Search: “benchmark”

WASD: Locating Critical Neurons as Sufficient Conditions for Explaining and Controlling LLM Behavior

arXiv:2603.18474v2 Announce Type: replace Abstract: Precise behavioral control of large language models (LLMs) is critical for complex applications. However, existing methods often incur high training

10 Apr 2026

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You Point, I Learn: Online Adaptation of Interactive Segmentation Models for Handling Distribution Shifts in Medical Imaging

DGX agent

arXiv:2503.06717v3 Announce Type: replace Abstract: Interactive segmentation uses real-time user inputs, such as mouse clicks, to iteratively refine model predictions. Although not originally designed

model-releasesarxiv-cs-cv

10 Apr 2026

A Distribution-to-Distribution Neural Probabilistic Forecasting Framework for Dynamical Systems

arXiv:2603.25370v2 Announce Type: replace-cross Abstract: Probabilistic forecasts provide a principled representation of forecast uncertainty through predictive distributions. Directly propagating pre

A Large-Scale Dataset for Multi-Class Financial News Classification in Brazilian Portuguese

arXiv:2610.20630v1 Announce Type: new Abstract: The development of Financial Natural Language Processing (NLP) systems for Brazilian Portuguese is hindered by the scarcity of domain-specific datasets.

researcharxiv-cs-cl

A Quantum Machine Learning Approach to Content-Based Media Recommendation

arXiv:2610.21562v1 Announce Type: new Abstract: We use quantum machine learning techniques to develop a content-based media recommender system and evaluate its performance on TV programmes using textu

A team of Gemini 4 Argon agents beats Minecraft

arXiv:2610.22319v1 Announce Type: new Abstract: We placed four Gemini 4 Argon agents in a sandboxed Minecraft survival world and gave them one goal: defeat the Ender Dragon. Each agent controlled a pl

AgentEval: Evidence-Bounded Assessment of Stateful Agents

arXiv:2610.21177v1 Announce Type: new Abstract: Task completion alone does not determine whether a stateful agent satisfied its obligations, and a recorded judgment does not guarantee that its support

All-in-One Memory: Process-Rewarded Reinforcement Learning for Memory Agents

arXiv:2610.21147v1 Announce Type: new Abstract: Large language models increasingly rely on external memory to answer queries grounded in long-horizon histories such as multi-session dialogues and leng

safetyarxiv-cs-ai

Amortizing Sequential Experimental Design in Reasoning LLMs

arXiv:2610.20832v1 Announce Type: cross Abstract: Despite their extensive pretraining knowledge and strong reasoning capabilities, large language models (LLMs) struggle to adaptively gather informatio

Anchor3DGS: Feed-Forward 3D Gaussian Splatting with Compact Anchor-Based Representation

arXiv:2610.21634v1 Announce Type: new Abstract: Recent feed-forward 3D Gaussian Splatting (3DGS) methods have enabled effective multi-view 3D reconstruction by predicting Gaussian primitives in a sing

Anticipatory Commonsense with Moving Objects: An ASP-Based Framework for Predictive Reasoning with Interacting Trajectories

arXiv:2610.20867v1 Announce Type: new Abstract: We present a general declarative framework for anticipatory reasoning about interactive motion in complex dynamic environments. Our focus is on (explain

Are You Sure Your LLM Is Sure? Repairing and Auditing Confidence

arXiv:2610.22139v1 Announce Type: new Abstract: Confidence scores determine whether an LLM answer is accepted, reviewed, or regenerated, yet scalar recalibration can only correct errors visible throug

ARGUS: An Agenda-Driven Framework for Reliable User Simulation

arXiv:2610.21346v1 Announce Type: new Abstract: High-fidelity user simulators are essential for evaluating and training agents in interactive environments. However, current LLM-based simulators strugg

