Search: “framework”

UniFGVC: Universal Training-Free Few-Shot Fine-Grained Vision Classification via Attribute-Aware Multimodal Retrieval

arXiv:2508.04136v4 Announce Type: replace-cross Abstract: Few-shot fine-grained visual classification (FGVC) aims to discriminate between subtly different categories with very limited data. While Mult

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Model Releases

VALCON: Benchmarking and Enhancing Value Consistency in Large Language Models via Dual-Role Variation

DGX agent

arXiv:2610.21304v1 Announce Type: new Abstract: Current value alignment evaluations for large language models (LLMs) heavily rely on output compliance, overlooking whether LLMs maintain value consiste

model-releasesarxiv-cs-cl

16 Oct 2026

Value as Memory: Online Value-Guided Post-training for General Robot Policies

arXiv:2610.22368v1 Announce Type: new Abstract: Real-world post-training of generalist robot policies faces two challenges: partial observability makes action selection ambiguous, while offline post-t

safetyarxiv-cs-ro

Tutorials

VLA-Delta: Learning Physical State Transition for Vision-Language-Action Models

arXiv:2610.21306v1 Announce Type: new Abstract: Vision-language-action (VLA) models transfer semantic knowledge acquired through vision-language pretraining to robot control, achieving strong performa

tutorialsarxiv-cs-cv

VP-EVT: Active Visibility Preservation for Embodied Visual Tracking

arXiv:2610.21999v1 Announce Type: new Abstract: Embodied Visual Tracking (EVT) is an essential capability for intelligent robots in human-robot collaboration, requiring an agent to follow a designated

agentsarxiv-cs-ro

WaveLLM: Wavelet-Domain LLM Entropy Modeling for Lossless Image Compression

model-releasesarxiv-cs-cv

arXiv:2610.22232v1 Announce Type: new Abstract: Lossless image compression fundamentally relies on accurate entropy modeling, driving a recent shift toward large language model (LLM)-based methods. Ho

WEAVE: Weaving Real-World Code Evolution into Dependency-Structured Tasks for Benchmarking and Training Code Agents

arXiv:2610.22039v1 Announce Type: cross Abstract: Real-world software engineering rarely consists of isolated changes. Features, migrations, and systematic fixes often unfold across multiple pull requ

agentsarxiv-cs-cl

When Does 'Post-Call' Begin? An Availability Contract for Earnings-Call NLP Benchmarks

arXiv:2610.21659v1 Announce Type: cross Abstract: Corporate financial disclosures often unfold over time, with announcements, prepared remarks, and discussion spanning multiple high-frequency return i

When is a better LLM worth paying for? Stochastic Optimization with Switching Mixed-Fidelity Oracles

arXiv:2610.21139v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used upstream of decision-making to clean data, detect label errors, and reconstruct missing values. Yet

Local Ai

When Is Muon Optimal? Radial Fragility and Minimax Geometry

arXiv:2610.21549v1 Announce Type: cross Abstract: Muon replaces a matrix gradient by an approximate polar factor and has shown strong empirical performance in neural-network training. The Isotropic Cu

local-aiarxiv-cs-ai

When Should a Low-Light Pipeline Generate? Auditable Risk Control for Selective Generative Enhancement

arXiv:2610.21335v1 Announce Type: new Abstract: Generative low-light enhancers recover plausible texture but may hallucinate structure; restoration networks preserve structure but can leave regions un

researcharxiv-cs-cv

Where, How, and When: Query-Guided Grounding for Video Understanding

arXiv:2610.21422v1 Announce Type: cross Abstract: Understanding video content requires reasoning at multiple levels of granularity, from identifying objects to interpreting their interactions and loca

Where to Steer: Input-Dependent Layer Selection for Steering Improves LLM Alignment

arXiv:2604.03867v2 Announce Type: replace Abstract: Steering vectors have emerged as a lightweight and effective approach for aligning large language models (LLMs) at inference time, enabling modulati

safetyarxiv-cs-lg

Which Tokens to Merge? Diffusion Dynamics for Efficient Image Generation

arXiv:2610.22370v1 Announce Type: new Abstract: Token merging has emerged as an effective training-free strategy for accelerating diffusion models by reducing redundant token computation while minimiz

researcharxiv-cs-cv

Whole-Body Dexterity

arXiv:2610.22184v1 Announce Type: cross Abstract: Current humanoid dexterous manipulation remains largely confined to end-effectors and simple grasps, falling short of humans' ability to engage the en

Why Do Agent Teams Fail Across Boundaries? A Failure Taxonomy for Agent-to-Agent Systems with Private States

arXiv:2610.19342v2 Announce Type: replace-cross Abstract: Agents are increasingly interacting with other agents that act for different principals (people or organizations on whose behalf they work), s

agentsarxiv-cs-ai

X-Fly: Learning to Reach and Stop in Full-Chunk Aerial Vision-Language Navigation

arXiv:2610.21450v1 Announce Type: cross Abstract: Aerial vision-language navigation (VLN) agents built on large vision-language models are expensive to query. Executing a complete predicted action chu

