Search: “context”

Indi-RomCoM: Code-Mixed Benchmark for Evaluating LLMs on Romanized Indic-English Instructions

arXiv:2606.30790v1 Announce Type: cross Abstract: Romanized Code Mixing (RCM), where bilingual speakers fluidly blend local languages with English in Roman script, has emerged as the dominant form of

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Research

Joint Optimization for 4D Human-Scene Reconstruction in the Wild

DGX agent

arXiv:2501.02158v3 Announce Type: replace Abstract: Reconstructing human motion and its surrounding environment is crucial for understanding human-scene interaction and predicting human movements in t

researcharxiv-cs-cv

1 Jul 2026

Learning Dexterous Grasping from Sparse Taxonomy Guidance

arXiv:2604.04138v2 Announce Type: replace-cross Abstract: Dexterous manipulation requires planning a grasp configuration suited to the object and task, which is then executed through coordinated multi

Applications

Learning Locomotion on Discrete Terrain via Minimal Proximity Sensing

arXiv:2606.31912v1 Announce Type: new Abstract: Learning-based control has revolutionized dynamic locomotion, yet navigating unstructured terrain remains limited by a robot's incomplete awareness of i

applicationsarxiv-cs-ro

Learning to Deny: Action Denial in Multimodal Large Language Models

arXiv:2606.31187v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have rapidly advanced video understanding, achieving strong zero-shot and few-shot recognition across standard

LLM-Powered Interactive Robotic Action Synthesis from Multimodal Speech, Gestures, and Music

arXiv:2606.31158v1 Announce Type: cross Abstract: The quest for intuitive and natural human-robot interaction (HRI) remains a significant challenge in robotics. Traditional methods often rely on rigid

Local Pheromone Network: Sparse Local Learning with Multi-Scale Synaptic Trails, Consolidation, and Replay

arXiv:2606.30669v1 Announce Type: cross Abstract: Backpropagation-trained dense neural networks are powerful function approximators, but they couple learning across many parameters and can overwrite p

Long-term Traffic Simulation via Structured Autoregressive Modeling

arXiv:2606.31209v1 Announce Type: new Abstract: Interactive traffic simulation is a vital world model for autonomous driving. A central challenge in long-horizon simulation is modeling sustained multi

Local Ai

Look But Don't Touch with Sparse Autoencoders for Unlearning in Diffusion Models

arXiv:2606.31699v1 Announce Type: cross Abstract: Sparse autoencoders (SAEs) have recently been proposed as interpretable tools for concept-level manipulation, under the assumption that isolated featu

local-aiarxiv-cs-ai

Mean-Field Model for Two-Layer Neural Networks Trained with Consensus-Based Optimization

arXiv:2511.21466v3 Announce Type: replace Abstract: We study Consensus-Based Optimization (CBO) for two-layer neural network training. We compare the performance of CBO against Adam on two test cases

Measuring & Mitigating Over-Alignment for LLMs in Multilingual Criminal Law Courts

arXiv:2606.23375v2 Announce Type: replace-cross Abstract: While the wider applicability of LLMs in the legal field is currently debated due to their reliability and the gravity of any errors, narrow u

MIRTH: Mutual-Information Reasoning with Temporal Hubs for Vision-Language-Action Agents

arXiv:2606.31167v1 Announce Type: cross Abstract: VLA models have emerged as a powerful paradigm for transferring semantic knowledge from web-scale data to physical robotic control. However, current s

MS-Resampler: Multi-Scope Visual Resampling for Efficient Multimodal LLMs

arXiv:2606.31383v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) typically employ resampling-based projectors to transform dense visual features into a compact token sequence f

researcharxiv-cs-cv

One Reflection Is Not Enough: Self-Correcting Autonomous Research via Multi-Hypothesis Failure Attribution

arXiv:2606.31478v1 Announce Type: new Abstract: Autonomous research agents can now draft hypotheses, write code, run experiments, and produce papers, but they remain brittle when experiments fail. Und

Online TT-ALS for Streaming Tensor Decomposition with Incremental Orthogonalization

arXiv:2606.31061v1 Announce Type: cross Abstract: Tensor Train (TT) decomposition is a powerful technique for analyzing high-dimensional data. Existing algorithms for computing TT decompositions can b

researcharxiv-cs-cv

Paper2Rebuttal: A Multi-Agent Framework for Transparent Author Response Assistance

arXiv:2601.14171v2 Announce Type: replace Abstract: Writing effective rebuttals is a high-stakes task that demands more than linguistic fluency, as it requires precise alignment between reviewer inten

