Search: “inference”

ViBE: Co-Optimizing Workload Skew and Hardware Variability for MoE Serving

arXiv:2606.00735v1 Announce Type: cross Abstract: In distributed Mixture-of-Experts (MoE) inference, input-dependent token routing interacts with GPU performance variability to create persistent strag

hardwarearxiv-cs-lg

2 Jun 2026

Tutorials

Video Reasoning without Training

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DGX agent

arXiv:2510.17045v2 Announce Type: replace-cross Abstract: Video reasoning using Large Multimodal Models (LMMs) relies on costly reinforcement learning (RL) and verbose chain-of-thought, resulting in s

tutorialsarxiv-cs-ai

2 Jun 2026

Active Timepoint Selection for Learning Measure-Valued Trajectories

arXiv:2605.30625v1 Announce Type: cross Abstract: Inferring continuous probability paths from sparse snapshots is a fundamental challenge in domains like single-cell biology, where high-fidelity data

safetyarxiv-cs-ai

Consolidating Rewarded Perturbations for LLM Post-Training

arXiv:2605.31494v1 Announce Type: new Abstract: Post-training of language models is commonly framed as a sample-score-update loop implemented by gradient descent. A recent line of work, exemplified by

Early Prediction of Future Behavioral Strategy from Process Traces

arXiv:2605.30550v1 Announce Type: new Abstract: Adaptive systems often need to make task-specific decisions about people from limited evidence: a tutor may need to anticipate how a learner will approa

Efficient Diffusion LLMs via Temporal-Spatial Parallel Decoding and Confidence Extrapolation

arXiv:2605.30753v1 Announce Type: new Abstract: Diffusion-based large language models (dLLMs) support parallel text generation via iterative denoising, yet inference remains latency-heavy because many

Local Ai

Graph Energy Matching: Transport-Aligned Energy-Based Modeling for Graph Generation

arXiv:2603.23398v2 Announce Type: replace-cross Abstract: Generative modeling of discrete data, such as graphs, underpins many scientific and industrial applications, including molecular discovery and

local-aiarxiv-cs-ai

HypoSpace: A Diagnostic Benchmark for Set-Valued Hypothesis Generation under Underdetermination and Sublinear Coverage Bounds

model-releasesarxiv-cs-cl

arXiv:2510.15614v3 Announce Type: replace Abstract: Many scientific problems are underdetermined: multiple distinct hypotheses are equally consistent with the same observations. In such settings, effe

IAPO: Information-Aware Policy Optimization for Token-Efficient Reasoning

arXiv:2602.19049v2 Announce Type: replace Abstract: Large language models increasingly rely on long chains of thought to improve accuracy, yet such gains come with substantial inference-time costs. We

safetyarxiv-cs-cl

idSCD: Identifying Training Datasets through Semantic Correlation Descriptors

arXiv:2605.30462v1 Announce Type: cross Abstract: Can a dataset be recognized from the spurious correlations it induces during training? We argue that datasets leave dataset-specific traces in a model

LVSA: Training-Free Sparse Attention for Long Video Diffusion

arXiv:2605.31057v1 Announce Type: new Abstract: Dense self-attention is the compute and quality bottleneck of long-video diffusion inference: cost grows quadratically with the sequence length, and bey

safetyarxiv-cs-cv

Applications

OrcaRouter: A Production-Oriented LLM Router with Hybrid Offline-Online Learning

arXiv:2605.30736v1 Announce Type: cross Abstract: The rapid development of large language models, each with distinct capabilities and inference costs, raises a practical deployment question: given an

applicationsarxiv-cs-ai

ParisKV: Fast and Drift-Robust KV-Cache Retrieval for Long-Context LLMs

arXiv:2602.07721v3 Announce Type: replace-cross Abstract: KV-cache retrieval is essential for long-context LLM inference, yet existing methods struggle with distribution drift and high latency at scal

hardwarearxiv-cs-cl

Physics-informed Goal-Conditioned Reinforcement Learning under Hybrid Contact Dynamics

arXiv:2605.30503v1 Announce Type: new Abstract: Learning to reach arbitrary goals from sparse feedback requires agents to infer a rich notion of reachability across state--goal pairs. Goal-conditioned

researcharxiv-cs-ro

Tutorials

Robust Dreamer: Deviation-Aware Latent Gaussian Memory for Action-Controlled AR Video Generation

arXiv:2605.30855v1 Announce Type: new Abstract: Frame-wise action-controlled image-to-video generation is a promising paradigm for interactive world simulation, where each control signal should elicit

tutorialsarxiv-cs-cv

Speculative Decoding Across Languages

arXiv:2605.30580v1 Announce Type: new Abstract: Speculative decoding has become a crucial component of large language model (LLM) inference, enabling faster generation by drafting multiple tokens and

