Search: “context”

PreSO: Privileged Representation Isolation for On-Policy Self-Distillation

arXiv:2610.14001v1 Announce Type: new Abstract: On-policy self-distillation (OPSD) uses a self-teacher conditioned on privileged information to turn the sparse outcome signal of reinforcement learning

safetyarxiv-cs-lg

Applications

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Proactive Physical AI through Continuous Observation and Timely Intervention

DGX agent

arXiv:2610.16967v1 Announce Type: new Abstract: Physical AI is commonly formulated around an explicitly specified task: given a goal or instruction, a system perceives, reasons, and acts. In many real

applicationsarxiv-cs-cv

14 Oct 2026

ProMoDD: Dataset Distillation for 3D Human Motion via Prototype-Conditioned Diffusion Models

arXiv:2610.16134v1 Announce Type: new Abstract: Dataset distillation (DD) aims to retain the training utility of a large dataset in a much smaller set of examples. For skeleton-based action recognitio

PTGPO: Prefix Tree Group Policy Optimization

arXiv:2610.14737v1 Announce Type: new Abstract: Training language agents on long-horizon interactive tasks is challenging because sparse terminal rewards provide weak credit signals for intermediate a

safetyarxiv-cs-lg

PVFH-Bench: Benchmarking Premise-Induced Visual Fixation Hallucinations in Vision-Language Models

arXiv:2610.14635v1 Announce Type: cross Abstract: Large Vision-Language Models (LVLMs) have achieved remarkable progress across a wide range of multimodal tasks. However, object hallucination remains

Query-Adaptive Neuron Steering for LLMs

arXiv:2610.14519v1 Announce Type: new Abstract: Effectively eliciting the capabilities of large language models (LLMs) at inference time remains an important challenge. Existing studies address this c

Relational Learning as World Modeling

arXiv:2610.16763v1 Announce Type: new Abstract: Relational learning typically predicts from a database state, but decision making asks a different question: how will that state change under an action?

SAFE-KV: Causal Suffix Repair for Behavior-Preserving Non-Prefix KV Cache Reuse in RAG

arXiv:2610.15186v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) reuses the same documents across many requests, making non-prefix KV-cache reuse attractive. Yet a cached documen

researcharxiv-cs-lg

Silence and Noise: Resolving Suppression and Overvaluation in Multimodal Entity Alignment

arXiv:2610.16106v1 Announce Type: new Abstract: Multimodal entity alignment (MMEA) is fundamental to integrating heterogeneous knowledge graphs (KGs), yet existing paradigms remain critically vulnerab

safetyarxiv-cs-lg

Skin Tone in the Wild: A Dataset and Benchmark for 10-tone MST Classification

arXiv:2603.02475v2 Announce Type: replace Abstract: Skin tone classification is a fundamental task in computer vision, with applications in quantifying medical features, assessing demographic represen

SPARE: Shared Perception and Adaptive Retrieval of Evidence for Streaming Video Understanding

arXiv:2610.14671v1 Announce Type: new Abstract: Streaming video understanding requires answering questions from the observed video, with evidence drawn from recent observations or earlier events. Hist

SWORD: Scene-Grounded Wasserstein Object-Relation Distance for 3D Scene Graph Prediction

arXiv:2610.17692v1 Announce Type: new Abstract: 3D scene graph prediction is commonly optimized with object-node and relation-edge classification losses. These objectives encourage exact object and re

TETRIS-4DGS: Efficient Post-Training Compression of 4D Gaussian Splatting

arXiv:2610.14663v1 Announce Type: new Abstract: 4D Gaussian Splatting (4DGS) has emerged as a powerful dynamic scene representation, supporting real-time high quality rendering but suffers from prohib

Text-Guided Medical Image Segmentation via Residual Aggregation and Dense Alignment Representations

arXiv:2610.14944v1 Announce Type: new Abstract: Specifying segmentation targets with natural language provides flexible semantic conditioning for medical image segmentation. However, existing methods

The Language of Looking: Motion Tokens Reveal Domain-Dependent Local Structure in Gaze Sequences

arXiv:2610.16565v1 Announce Type: new Abstract: Human gaze is the primary high-bandwidth interface through which we parse the semantics of our environment. While often modeled as a sequence, the degre

researcharxiv-cs-lg

UniLAP: A Unified Latent Action Policy for Cross-Embodiment Manipulation

arXiv:2610.16969v1 Announce Type: cross Abstract: Latent Action Models (LAMs) can capture manipulation priors from action-free videos, but discrete latents usually impose a granularity bottleneck, lim