ARIA: Runtime Inspection and Amendment for Multi-Agent Systems

arXiv:2610.20780v1 Announce Type: new Abstract: In LLM-based multi-agent systems (MAS), a local mistake can propagate as other agents build on it, turning a correctable error into a failed task. Diagn

local-aiarxiv-cs-ai

Atomic Proximal Policy Optimization for Electric Robo-Taxi Dispatch and Charger Allocation

arXiv:2502.13392v3 Announce Type: replace Abstract: Pioneering companies such as Waymo have deployed electric robo-taxi services in several U.S. cities. Operating such fleets requires coordinating rid

Audio-Visual Dog Identification and Tracking in Real-World Videos

arXiv:2610.21011v1 Announce Type: new Abstract: Identifying individual dogs from barks in real-world videos remains challenging and largely unexplored. Solving this problem would enable long-term beha

BASIS: Evaluating Belief-Aware Solutions in Interactive Settings beyond Instructions

arXiv:2602.13832v2 Announce Type: replace Abstract: Large language model (LLM) agents are increasingly capable of carrying out complex, long-horizon tasks, yet effective assistance requires more than

BD-HazardVLM: Probing Vision-Language Models for Latent Defensive-Driving Hazards in Bangladesh Road Scenes

arXiv:2610.20627v1 Announce Type: new Abstract: Vision-language models are increasingly used for driving-scene understanding, yet their defensive reasoning under weakly structured Global South traffic

Behavioral Forgetting Is Not Privacy in Machine Unlearning

arXiv:2610.21799v1 Announce Type: new Abstract: Machine unlearning aims to remove targeted information from large language models, but existing evaluations often measure forgetting only on a designate

Beyond Context Length: Characterising the Difficulty of Long-Context Reasoning

arXiv:2610.22067v1 Announce Type: new Abstract: Long-context language models support ever longer context windows, and evaluations typically treat context length as the main indicator of difficulty. Ho

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

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 Pairwise Repulsion: Collective Diversity via Determinant Maximization in Diffusion Sampling

arXiv:2610.22267v1 Announce Type: new Abstract: Strong guidance in text-to-image (T2I) diffusion models concentrates sampling toward high-density modes of the conditional distribution, collapsing inde

researcharxiv-cs-cv

Bias Control and Injection for Multi-Agent Aggregation

arXiv:2610.21290v1 Announce Type: new Abstract: Multi-agent reasoning with large language models (LLMs) raises a central question for collective decision-making: when agents disagree, whose decision s

safetyarxiv-cs-ai

Bias Mitigation in Audio-Enabled LLMs through Adversarial Training and Distillation Methods

arXiv:2610.21763v1 Announce Type: new Abstract: Audio-enabled large language models (AuLLMs) allow users to interact with them simply by talking to them, without the need for an intermediate transcrip

safetyarxiv-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

Bridging the Markerless Tracking Validation Gap: Intraoperative X-ray Workflow Integration

arXiv:2610.21696v1 Announce Type: new Abstract: Markerless intraoperative tracking of spinal anatomy via RGB-D sensors is a promising alternative to invasive bone-anchored fiducials, yet no existing c

researcharxiv-cs-cv

Can AI Forecast the Extremes? Evaluating Probabilistic Weather Models on Tropical Cyclones

arXiv:2610.22077v1 Announce Type: new Abstract: Weather prediction is undergoing an important shift, with data-driven AI models outperforming leading numerical weather prediction systems on average at

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 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

ChronoSheaf: Joint Spatio-Temporal Spectral Filtering on Cellular Sheaves

arXiv:2610.21958v1 Announce Type: new Abstract: Sheaf neural networks generalize graph neural networks by assigning each edge a learned linear restriction map that specifies how the local representati

local-aiarxiv-cs-lg

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

Comfortably Stuck: Evaluation Pitfalls in Bench2Drive's Closed-Loop Protocol

model-releasesarxiv-cs-ro

arXiv:2610.21741v1 Announce Type: new Abstract: Closed-loop evaluation is widely regarded as a more faithful way to assess end-to-end (E2E) driving models than open-loop evaluation, and Bench2Drive, b

