Search: “inference”

Adaptive Self-Consistency: From Black-Box Sampling to Distribution-Valued Feedback

arXiv:2609.38931v1 Announce Type: cross Abstract: Self-consistency samples many reasoning trajectories and aggregates their final answers, treating the LLM as a black box that returns one answer per t

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AIMS: An Agentic AI Framework for Sim-to-Real Multi-Modal ISAC

DGX agent

arXiv:2609.39964v1 Announce Type: new Abstract: Multi-modal integrated sensing and communication (ISAC) enables environmental perception and reliable connectivity for intelligent wireless networks. Da

model-releasesarxiv-cs-ai

1 Oct 2026

Aligned Data Can Induce Misalignment via Context Confusion

arXiv:2609.38379v1 Announce Type: new Abstract: Large language models (LLMs) are frequently updated for various use cases, where filtering out misaligned training samples is a common practice for prev

Alignment via Training Against Probes Without Losing Monitorability

arXiv:2609.38645v1 Announce Type: cross Abstract: Models are usually aligned based on their observed outputs, using demonstrations, preference data, or reward signals. These objectives reward response

Amortized Data Borrowing with Exchangeability-Aware Neural Posterior Estimation

arXiv:2609.38902v1 Announce Type: new Abstract: Augmenting small concurrent studies with external or historical cohorts is attractive in drug development, where enrollment is slow, follow-up is expens

safetyarxiv-cs-lg

An Empirical Study of On-Device Translation for Real-Time Live-Stream Chat on Mobile Devices

arXiv:2601.02641v2 Announce Type: replace Abstract: Despite its efficiency, there has been little research on the practical aspects required for real-world deployment of on-device AI models, such as t

Approval Laundering: Systematizing Approval--Execution Binding Failures in AI Coding-Agent Harnesses

arXiv:2609.38983v1 Announce Type: cross Abstract: Modern AI coding-agent harnesses (Claude Code, Codex CLI, Cursor) rest their security boundary on a largely unexamined assumption: that the action A a

Argument Structure Prediction in Online Conversations: A Comparative Study of Modeling Paradigms and Task Architectures

arXiv:2609.39225v1 Announce Type: new Abstract: Argument structure prediction (ASP) constructs complete argument structures from discourse by identifying argumentative units and their relations. While

Atomic and Holistic LLM Judges for Reference-Grounded Support Labels: A Prompt-Controlled Comparison

arXiv:2603.28005v2 Announce Type: replace Abstract: When an LLM judge only has to assign a three-way support label to a candidate answer given a reference, does asking it to decompose the answer into

Local Ai

Atomizer-IO: Beyond Pixels, Patches and Grids

arXiv:2609.40320v1 Announce Type: new Abstract: Most vision architectures assume that observations lie on a regular grid, an effective abstraction for natural images but a restrictive one for sensing

local-aiarxiv-cs-cv

Auditing Agent Actions through Query-Conditioned Attribution

arXiv:2609.33676v2 Announce Type: replace Abstract: LLM agents increasingly take consequential actions through interactions with users, policies, and external tools. Auditing these agents requires aut

BAM! Bayesian Anything Model: a foundation model for generative computational imaging

model-releasesarxiv-cs-cv

arXiv:2609.39660v1 Announce Type: new Abstract: Generative models are transforming Bayesian computational imaging, yet the field still lacks physics-aware foundation models. Current practice falls int

Better Supervision Is Nearby: Neighborhood On-Policy Self-Distillation

arXiv:2609.39687v1 Announce Type: new Abstract: On-policy self-distillation (OPSD) trains mathematical reasoning models using a privileged teacher that sees a reference solution and supervises student

Beyond Spatial-Domain Supervision: A Relation Constrained Space for Multi-Modal Image Fusion

arXiv:2609.38968v1 Announce Type: new Abstract: Multi-modal image fusion (MMIF) aims to form a single image by integrating shared information, preserving complementary cues, and coordinating cross-mod

Beyond the Remembered World: Predictive 4D Belief for Persistent Navigation in Evolving Worlds

arXiv:2609.39166v1 Announce Type: new Abstract: Persistent spatial memory enables embodied agents to navigate familiar environments across repeated visits. However, targets may move while unobserved,

Breaking Babel: A Self-Evolving Multi-Agent System for Long-Form Subtitle Translation

arXiv:2609.38660v1 Announce Type: cross Abstract: Long-form subtitle translation requires reasoning over discourse and cultural context spanning episodes or entire series, while maintaining consistent

