Search: “evaluation”

Anvil: Scaling Embodied Spatial Intelligence through Knowledge Recirculation

arXiv:2610.21882v1 Announce Type: cross Abstract: Embodied spatial intelligence requires more than visual recognition: models must localize entities, reason about their relations, and express this kno

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Research

Automatic Sentence Completion Using Bengali Audio Speech with a Transformer-Based Early Speech Recognition System

DGX agent

arXiv:2610.21164v1 Announce Type: new Abstract: Dementia severely impairs communication abilities and turns everyday conversations into challenging experiences. Individuals affected by dementia freque

researcharxiv-cs-cl

16 Oct 2026

AutoOnboarder: Autonomously Onboarding LLM Agents

arXiv:2610.21218v1 Announce Type: new Abstract: Agentic large language models have been documented to lose reasoning capability when placed inside a harness, the software that mediates their observati

Bellman-Consistent Trajectory RL for LLM Arithmetic Reasoning

arXiv:2610.21060v1 Announce Type: cross Abstract: To address sparse terminal rewards in LLM arithmetic reasoning, we propose a Bellman-consistent trajectory RL method. Our framework introduces Traject

Beyond Generation: Using Multimodal LLMs as Detectors of LLM-Generated Deepfake Facial Images

model-releasesarxiv-cs-cv

arXiv:2610.21760v1 Announce Type: new Abstract: As image generation models become increasingly capable of producing highly realistic content, traditional forensic techniques are struggling to keep up.

Beyond Invariance: Factor-wise Selective Treatment of Shifts for Multimodal Learning

arXiv:2610.21403v1 Announce Type: new Abstract: Distribution shifts pose a fundamental challenge to robust multimodal learning. Existing methods typically promote invariance by suppressing environment

researcharxiv-cs-cl

Agents

Beyond Retrieval Failure: Understanding Why LLMs Miss Evidence in Multi-Hop RAG

arXiv:2610.21184v1 Announce Type: new Abstract: Multi-hop retrieval-augmented generation (RAG) requires an agent to retrieve evidence for a sequence of dependent sub-questions. When a wrong answer lac

agentsarxiv-cs-cl

Blame Errant Words, Not the Canvas: Defect-Aware Spatial Credit Assignment for Visual Text Generation

arXiv:2610.20794v1 Announce Type: new Abstract: Recent reinforcement learning approaches have improved visual text generation, yet generated images still suffer from incorrect wording and malformed gl

local-aiarxiv-cs-cv

Calibration Language Shapes Block-Influence Pruning in Multilingual Language Models

arXiv:2610.21383v1 Announce Type: new Abstract: Block Influence (BI) ranks Transformer blocks for depth pruning from their input-output cosine change, but the ranking depends on the calibration distri

Can Capability Enhancement be Localized?

arXiv:2610.21294v1 Announce Type: new Abstract: Transformer-based language models have shown strong capabilities across many tasks and domains. However, prior work shows that, for a given task, not al

local-aiarxiv-cs-lg

Can LLMs Anticipate Their Cruxes?

arXiv:2610.21006v1 Announce Type: new Abstract: To use language models to help us make decisions we would like to understand the rationale behind the language model's outputs. In principle, the langua

researcharxiv-cs-cl

Can MLLMs Read the Room? A Multimodal Benchmark for Assessing Deception in Multi-Party Social Interactions

arXiv:2511.16221v2 Announce Type: replace-cross Abstract: Despite their advanced reasoning capabilities, state-of-the-art Multimodal Large Language Models (MLLMs) still lack a core component of human

Can World and Action Modeling Benefit Each Other under Unified Causal Training?

arXiv:2610.21095v1 Announce Type: new Abstract: World and action modeling are closely related, yet their reciprocal benefits under unified causal training remain unclear. We introduce OneWM, a simple

safetyarxiv-cs-cv

CARE-SD: Explainable Reasoning Architecture for Local SLM Self-Disclosure Analysis in Textual Data

arXiv:2610.21151v1 Announce Type: cross Abstract: Cybersecurity interviews uncover critical security experiences, behaviors, and privacy concerns often not fully captured by conventional technical ass

CascadeLedger: Counterfactual Auditing of Information and Resource Integrity in LLM Cascades

arXiv:2610.20668v1 Announce Type: cross Abstract: We introduce CascadeLedger, a counterfactual execution-audit framework for budgeted language-model cascades. The protocol enforces call-before-read se

safetyarxiv-cs-cl

CAT-alyzing Honesty: Continuous Adversarial Training for Transferable LLM Honesty

arXiv:2610.22292v1 Announce Type: cross Abstract: Large language models (LLMs) are becoming prevalent in scenarios where honesty is critical. However, despite alignment training, these models still ex