Speculative Pipeline Decoding: Higher-Accruacy and Zero-Bubble Speculation via Pipeline Parallelism

arXiv:2605.30852v1 Announce Type: new Abstract: Speculative Decoding (SD) accelerates low-concurrency LLM inference by employing a draft-then-verify paradigm. However, mainstream methods typically rel

Applications

VisionPulse: Dynamic Visual Sparsity for Efficient Multimodal Reasoning

arXiv:2605.31457v1 Announce Type: new Abstract: With the rapid advancement of large multimodal models (LMMs), inference-time overhead has become a key bottleneck for real-world deployment. Existing me

applicationsarxiv-cs-cv

VolFill: Single-View Amodal 3D Scene Reconstruction with Volumetric Flow Matching

arXiv:2605.31466v1 Announce Type: new Abstract: Reconstructing the complete geometry of a scene from a single RGB image remains challenging - especially when inferring hidden structures where visual e

researcharxiv-cs-cv

Attention as In-Context Empirical Bayes: A Two-Stage View via Particle Dynamics

arXiv:2605.29351v1 Announce Type: new Abstract: We study minimal attention-only transformers under all-token corruption and show they admit a two-stage empirical Bayes interpretation. A single attenti

DFlash: Block Diffusion for Flash Speculative Decoding

arXiv:2602.06036v2 Announce Type: replace Abstract: Autoregressive large language models (LLMs) deliver strong performance but require inherently sequential decoding, leading to high inference latency

hardwarearxiv-cs-cl

DLM-SWAI: Steering Diffusion Language Models Before They Unmask

arXiv:2605.29626v1 Announce Type: cross Abstract: Steering language model generation toward desired textual properties is essential for practical deployment, and inference-time methods are particularl

safetyarxiv-cs-ai

Domino: Decoupling Causal Modeling from Autoregressive Drafting in Speculative Decoding

arXiv:2605.29707v1 Announce Type: new Abstract: Speculative decoding accelerates LLM inference by drafting multiple tokens and verifying them in parallel with the target model. However, its practical

EVADE: LLM-Based Explanation Generation and Validation for Error Detection in NLI

arXiv:2511.08949v2 Announce Type: replace Abstract: High-quality datasets are critical for training and evaluating reliable NLP models. In tasks like natural language inference (NLI), human label vari

Improved Guarantees for Heterogeneous Treatment-Effect Estimation via Matrix Completion

arXiv:2605.30319v1 Announce Type: cross Abstract: A central goal of modern causal inference is estimating heterogeneous treatment effects to answer questions like 'how does an intervention affect each

MARS Policy: Multimodality Only When It Matters

arXiv:2605.29766v1 Announce Type: new Abstract: Imitation learning has become a cornerstone for solving complex robotic manipulation tasks. In particular, multimodality, which enables robots to captur

safetyarxiv-cs-ro

MemoSight: Unifying Context Compression and Multi Token Prediction for Reasoning Acceleration

arXiv:2604.14889v2 Announce Type: replace Abstract: While chain-of-thought (CoT) reasoning enables LLMs to solve challenging reasoning tasks, the linear growth of the KV cache leads to substantial mem

Applications

PARCEL: Pool-Anchored Resampling with Conditioned Elastic Queries for Efficient Vision-Language Understanding

arXiv:2605.30126v1 Announce Type: cross Abstract: Large Vision-Language Models (LVLMs) map visual inputs into dense token sequences, imposing a quadratic computational bottleneck for inference. Elasti

applicationsarxiv-cs-ai

Rare Event Analysis of Large Language Models

arXiv:2602.06791v2 Announce Type: replace Abstract: Being probabilistic models, during inference large language models (LLMs) display rare events: behaviour that is far from typical but highly signifi

Rethinking Stepwise Model Routing: A Cost-Efficient Table Reasoning Perspective

arXiv:2605.29319v1 Announce Type: new Abstract: Large Reasoning Models (LRMs) achieve strong performance on table reasoning tasks but incur substantial inference cost due to long reasoning traces. Ste

SGMD: Score Gradient Matching Distillation for Few-Step Video Diffusion Distillation

arXiv:2605.30116v1 Announce Type: new Abstract: Distribution Matching Distillation (DMD) is a widely used paradigm for accelerating inference in few-step video diffusion models. However, DMD-style vid

safetyarxiv-cs-cv

Toward User Preference Alignment in LLM Recommendation via Explicit Context Feedback

arXiv:2605.29141v1 Announce Type: cross Abstract: Traditional recommender systems (RecSys) primarily infer user preferences from implicit signals (such as clicks, watches, and purchases), often neglec

safetyarxiv-cs-ai

A Conflict-Aware Penalty and Statistical Loss Framework for Balancing Modalities and Enhancing Stability in Multimodal Sentiment Analysis

arXiv:2605.28575v1 Announce Type: new Abstract: Multimodal Sentiment Analysis (MSA) fuses text, acoustic, and visual streams to infer sentiment. Because pre-trained text encoders are far more expressi