PriorEye: Geospatial Visual Priors for End-to-End Autonomous Driving

arXiv:2606.31830v1 Announce Type: new Abstract: Most end-to-end autonomous driving methods rely solely on instantaneous sensor observations, limiting them to reactive behavior without the anticipatory

Probabilistic Inversion with Flow Matching

arXiv:2606.31288v1 Announce Type: new Abstract: We demonstrate the application of Flow Matching, a technique originating from generative Artificial Intelligence, to probabilistic inversion in geophysi

Local Ai

PruneGround: Plug-and-play Spatial Pruning for 3D Visual Grounding

arXiv:2606.31148v1 Announce Type: cross Abstract: 3D Visual Grounding (3DVG) aims to localize target objects in 3D scenes given natural language descriptions. Existing approaches typically perform rea

local-aiarxiv-cs-ai

Reinforcement Learning with Metacognitive Feedback Elicits Faithful Uncertainty Expression in LLMs

arXiv:2606.32032v1 Announce Type: cross Abstract: Metacognition is a critical component of intelligence that describes the ability to monitor and regulate one's own cognitive processes. Yet LLMs exhib

REMSA: Foundation Model Selection for Remote Sensing via a Constraint-Aware Agent

arXiv:2511.17442v3 Announce Type: replace-cross Abstract: Foundation Models (FMs) are increasingly integrated into remote sensing (RS) pipelines. These models include unimodal vision encoders and mult

Local Ai

Robust 3D-Masked Part-level Editing in 3D Gaussian Splatting with Regularized Score Distillation Sampling

arXiv:2507.11061v3 Announce Type: replace-cross Abstract: Recent advances in 3D neural representations and instance-level editing models have enabled the efficient creation of high-quality 3D content.

local-aiarxiv-cs-ai

Robust Text Watermarking for Large Language Models via Dual Semantic Embeddings

arXiv:2606.31602v1 Announce Type: new Abstract: This work presents Dual-Embedding Watermarking (DEW), a semantic watermarking scheme for large language models (LLMs) that leverages contextual and toke

safetyarxiv-cs-cl

Scientific Explanations in Health Sciences: Causality, Trust, and Epistemic Adequacy

arXiv:2606.31616v1 Announce Type: new Abstract: Medical Artificial Intelligence (AI) is widely expected to transform clinical practice, yet the decision-making processes of many Machine Learning (ML)

Seeing Is Not Sharing: Some Vision-Language Models Overestimate Common Ground in Asymmetric Dialogue

arXiv:2606.31719v1 Announce Type: cross Abstract: In collaborative dialogue, shared perception does not guarantee shared interpretation. Mutual understanding must be established through interaction. W

Agents

ShopX: A Foundation Model for Intent-to-Item Fulfillment in Agentic Shopping

arXiv:2606.31693v1 Announce Type: cross Abstract: The wave of AI-native applications is moving shopping beyond page- and feed-based browsing toward intent-driven experiences orchestrated by LLM agents

agentsarxiv-cs-ai

SimpleSearch-VL: A Simple Recipe for Multimodal Agentic Deep Search

arXiv:2606.31504v1 Announce Type: new Abstract: We present SimpleSearch-VL, an efficient, reliable, and practical framework for multimodal agentic search. Its core idea is to improve the agent's own s

Tutorials

Step-by-Step Video-to-Audio Synthesis via Negative Audio Guidance

arXiv:2506.20995v4 Announce Type: replace Abstract: We propose a step-by-step video-to-audio (V2A) generation method that provides finer control over the generation process and more realistic audio sy

tutorialsarxiv-cs-cv

Temporal Preservation over Processing: Diagnosing and Designing Spatiotemporal Single-Stage Video Detectors

arXiv:2606.31421v1 Announce Type: cross Abstract: Single-stage video object detectors are increasingly deployed in time-critical applications, yet it remains unclear whether these models genuinely rea

The Bidirectional Process Reward Model

model-releasesarxiv-cs-cl

arXiv:2508.01682v3 Announce Type: replace Abstract: Process Reward Models (PRMs), which assign fine-grained scores to intermediate reasoning steps within a solution trajectory, have emerged as a promi

The Label Imitation Game: Turing Test Network for Zero-Shot Pseudo-Label Pruning

arXiv:2606.30875v1 Announce Type: cross Abstract: Foundation model pseudo-labeling - labeling data strictly via zero-shot inference - enables massive scale, but performance is undermined by hallucinat

Thinking Before Retrieving: Robust Zero-Shot Composed Image Retrieval via Strategic Planning and Self-Criticism

arXiv:2606.31222v1 Announce Type: new Abstract: Composed image retrieval requires identifying a target image from a gallery by integrating a reference image with a textual modification instruction. In