5/5 Across the board, results show the business impact and differentiation of sovereign specialized intelligence, and the opportunity for co…

model-releasesai21-labs--x

5/5 Across the board, results show the business impact and differentiation of sovereign specialized intelligence, and the opportunity for companies to reach AI independence. Thanks to @nvidia, @Gong_i

A Bregman Proximal Viewpoint on Neural Operators

arXiv:2610.20120v1 Announce Type: new Abstract: We present several advances on neural operators by viewing the action of operator layers as the minimizers of Bregman regularized optimization problems

researcharxiv-cs-lg

A Counterfactual Graph Approach to Oppositional Narrative Analysis

arXiv:2603.06135v3 Announce Type: replace-cross Abstract: Distinguishing legitimate critical speech from coordinated conspiracy narratives is a pressing challenge for the integrity of the online infor

A Decade in a Day: Synthesizing Agent-Native Interfaces from Human-Oriented Software Evolution

arXiv:2610.15765v1 Announce Type: cross Abstract: Large language model agents are emerging as an important new class of users of desktop applications. However, existing desktop interfaces were designe

Applications

A Graph-Based Analysis of Comparability, Scale, and Attribution in Private Transformer Inference

arXiv:2610.19607v1 Announce Type: cross Abstract: Rising privacy concerns around large language models have accelerated research in private Transformer inference (PTI). Synthesizing the empirical clai

applicationsarxiv-cs-lg

A Master-to-Simulation Interface with Demonstration-Trajectory Guidance for Vascular Intervention

arXiv:2610.19395v1 Announce Type: new Abstract: Robotic vascular intervention can reduce radiation exposure to physicians and improve manipulation stability, but effective guidance remains challenging

researcharxiv-cs-ro

A Mode-Unified, Continuous, and Biomimetic Control Strategy of a Robotic Lower Limb Prosthesis

model-releasesarxiv-cs-ro

arXiv:2610.19183v1 Announce Type: new Abstract: Existing biomimetic lower-limb prosthesis controllers are commonly designed for discrete locomotion modes, requiring separate parameterizations for leve

A^3PreCore: Robust Rigid Registration for Native FLAIR-Space Brain-Mask Transfer

arXiv:2610.20561v1 Announce Type: new Abstract: Reliable brain-mask transfer into native fluid-attenuated inversion recovery (FLAIR) space can fail when T1-to-FLAIR rigid registration is unstable. We

safetyarxiv-cs-cv

Active Generative Simulation: Meta-Learning What to Simulate for Sim-and-Real Policy Co-Training

model-releasesarxiv-cs-ro

arXiv:2610.19479v1 Announce Type: new Abstract: Sim-and-real co-training is an effective way to scale robot learning by augmenting limited real-world demonstrations with simulation data. However, exis

Active Perception of Upper-Limb Functional Mobility through Human-Robot Handovers

arXiv:2610.19896v1 Announce Type: new Abstract: The reintegration of people in the workplace after an upper-limb injury is often a long process. Collaborative robots and humanoids operating in shared

researcharxiv-cs-ro

AdaptFuse: Training-Free Sequential Preference Inference via Externalized Bayesian Computation

arXiv:2604.03925v2 Announce Type: replace Abstract: Large language models (LLMs) struggle to accumulate evidence across multiple rounds of user interactions, failing to update their beliefs in a manne

Hardware

AdaRSI: On-Demand Recursive Self-Improvement for Embodied Agents

arXiv:2610.20474v1 Announce Type: new Abstract: Pretrained vision-language-action models (VLAs) often fail midway through unseen long-horizon tasks. Recursive self-improvement (RSI) offers a remedy, b

hardwarearxiv-cs-cl

AegisVox: Factorized Privacy and Clinical Preservation for Long-Form Speech

arXiv:2610.14643v1 Announce Type: new Abstract: Clinical speech reveals identity through both spoken identifiers and voice, yet its pauses, delivery, and speaker roles can also carry useful clinical e

Agent-Environment Alignment via Automated Interface Generation

arXiv:2505.21055v2 Announce Type: replace Abstract: Large language model (LLM) agents have shown impressive reasoning capabilities in interactive decision-making tasks. These agents interact with envi

Agent Sociodrama: Social-Dynamics-Guided Persona Recasting for LLM Agent Teams

arXiv:2610.15788v1 Announce Type: new Abstract: Large language model (LLM) agents are increasingly deployed as teams, yet they fail in characteristically social ways: information holders stay silent,

agentsarxiv-cs-ai

AgentStripes: An Evidence-Graded Maturity Model for AI Agents

arXiv:2610.18603v1 Announce Type: new Abstract: Benchmarks report what an Artificial Intelligence (AI) agent can do on a task suite, but not whether one released version has been engineered with the c