Causal Analysis of Robot Foundation Models Enables Efficiency Gains

arXiv:2610.20750v1 Announce Type: new Abstract: Vision-language-action (VLA) models are a promising approach to general purpose robot manipulation. While the internal computation of vision-language mo

researcharxiv-cs-ro

Causal Integrated Gradients: Scalable Feature Attribution Along Causal Paths

arXiv:2610.22126v1 Announce Type: cross Abstract: Existing feature attribution methods that account for feature dependencies do not scale to high dimensions. We propose causal integrated gradients (CI

Circuit Claims Depend on What Is Extracted and How It Is Compared

arXiv:2607.18921v2 Announce Type: replace-cross Abstract: Circuit extraction identifies model components whose presence preserves a target behavior under ablation, but preserving behavior does not sin

CLAD: Keypoint Matching Using Global Line Correspondences

arXiv:2610.21409v1 Announce Type: new Abstract: Traditional keypoint descriptors, such as SIFT (Scale-Invariant Feature Transform) and ORB (Oriented FAST and Rotated BRIEF), are computed from local im

Co2In: a Bi-level Memory Incremental Learning Framework with Knowledge Encoding, Consolidation, and Integration

arXiv:2610.21804v1 Announce Type: new Abstract: Incremental learning (IL) aims to continually acquire new knowledge (plasticity) while retaining previously learned information (stability). However, st

CoDeFont: One-Shot Font Generation via Multi-Scale Factor-Specific Representation Learning

arXiv:2610.21364v1 Announce Type: new Abstract: One-shot Font Generation (OFG) aims to synthesize a target glyph by transferring the stylistic characteristics of a single reference glyph while preserv

CogDrift-4D: Hierarchical Multimodal Modeling of Temporal Behavioral Decay for MCI Detection

arXiv:2610.20877v1 Announce Type: cross Abstract: Early detection of mild cognitive impairment remains a critical bottleneck in dementia care, demanding scalable tools capable of capturing subtle beha

local-aiarxiv-cs-cl

Compression Does Not End at Selection: Post-Selection Positional Geometry for Sparse KV Caches

arXiv:2610.21126v1 Announce Type: new Abstract: Sparse KV compression reduces long-context inference costs by retaining selected historical states, yet these states typically keep their coordinates fr

Condition-Contrastive Extrapolation for On-Policy Distillation of Language Models

arXiv:2610.21195v1 Announce Type: new Abstract: On-policy distillation (OPD) improves a student language model by training on its own generated trajectories with supervision from a stronger teacher. H

CoTranslator: Reverse to Forward Chain-of-Thought Translator for Reasoning Distillation

arXiv:2610.20828v1 Announce Type: cross Abstract: Reasoning distillation requires chain-of-thought (CoT) data with correct answers, but obtaining such data efficiently remains challenging. Forward CoT

Counterfactual Neighborhood Risk Fields: Evidence-Grounded Selective Safety for Vision-Language Models

arXiv:2610.20679v1 Announce Type: new Abstract: Representation-based safety defenses for vision-language models (VLMs) often learn to separate harmful from benign inputs, but separation alone does not

CoViG: Coarsened Vision GNN for Image Classification

arXiv:2610.21321v1 Announce Type: new Abstract: Although Graph Neural Networks are widely used in various domains, they remained mostly unexplored in computer vision. Convolutional Neural Networks and

Cross-Prompt Inference Mitigates Rare-Class Suppression in Imbalanced VLM Finetuning

arXiv:2610.21470v1 Announce Type: new Abstract: When a vision-language model is finetuned on class-imbalanced data, rare-class recall can fall well below the model's own zero-shot performance. In this

Data Strategies for Large Language Models: A Unified Perspective on the Training Lifecycle

arXiv:2610.21681v1 Announce Type: new Abstract: Data strategy plays a central role in training large language models (LLMs). It governs the selection, weighting, and scheduling of training data, there

researcharxiv-cs-cl

Decentralized LLM Workflows via Sequential Auctions

arXiv:2610.22201v1 Announce Type: cross Abstract: We present a scalable framework for solving multi-step tasks through a decentralized market of self-interested agents. Prior theoretical work demonstr

Defining and Generating Compositional Structure

arXiv:2610.20922v1 Announce Type: new Abstract: Compositional structure is pervasive in nature and across scales: atoms combine into molecules, molecules into cells, and cells into organisms, while fu

Dense4D: Pixel-Level 4D Human Correspondence

arXiv:2610.22325v1 Announce Type: new Abstract: Reconstructing human motion in 4D requires identifying the same surface points through articulation, deformation and changes in visibility. We introduce