Tutorials

Complete or Sparse: A Tale of Two Identifiabilities

arXiv:2610.20851v1 Announce Type: cross Abstract: Understanding when neural networks learn interpretable representations is central to mechanistic interpretability. We study this through identifiabili

tutorialsarxiv-cs-lg

Constrained Multi-Agent Reinforcement Learning in Imagination

arXiv:2610.21319v1 Announce Type: new Abstract: Predicting cost in a multi-agent world model moves most constrained policy updates into imagination: the stronger model-free baseline needs 10 to 20 tim

Cost-Efficient RAG for Entity Matching with LLMs: A Blocking-based Batch Processing Framework

arXiv:2602.05708v2 Announce Type: replace-cross Abstract: Large language models (LLMs) offer a compelling approach to entity matching (EM) in label-scarce settings, yet their matching quality is sensi

CoSTA: Compressed Speech Token Adaptation for Efficient Spoken Dialogue Models

arXiv:2610.21143v1 Announce Type: cross Abstract: Spoken Dialogue Models (SDMs) typically share a speech-token space for generation and synthesis, leading to long autoregressive sequences and costly i

researcharxiv-cs-ai

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

researcharxiv-cs-ai

CoTS: Competitive Token Selection for Latent Reasoning in Large Language Models

arXiv:2610.20642v1 Announce Type: cross Abstract: Recent latent reasoning methods move beyond discrete Chain-of-Thought (CoT) by replacing sampled tokens with continuous soft embeddings or hidden stat

researcharxiv-cs-ai

CQDC-Warp: GPU-Accelerated Differentiable Quasi-Dynamic Simulation for Contact-Rich Manipulation

model-releasesarxiv-cs-ro

arXiv:2610.21349v1 Announce Type: new Abstract: Efficient synthesis of contact-rich manipulation trajectories is essential for downstream robot learning. Gradient-based planning offers a promising app

Cross-Embodiment Causal Transfer from Human Videos to Robot Manipulation

arXiv:2610.21798v1 Announce Type: cross Abstract: Scaling robot manipulation models requires large amounts of interaction data, yet collecting diverse real-robot experience remains costly. Human manip

local-aiarxiv-cs-ai

DeciCAD: Harness-Grounded Learning of Action Policies for CAD Agents

arXiv:2610.21755v1 Announce Type: new Abstract: Large Language Model agents operate through closed-loop action policies whose decision space is defined by an agent harness. We investigate how this ope

safetyarxiv-cs-ai

Decoding What iOS Location Services Send to Apple: An LLM Is an Unreliable Analyst but a Useful Toolmaker

arXiv:2610.21597v1 Announce Type: cross Abstract: Reverse engineering the data formats used by mobile software is skilled and slow, and using AI to assist with it is attractive. We evaluate this for t

Decoupled Safety Control: A Safety-Control Algorithm for Training-Free Safety Guidance

arXiv:2610.21569v1 Announce Type: new Abstract: Diffusion models achieve strong performance in text-to-image generation, but they can still produce unsafe content. Training-free safety guidance offers

safetyarxiv-cs-cv

DeepUnfolding_Agent: A Classical_Quantum Adaptive Control API

arXiv:2610.20615v1 Announce Type: new Abstract: Adaptive optimization workflows in machine learning, federated learning, quantum machine learning, and hybrid classical quantum systems often embed cont

DeFlow: Decoupling Behavior-Prior Modeling and Value Maximization for Offline Policy Extraction

arXiv:2601.10471v3 Announce Type: replace Abstract: We present DeFlow, a decoupled offline RL framework that leverages flow matching to faithfully capture complex behavior manifolds. Optimizing genera

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

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

DK-VLM: Geometry as Position for Spatial Reasoning in Vision-Language Models

arXiv:2610.22356v1 Announce Type: new Abstract: Vision-language models still struggle to understand 3D spatial relations across views and update spatial judgments as the observer moves. A common appro

researcharxiv-cs-cv

Tutorials

Do VLAs Really Follow Instructions? Diagnosing How-Level Instruction Following in Vision-Language-Action Models

arXiv:2610.21251v1 Announce Type: new Abstract: Vision-language-action (VLA) models are expected to follow instructions like their language backbones, yet prior work has focused on What-level instruct

tutorialsarxiv-cs-cv