Hardware

AgriJev: Efficient Agricultural Candidate Scoring with Multi-Scale Adapted Models

arXiv:2610.19478v1 Announce Type: new Abstract: Agricultural systems make decisions over heterogeneous entity types, textual judgments, and knowledge-question options. Generating a textual answer adds

hardwarearxiv-cs-cl

Alignment Faking - the Train -> Deploy Asymmetry: Through a Game-Theoretic Lens with Bayesian-Stackelberg Equilibria

arXiv:2511.17937v2 Announce Type: replace Abstract: Alignment faking is a form of strategic deception in AI in which models selectively comply with training objectives when they infer that they are in

AlignMerge - Alignment-Preserving Large Language Model Merging via Fisher-Guided Geometric Constraints

arXiv:2512.16245v2 Announce Type: replace Abstract: Merging large language models (LLMs) is a practical way to compose capabilities from multiple fine-tuned checkpoints without retraining. Yet standar

AlignPoison: Conditional Targeted Poisoning of Generative Recommenders via Decoding-Aligned Prefixes

arXiv:2610.14487v1 Announce Type: new Abstract: Generative recommendation models based on autoregressive decoding have been adopted as alternatives to classical ranking-based systems. While their mode

Analyzing the Dynamics of WSBM-based Echo State Networks using InputDSA

arXiv:2610.15380v1 Announce Type: new Abstract: Bridging the structural gap between biological brains and artificial neural networks presents a pathway to altered computational dynamics. This paper in

researcharxiv-cs-ai

ANCHOR: Assessing Naturalistic Constraint Hierarchies and Ordering in Repository-Grounded Agentic Coding

arXiv:2610.16859v2 Announce Type: replace Abstract: For repository-grounded coding agents, a functionally correct patch is not necessarily an acceptable one: developers also constrain how the task mus

AphaVoice: Text-to-Speech Model for Aphasia Patient Simulation

arXiv:2610.14479v1 Announce Type: cross Abstract: While language therapy is the primary treatment for post-stroke aphasia, limited clinical resources often restrict patient access to proper care. Addr

researcharxiv-cs-ai

Are Benchmarks Reliable? Toward Structural Diagnosis via Item-Level Capability Boundaries

arXiv:2609.33196v2 Announce Type: replace Abstract: Evaluating large language models (LLMs) relies heavily on benchmark scores, yet aggregate metrics can obscure whether individual items serve their i

Are Multimodal Benchmarks Really Useful? Item-Level Multimodal Benchmark Diagnosis via Structure-Response Co-Calibration

arXiv:2610.14542v1 Announce Type: new Abstract: Multimodal benchmarks are central to evaluating whether models can reason over information from multiple modalities. However, existing literature has re

Hardware

AReaL-RSI: Adaptive Scaling and Coordination of Recursive Self-Improvement

arXiv:2610.18083v1 Announce Type: new Abstract: Scaling recursive self-improvement requires additional computation to produce useful research progress in reaching persistent objectives. Intuitively, m

hardwarearxiv-cs-ai

Atomic-WAM: Execution-Grounded Atomic-Motion Reasoning for World Action Models

arXiv:2610.20157v1 Announce Type: new Abstract: World Action Models (WAMs) typically adapt video foundation models to robotic control through joint video and action prediction. However, task-level ins

researcharxiv-cs-ro

au-Emotion-Bench: Exposing the Interaction Fragility of LLM Agents through Real-World User Emotions

arXiv:2610.19560v1 Announce Type: cross Abstract: In long-horizon tool-calling tasks, LLM agents can fail not only because of tool-use errors, but also because of ineffective interaction with users. Y

Applications

AutoRSR: Automated Real-to-Sim-to-Real Data Generation for Scalable Robot Learning

arXiv:2610.20336v1 Announce Type: new Abstract: Scaling embodied robot learning requires large and diverse manipulation datasets, but collecting real-world demonstrations remains expensive in human ef

applicationsarxiv-cs-ro

Back on Track: Deployment-time Policy Improvement via World Model Planning

arXiv:2610.19579v1 Announce Type: new Abstract: State-of-the-art visuomotor policies are increasingly capable of executing complex tasks, yet can fail during deployment in ways they cannot predict or

safetyarxiv-cs-ro

Back to the Future: Reverse-Consequence Modeling for Long-Horizon Particle Dynamics

arXiv:2610.18168v1 Announce Type: new Abstract: Accurate prediction of object trajectories is fundamental to mechanical understanding and robotic control. However, autoregressive models inherently suf

researcharxiv-cs-ai