Budget Boundary Effects in Test-Time Mathematical Reasoning

arXiv:2609.38699v1 Announce Type: new Abstract: A cumulative token cap can fall inside a mathematical derivation, forcing a test-time controller to choose between stopping at the cap (strict) and allo

CADeT: Causal-Aware Deformation Transmission for Indirect Robotic Manipulation of Soft Tissue

arXiv:2609.38483v1 Announce Type: new Abstract: Indirect manipulation of deep-seated deformable anatomy inaccessible to the robot is challenging in robot-assisted minimally invasive surgery (RAMIS) be

researcharxiv-cs-ro

CARAT: Do Materials LLMs Reason or Recite?

arXiv:2609.38340v1 Announce Type: new Abstract: When a materials LLM answers a question about crystal structure, does it reason from the structure or copy an answer already printed in its input? Accur

Agents

Characterizing High Bandwidth Flash for LLM Serving

arXiv:2609.39131v1 Announce Type: new Abstract: Large language model (LLM) serving requires substantial memory to store model weights and KV caches. As models grow larger and contexts become longer, m

agentsarxiv-cs-lg

ChunkTrust: Adapting Execution Horizons for Robot Policies with Action-Expert Evidence

arXiv:2609.39754v1 Announce Type: new Abstract: Robot foundation policies predict action chunks, but how many actions to execute before replanning depends on the current task phase. We introduce Chunk

safetyarxiv-cs-ro

Code to Control: Synthesizing Parameterized Reactive Controllers

arXiv:2609.38733v1 Announce Type: new Abstract: Recent LLM-based approaches to control either invoke a language model to select actions or synthesize world models that require planning at every decisi

Comparison of techniques for fine-tuning open-weight models for entity extraction from radiology reports

arXiv:2609.40236v1 Announce Type: new Abstract: Converting free-text radiology reports into structured labels supports cohort building, quality assurance, and monitoring of clinical imaging models, bu

Local Ai

Component-Aware Feedback for Self-Evolving Programs

arXiv:2609.38639v1 Announce Type: new Abstract: LLM-guided evolutionary search can discover complex programs, but existing methods mostly only save candidate programs and fitness scores while discardi

local-aiarxiv-cs-ai

Concept-Grounded Attention: A Controlled Evaluation of Graph-Injected Attention, Temporal Versioning, and Epistemic Status

arXiv:2609.38684v1 Announce Type: new Abstract: Knowledge-intensive language-model systems typically represent external knowledge as text chunks or static graphs, with limited support for concept evol

Consistent Plan-Act for Long-Horizon Agentic Tasks

arXiv:2609.38891v1 Announce Type: new Abstract: Long-horizon agentic tasks demand strong reasoning and efficient execution across successive interactions with dynamic environments. A common approach d

Tutorials

CoVisco: Codec-Native Vision Encoder with Native Token Compression for Unified Image-Video Understanding

arXiv:2609.39924v1 Announce Type: cross Abstract: Vision-language models face a fundamental scaling bottleneck: the number of visual tokens grows with both temporal duration and spatial resolution, ma

tutorialsarxiv-cs-ai

Cue the Flow: Steering Flow-Matching Policies for Open-World Delivery Manipulation

arXiv:2609.38989v1 Announce Type: new Abstract: Open-world goods delivery requires mobile manipulators to follow free-form user instructions and manipulate potentially novel objects. Existing dual-sys

safetyarxiv-cs-ro

DataFlex: A Unified Framework for Data-Centric Dynamic Training of Large Language Models

arXiv:2603.26164v2 Announce Type: replace-cross Abstract: Data-centric training has emerged as a promising direction for improving large language models (LLMs) by optimizing not only model parameters

DeCoPrune: Efficient KV-Cache Pruning for Autoregressive Video Diffusion via Denoising Consistency

model-releasesarxiv-cs-cv

arXiv:2609.39096v1 Announce Type: new Abstract: Autoregressive video diffusion supports streaming generation and interactive control, but its KV cache grows with the generated history. Existing compre

Tutorials

Decoupling Multi-Contrast Super-Resolution: Self-Supervised Implicit Re-Representation for Unpaired Cross-Modal Synthesis

arXiv:2505.05855v4 Announce Type: replace Abstract: Multi-contrast super-resolution (MCSR) is crucial for enhancing MRI but current deep learning methods are limited. They typically require large, pai

tutorialsarxiv-cs-cv

Delta-K: Boosting Multi-Instance Generation via Cross-Attention Augmentation

arXiv:2603.10210v2 Announce Type: replace-cross Abstract: While Diffusion Models excel in text-to-image synthesis, they frequently suffer from catastrophic concept omission when generating complex mul