DIAL: Dynamic and Informed Adjustment of the Native Stochastic Law for Reliable Weather Ensembles

arXiv:2610.21639v1 Announce Type: new Abstract: Ensemble weather forecasts can look reliable in global averages while hiding too little spread in some cases and too much in others. These errors vary a

Differentially Private Distribution Release of Gaussian Mixture Models via KL-Divergence Minimization

model-releasesarxiv-cs-lg

arXiv:2506.03467v4 Announce Type: replace-cross Abstract: Gaussian Mixture Models (GMMs) are widely used statistical models for representing multi-modal data distributions, with numerous applications

Digital Typhoon Dataset V3: Benchmarking for Multi-spectral Extension and Analyzing Systematic Bias in Intensity Regression

model-releasesarxiv-cs-cv

arXiv:2610.21654v1 Announce Type: new Abstract: This paper presents the Digital Typhoon Dataset V3, a new version of the longest typhoon satellite image dataset spanning nearly 50 years, designed to b

Dimension-Free PAC-Bayes Generalization for Deep Neural Networks via Dirichlet Processes

model-releasesarxiv-cs-lg

arXiv:2610.21340v1 Announce Type: cross Abstract: Classical PAC-Bayesian generalization theory places prior distributions over Euclidean parameter space Theta subseteq R^D, causing relative entropy to

Diminishing Returns of Data in Sparse Autoencoders: Functional Behavior does not Guarantee Feature Reproducibility

model-releasesarxiv-cs-lg

arXiv:2610.20680v1 Announce Type: new Abstract: Sparse autoencoders (SAEs) are typically trained on hundreds of millions to billions of activation tokens, yet little work has tested whether this scale

Agents

Diviner: Agentic RCA with Human-Governed Adaptation for Large-Scale Infrastructure

arXiv:2610.21281v1 Announce Type: new Abstract: Root-cause analysis (RCA) in large-scale distributed systems is challenging because a single symptom can cross service, data, configuration, compute, an

agentsarxiv-cs-ai

DLOSAC: Joint Spatial-Geometric Image Estimation via Delaunay-Guided Local Optimization RANSAC

arXiv:2610.21215v1 Announce Type: new Abstract: Reliable image geometric estimation from noisy matching points is typically addressed using RANSAC, often combined with local optimization to refine inl

local-aiarxiv-cs-cv

Do Agents Need a New Kind of Paper? SPRA: Structured Paper Representation for Agents

arXiv:2610.21424v1 Announce Type: new Abstract: Scientific agents must connect research problems, methods, and findings dispersed through narrative articles. We introduce SPRA (Structured Paper Repres

Does On-Policy Distillation Need to Complete Every Rollout?

arXiv:2610.21337v1 Announce Type: cross Abstract: On-policy distillation (OPD) effectively transfers capabilities from a teacher to a student through feedback on student-generated rollouts. However, g

Does Personalization Break Trust? Open-Set Rejection Calibration Under Few-Shot On-Device Intent Adaptation

arXiv:2610.20652v1 Announce Type: new Abstract: Always-on virtual assistants increasingly personalize on-device to new user-specific commands via few-shot fine-tuning (e.g., LoRA), but this adaptation

local-aiarxiv-cs-cl

DropKV: Decoupling Residual-Output Perturbation for Near-Optimal KV-Cache Eviction

arXiv:2610.22130v1 Announce Type: new Abstract: Key-value (KV) cache management has become a critical bottleneck for scaling Large Language Models (LLMs) to long-context scenarios due to linear memory

DuET: Note-Frame Dual Encoding for Piano Performance-to-Score Transcription

arXiv:2610.21467v1 Announce Type: cross Abstract: Transcribing expressive piano performances into scores requires interpreting individual note timings within an underlying metrical structure. However,

researcharxiv-cs-lg

Efficient Pairwise Difference Learning: A Comparative Study of Encoding Strategies and Training Pair Selection

arXiv:2610.21644v1 Announce Type: cross Abstract: Pairwise Difference Learning for Classification (PDC) enhances supervised learning in low-data regimes by training a binary similarity classifier on p

Applications

EgoJEPA: Beyond Retargeting for Dexterous Manipulation from Egocentric Videos

arXiv:2610.20904v1 Announce Type: cross Abstract: Egocentric human videos offer a scalable alternative to costly robot demonstra- tions, yet transferring their manipulation priors to robot control rem

applicationsarxiv-cs-cv

Emotion Is Not External Knowledge: Internal Attention Signals for Affective State Reasoning

arXiv:2610.21347v1 Announce Type: new Abstract: Large Language Models (LLMs) increasingly operate in multi-turn interactions that require maintaining latent conversational states, not only explicit fa

local-aiarxiv-cs-cl