly similar outputs across g