Diffusion-2BC: Hybrid Diffusion and Regression Training for Offline Behavior Cloning in Autonomous Driving

model-releasesarxiv-cs-lg

arXiv:2609.38472v1 Announce Type: cross Abstract: Behavior cloning provides an offline route to autonomous-driving policy learning, but mean-squared-error regression is poorly matched to demonstration

Discrete Forcing: Infusing Discrete Guidance into Continuous Denoising for Few-Step Action Experts

model-releasesarxiv-cs-ro

arXiv:2609.39526v1 Announce Type: new Abstract: Efficient action generation in vision-language-action (VLA) models requires capturing both coarse action structure and fine-grained details. Discrete ac

Don't Inoculate Everything: Stratified Inoculation Prompting Narrows Backdoor Triggers and Preserves Desired Traits

arXiv:2609.35356v2 Announce Type: replace Abstract: Supervised fine-tuning can teach language models undesired behaviours alongside desired ones. Inoculation prompting (IP) aims to limit unwanted gene

DrivingBench: Can Vision-Language Models Drive a Toyota Corolla?

arXiv:2609.38948v1 Announce Type: cross Abstract: Frontier models excel at many digital benchmarks, yet their ability to drive a real car, an everyday human skill, remains largely untested. We present

Dynamic LoRA-Experts and Prototype-Ensemble Matching for Class-Incremental Learning

model-releasesarxiv-cs-lg

arXiv:2609.39839v1 Announce Type: new Abstract: Class-Incremental Learning (CIL) aims to continuously learn new classes without forgetting previously acquired knowledge. Parameter-efficient fine-tunin

ECHO-G: Embodied Co-speech Humanoid mOtion Generation

arXiv:2609.39575v1 Announce Type: cross Abstract: Generating full-body co-speech motion for humanoid robots requires coordinating speech prosody, linguistic content, and embodiment-specific motion. To

Efficient Multi-Modal Planning with Reward-Guided Preference Optimization for Autonomous Driving

arXiv:2609.38862v1 Announce Type: cross Abstract: Safe and efficient trajectory planning is essential in autonomous driving. However, existing end-to-end approaches often fall short in both computatio

Embedding Physical Reasoning into Diffusion-Based Shadow Generation Under the Sun and Sky

arXiv:2512.06174v3 Announce Type: replace Abstract: Generating realistic cast shadows for inserted foreground objects requires reasoning about scene geometry and illumination. However, most learning-b

researcharxiv-cs-cv

Enhancing Autoregressive Video Generation via Representation Adversarial Distillation

arXiv:2609.40037v1 Announce Type: new Abstract: Few-step autoregressive video generation enables efficient streaming synthesis, but errors introduced in early temporal blocks are reused as context and

Evaluating Persistent Calibration under Evolving Model Knowledge

arXiv:2609.38797v1 Announce Type: cross Abstract: As AI systems move from static repositories to agents that are capable of continual adaptation and learning, maintaining their trustworthiness means e

ExploreNet: Learning Where to Explore in Diffusion GRPO

arXiv:2609.38329v1 Announce Type: new Abstract: Group-relative RL methods such as Flow-GRPO post-train image generators by exploring with isotropic Gaussian noise added at every denoising step. This n

FORTE: Forecasting Occupancy for Spatiotemporal Risk-Aware Planning in Dynamic Environments

arXiv:2609.39305v1 Announce Type: new Abstract: Safe navigation in dynamic environments requires anticipating future environmental states to account for spatiotemporal risks, specifically when and whe

researcharxiv-cs-ro

FrameMorrow: Future-guided Frame Selection with Prospective Tokens for Long-Horizon Video Generation

arXiv:2609.38839v1 Announce Type: new Abstract: Long-horizon video generation requires models to effectively leverage an increasingly long generation history. As the generated history grows, retaining

Function-Space Transformer with Adaptive Anchors

arXiv:2609.38348v1 Announce Type: new Abstract: Many forms of data, including physical fields, geometric shapes, and visual signals, are naturally described by functions over continuous domains but ar

researcharxiv-cs-lg

Geometry-physics confounding impairs PDE learning across varying domains

arXiv:2609.38623v1 Announce Type: new Abstract: Learning partial differential equation (PDE) dynamics across varying domains is central to predictive modelling and data-driven discovery of governing e

researcharxiv-cs-lg

Hardware

Gestalt: a meta-foundation model for astronomy

arXiv:2609.38312v1 Announce Type: cross Abstract: The Platonic Representation Hypothesis predicts that sufficiently scaled foundation models converge on a shared representation of the world. As each n

hardwarearxiv-cs-lg