VL-DocIR: A Benchmark for Vision-Based Long Document Information Retrieval

arXiv:2610.17057v1 Announce Type: cross Abstract: Vision-based document retrieval has improved rapidly, but current evaluation settings still emphasize short documents and single relevant pages. This

What Survives When Activation Steering Is Used as Memory

arXiv:2610.14958v1 Announce Type: cross Abstract: Activation steering has recently been used as a memory for skills: past experiences of an agent are stored as steering vectors and retrieved later. Fa

agentsarxiv-cs-lg

Hardware

When Log Parsing Removes What Matters: Detecting Failures in Distributed GPU Workloads

arXiv:2610.14009v1 Announce Type: new Abstract: Large AI models increasingly rely on distributed GPU execution, yet it remains unclear whether established failure analysis methods transfer effectively

hardwarearxiv-cs-lg

When Trackers Fail: VLM-Guided Verification and Recovery for Robust Video Object Segmentation

arXiv:2610.15929v1 Announce Type: new Abstract: Recent trackers built on foundation models such as the Segment Anything Model (SAM) achieve strong performance by propagating object masks through memor

agentsarxiv-cs-cv

WorkRover: Scaling Long-Horizon Cowork Agent Training Via Recursive Environment Evolution

arXiv:2610.18067v1 Announce Type: cross Abstract: Scaling interactive environments is important for training long-horizon agents through reinforcement learning. These environments often require furthe

agentsarxiv-cs-lg

AMLworld-Compact: Importance-Weighted Downsampling for Cost-Effective LLM Evaluation and Error Diagnosis

arXiv:2610.13627v1 Announce Type: new Abstract: Evaluating large language models (LLMs) on AMLworld's smallest test splits is costly because each of over a million targets requires a separate graph pr

An Input-Dependent Readout Phase for Resonant Sequence Models

arXiv:2610.12496v1 Announce Type: cross Abstract: Sequence models with a fixed-size state avoid the quadratic cost of attention, but face a design choice. An input-dependent state transition gives con

Behind-the-Meter Photovoltaic Visibility from Net Smart Meters: Deployment Regimes and Operational Insights

arXiv:2610.12527v1 Announce Type: new Abstract: Distribution operators need visibility of behind-the-meter photovoltaic (PV) generation, yet most residential customers are observed only through net sm

Beyond the Final Embedding: Retrieving Memories from Token-Level Evidence

arXiv:2610.13277v1 Announce Type: cross Abstract: Memory-augmented assistants retrieve evidence from stored conversations and documents to answer queries. Most embedding-based retrievers compare singl

local-aiarxiv-cs-cl

Collaborative Theory of Mind: Learning to Self-Revise by Anticipating User Responses

arXiv:2610.12872v1 Announce Type: new Abstract: Large language models (LLMs) demonstrate strong individual task performance, yet still struggle to collaborate with users over extended, multi-turn inte

safetyarxiv-cs-ai

Continually Post-training Small Models via Synthetic Self-distillation

arXiv:2610.13113v1 Announce Type: cross Abstract: Continual post-training faces a dual challenge of acquisition and retention: models must learn new capabilities while preserving prior knowledge. Whil

local-aiarxiv-cs-ai

DeltaLLM: Delta-Key Sparse Attention for Edge LLMs

arXiv:2507.19608v2 Announce Type: replace Abstract: On-device LLM inference is increasingly important for edge platforms but remains challenging due to high computational and memory demands and tight

local-aiarxiv-cs-ai

Applications

Discovering Phase Space Structure in Learned Hamiltonian Systems

arXiv:2509.23003v3 Announce Type: replace-cross Abstract: Mechanics-inspired neural dynamical models improve interpretability and physical consistency, but they usually assume a known configuration sp

applicationsarxiv-cs-ai

Faithful and Complete LLM-Assisted Automated Construction of Hierarchical Hardware Knowledge Graphs

model-releasesarxiv-cs-ai

arXiv:2610.12762v1 Announce Type: new Abstract: Hardware datasheets contain engineering specifications essential for component selection, system integration, and hardware compatibility verification. H

Forecasting Corpus-Sampling Disagreement in Masked Text Reconstruction

arXiv:2610.12987v1 Announce Type: new Abstract: If a second text corpus were collected from the same population, how much would a predictor's outputs change? We study this question for masked-text rec

researcharxiv-cs-cl

Know What You Don't Know: Agentic Data Synthesis by Evolving Generation Space for Closed-Loop Learning

arXiv:2610.12593v1 Announce Type: new Abstract: The continued improvement of large language models increasingly depends on synthetic experience, yet effective data synthesis for interactive agents req

agentsarxiv-cs-ai

Les Miserables Dialogue: A film-based network representation of social communication

arXiv:2610.13148v1 Announce Type: cross Abstract: In this work, we revisit the classic Les Miserables benchmark network from the perspective of social communication. Using the 1998 film adaptation of