What Counts as an Error? Dual-Reference Benchmarking for Atypical ASR

model-releasesarxiv-cs-cl

arXiv:2606.31112v1 Announce Type: new Abstract: ASR systems have been often reported to underperform on atypical speech. An often conflated compounding factor is the existence of two valid transcripti

5ting at SemEval-2026 Task 8: Strong End-to-End Multi-Turn RAG via LLM-Based Reranking and Faithfulness Control

arXiv:2606.28737v1 Announce Type: cross Abstract: We introduce 5ting, our system for the SemEval2026 Task 8 (MTRAGEval), which evaluates multi-turn Retrieval Augmented Generation (RAG) systems. Multi

A multi-architecture study of specificity refinement and false-positive mechanism analysis in prostate MRI

arXiv:2606.29977v1 Announce Type: cross Abstract: Objectives: To characterize residual false positives in prostate MRI detection, and to evaluate a lightweight post-hoc refinement head for case-level

Adaptive Financial Transformer with Regime-Gated Attention for Stock Return Prediction

arXiv:2606.29347v1 Announce Type: cross Abstract: Adaptive Financial Transformer (AFT) is proposed for stock return prediction under non-stationary financial markets. The model incorporates a Market R

AERMANI-VLM: Structured Prompting and Reasoning for Aerial Manipulation with Vision Language Models

arXiv:2511.01472v2 Announce Type: replace Abstract: The rapid progress of vision--language models (VLMs) has sparked growing interest in robotic control, where natural language can express the operati

safetyarxiv-cs-ro

Agentic Abstention: Do Agents Know When to Stop Instead of Act?

arXiv:2606.28733v1 Announce Type: new Abstract: LLM agents are expected to act over multiple turns, using search, browsing interfaces, and terminal tools to complete user goals. Yet not every goal is

ANVIL: Anomaly-based Vulnerability Identification without Labelled Training Data

arXiv:2408.16028v4 Announce Type: replace-cross Abstract: Supervised-learning-based vulnerability detectors often fall short due to limited labelled training data. In contrast, Large Language Models (

BabyHuBERT: Multilingual Self-Supervised Learning for Segmenting Speakers in Child-Centered Long-Form Recordings

arXiv:2509.15001v3 Announce Type: replace-cross Abstract: Child-centered daylong recordings are essential for studying early language development, but existing speech models trained on clean adult dat

Behavior Prompting Policy: Demonstrations as Prompts for Manipulation

arXiv:2606.30457v1 Announce Type: new Abstract: We study behavior prompting, a paradigm that enables robots to perform new tasks at inference time given a single human demonstration, which we call a b

safetyarxiv-cs-ro

BERTomelo: Your Portuguese Encoder Best Friend

arXiv:2606.28999v1 Announce Type: cross Abstract: Encoders have become the state of the art for multiple NLP tasks, especially those requiring deep contextual understanding. While multilingual models

BTI-Net: Bidirectional Decoder-Level Task Interaction via Uncertainty-Aware Gating for Multi-Task Medical Image Analysis

arXiv:2606.29102v1 Announce Type: cross Abstract: Jointly learning to segment and classify medical images demands cross-task synergy, yet encoder-sharing architectures limit decoder reconstruction to

Carolina Guide: A Multi-Agent RAG System with Institutional Guardrails for Academic Policy Assistance

arXiv:2606.28360v1 Announce Type: cross Abstract: University students often struggle to navigate complex academic policies, leading to advising bottlenecks and delayed access to critical information.

Categorize Early, Integrate Late: Divergent Processing Strategies in Automatic Speech Recognition

arXiv:2601.06972v2 Announce Type: replace Abstract: In speech language modeling, two architectures dominate the frontier: the Transformer and the Conformer. However, it remains unknown whether their c

researcharxiv-cs-cl

Categorizing Mathematical Concepts with LLM Voting Ensembles in Mathswitch

arXiv:2606.28815v1 Announce Type: cross Abstract: Mathswitch is an open-source project that imports mathematical concept records from sources such as Wikidata, Wikipedia, MathWorld, Encyclopedia of Ma

CLIMP: Contrastive Language-Image Mamba Pretraining

arXiv:2601.06891v2 Announce Type: replace Abstract: Contrastive Language-Image Pre-training (CLIP) relies on Vision Transformers whose attention mechanism is susceptible to spurious correlations, and

researcharxiv-cs-cv

CLMASP: Coupling Large Language Models with Answer Set Programming for Robotic Task Planning

arXiv:2406.03367v2 Announce Type: replace Abstract: Large Language Models (LLMs) possess extensive foundational knowledge and moderate reasoning abilities, making them suitable for general task planni