Agentic Separation Logic Specification Synthesis

model-releasesarxiv-cs-cl

arXiv:2605.27531v1 Announce Type: cross Abstract: Specification synthesis, the task of automatically inferring formal specifications from program implementations and natural language, is important for

CIRF: Tokenizing Chain-of-Thoughts into Reusable Functional Units for Efficient Latent Reasoning in Large Language Models

arXiv:2605.28292v1 Announce Type: new Abstract: Implicit Chain-of-Thought (CoT) reduces the inference cost of large language models by internalizing the explicit rationales. However, existing approach

safetyarxiv-cs-cl

EvoSpec: Evolving Speculative Decoding via Real-Time Vocabulary and Parameter AdaptationTarget

model-releasesarxiv-cs-ai

arXiv:2605.27390v1 Announce Type: cross Abstract: Speculative decoding accelerates Large Language Model inference via a draft-then-verify paradigm, yet the output projection layer becomes a bottleneck

Agents

Extrapolative Weight Averaging Reveals Correctness-Efficiency Frontiers in Code RL

arXiv:2605.28751v1 Announce Type: cross Abstract: Linear interpolation between fine-tuned checkpoints has been shown to trace the Pareto front between competing objectives, but whether extrapolative w

agentsarxiv-cs-ai

HiRQA: Hierarchical Ranking and Quality Alignment for Opinion-Unaware Image Quality Assessment

arXiv:2508.15130v2 Announce Type: replace Abstract: Despite significant progress in no-reference image quality assessment (NR-IQA), dataset biases and reliance on subjective labels continue to hinder

safetyarxiv-cs-cv

Learning Compositional Latent Structure with Vector Networks

model-releasesarxiv-cs-ai

arXiv:2605.28007v1 Announce Type: cross Abstract: Deep networks are powerful function approximators, but they typically store many different computations in shared weight matrices, making it difficult

Linear Causal Representation Learning by Topological Ordering, Pruning, and Disentanglement

arXiv:2509.22553v2 Announce Type: replace-cross Abstract: Causal representation learning (CRL) has garnered increasing interest from the causal inference and artificial intelligence communities due to

Long Live the Librarian! A Persistent Search Sub-Agent for Energy-Efficient Multi-Agent Software Engineering Systems

arXiv:2605.27787v1 Announce Type: cross Abstract: Multi-agent systems (MAS) have substantially advanced autonomous software engineering (SWE), but their growing inference energy demands raise sustaina

hardwarearxiv-cs-cl

MaskClaw: Edge-Side Personalized Privacy Arbitration for GUI Agents with Behavior-Driven Skill Evolution

model-releasesarxiv-cs-cl

arXiv:2605.28646v1 Announce Type: cross Abstract: GUI agents rely on screenshots to infer intent and operate across applications, but these screenshots often contain private messages, medical records,

Not All NVFP4 QAT Recipes Are Equal: How Architecture and Scale Shape Model Quality for Anomaly Segmentation

arXiv:2605.27616v1 Announce Type: cross Abstract: Real-time anomaly segmentation demands both high recall and efficient low-precision inference. We study the three-way interaction of model architectur

PEAM: Parametric Embodied Agent Memory through Contrastive Internalization of Experience in Minecraft

model-releasesarxiv-cs-ai

arXiv:2605.27762v1 Announce Type: new Abstract: We present PEAM, a Parametric Embodied Agent Memory framework in Minecraft that transforms agent memory from inference-time retrieval into parameter-res

Reflective Dialogue between Teacher and Solver Agents for Video Question Answering

model-releasesarxiv-cs-cv

arXiv:2605.27885v1 Announce Type: new Abstract: Various approaches have been proposed to adapt Vision-Language Models (VLMs) to specialized domains for Video Question Answering, including fine-tuning

Rethinking Calibration for Early-Exit Neural Networks

arXiv:2508.21495v3 Announce Type: replace Abstract: Early-exit neural networks (EENNs) accelerate inference by allowing intermediate classifiers to stop computation once predictions are confident enou

Robust Moment-Based Estimation via Spectral Gradient Reweighting

model-releasesarxiv-cs-lg

arXiv:2605.27718v1 Announce Type: cross Abstract: Moment-based estimation is a theoretically attractive approach to parametric inference, especially when likelihood-based estimation is unavailable, mi

Agents

Segment to Focus: Guiding Latent Action Models in the Presence of Distractors

arXiv:2602.02259v2 Announce Type: replace-cross Abstract: Latent action models (LAMs) offer a promising path to pre-training embodied agents on large amounts of action-free video. They infer latent ac

agentsarxiv-cs-cv