Oido: Open-Vocabulary Speech Recognition on a $5 Microcontroller without a Neural Accelerator

arXiv:2610.13447v1 Announce Type: cross Abstract: Speech recognition on low-cost microcontrollers is, in practice, limited to keyword spotting or a fixed list of commands. We present Oido, an inferenc

PACT: Privileged Trace Co-Training for Multi-Turn Tool-Use Agents

arXiv:2606.16215v2 Announce Type: replace-cross Abstract: Multi-turn tool-use agents must reason, call tools, and adapt to observations across several interaction turns. Post-training such agents is c

agentsarxiv-cs-ai

Hardware

RAMP: Recurrent Adaptive Mixed Precision for Efficient Prefill in Recurrent-Depth Language Models

arXiv:2610.13041v1 Announce Type: new Abstract: Recurrent-depth language models improve inference-time reasoning by repeatedly applying a shared network to refine internal representations, but the add

hardwarearxiv-cs-cl

Realism VS Accuracy: Event Sequence Forecasting from a Generative Modeling Perspective

arXiv:2610.12586v1 Announce Type: new Abstract: Event sequences are chains of random events, each described by heterogeneous (numerical and categorical) features. The problem of event sequence forecas

Revisiting Tabular Deep Regression: Objectives and the Limits of Global Early Stopping

arXiv:2610.13909v1 Announce Type: cross Abstract: While deep learning models for tabular data have recently received significant research attention, the choice of objective functions for regression ta

researcharxiv-cs-ai

Scaling RNA Foundation Models through Iterative Refinement

arXiv:2610.13106v1 Announce Type: new Abstract: Biological function in RNA is encoded across scales, from local sequence motifs to long-range structural dependencies. Conventional RNA foundation model

SpireBench: Evaluating Long-Horizon Strategic Play of Agentic Models with Slay the Spire

model-releasesarxiv-cs-ai

arXiv:2610.12596v1 Announce Type: new Abstract: Agentic large language models now tackle complex tasks, yet strategic reasoning over long horizons is under-studied: most agentic benchmarks are short a

Structural Automata for Neural Semantic Parsing

arXiv:2610.13896v1 Announce Type: new Abstract: Neural semantic parsers generate meaning representations token by token, yet well-formedness depends on references, scope, and graph relations that unfo

local-aiarxiv-cs-cl

Test-Time Memory Construction

arXiv:2610.13348v1 Announce Type: new Abstract: Large Language Models (LLMs) struggle to answer questions over long interaction histories, where relevant evidence may be scattered across distant sessi

researcharxiv-cs-cl

Tracing and Taming Hallucinated Terms via Subsequence-Association Filtering and Breadth-Aware Selection for LLM Query Expansion

arXiv:2610.13810v1 Announce Type: cross Abstract: Large language models (LLMs) are now a standard source of query expansion terms but they hallucinate. They inject non existent entities and off-topic

safetyarxiv-cs-cl

Trainable Quantum-Native Language Models: Dissipative Memory, Capacity Limits, and Hardware Validation

arXiv:2610.12806v1 Announce Type: cross Abstract: We study byte-level autoregressive language models whose hidden state is a small quantum register, whose transitions are learned token-conditioned qua

Understanding Mamba-3 Through Oscillatory Dynamics

arXiv:2610.13341v1 Announce Type: new Abstract: Mamba-3 introduces input-dependent rotations into recurrent state updates, but their contribution beyond state retention remains unclear. We interpret t

researcharxiv-cs-lg

Unreliable Narrator Framing as a Cost-effective Mechanism for Satire Explanation of Australian and American Satirical News

arXiv:2610.12863v1 Announce Type: new Abstract: Satirical news is a unique form of misinformation: it is intended to be humorous by the original publication source but can be misinterpreted. Explanati

zip2zip++: Towards Inference-Time Token Compression with Minimal Quality Loss

arXiv:2610.13605v1 Announce Type: new Abstract: Dynamic vocabularies built on-the-fly via Lempel-Ziv-Welch (LZW) compression let a language model represent the same text in fewer tokens, but prior wor

researcharxiv-cs-cl

Tutorials

3DTexMOR: 3D Gaussian Multi-Object Removal via Texture-Space Inpainting