Search: “benchmark”

How Can Recommendation Feedback Evolve Agent Memory?

arXiv:2609.37544v1 Announce Type: new Abstract: Content-generation agents continuously receive impressions, clicks, conversions, and negative feedback from recommendation systems, providing real-world

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Imagine3D-LLM: Teaching MLLMs to Imagine 3D Scenes Before Answering

DGX agent

arXiv:2609.38177v1 Announce Type: cross Abstract: Reasoning about the 3D world from multi-view images remains a fundamental challenge for Multimodal Large Language Models (MLLMs). While modern MLLMs h

researcharxiv-cs-cl

30 Sept 2026

ImbalancE: Inference-Time Latent Search Against Degree Imbalance in Link Prediction

arXiv:2609.36996v1 Announce Type: new Abstract: Knowledge Graph Embedding models have been extensively used to learn representations of entities and relations in Knowledge Graphs for predicting missin

Inducing Process Supervision from Outcome-Only Reinforcement Learning

arXiv:2609.36641v1 Announce Type: cross Abstract: Process reward models (PRMs) have become a key component for LLMs, as their step-level feedback supports both post-training and test-time reasoning. H

Inferring Soil Friction Angle from Robot Foot-Ground Force Histories: A Bayesian Inverse Approach to Proprioceptive Soil Sensing

arXiv:2609.36582v1 Announce Type: new Abstract: Foot-ground interaction signals recorded by quadruped robots may enable spatially distributed, in situ characterization of soil strength. As a first ste

researcharxiv-cs-ro

Interactive-Policy Distillation with Bidirectional Propose-and-Verify

arXiv:2609.36546v1 Announce Type: cross Abstract: On-policy distillation (OPD) trains a student model on its self-generated trajectories with dense token-level teacher feedback. However, naive OPD may

InterBias-SV: Compound Conditions in Speaker Verification

arXiv:2609.36500v1 Announce Type: cross Abstract: Speaker verification systems encounter combinations of noise, channel distortion, and changes in speech. Evaluating each condition separately does not

Interpolated Policy Distillation: A Controllable Continuum Between Off-Policy and On-Policy Distillation

arXiv:2609.37170v1 Announce Type: cross Abstract: Off-policy and on-policy distillation have traditionally been formulated as separate paradigms, each favoring a different property of distillation tra

Interpretable intrinsic dimension estimation through componentwise calibration of distance and angle

arXiv:2609.37114v1 Announce Type: new Abstract: DANCo (Dimensionality from Angle and Norm Concentration) jointly calibrates nearest-neighbor distance and angular statistics and consistently reaches st

researcharxiv-cs-lg

Is Human-Readable Text Necessary for Effective LLM Fine-Tuning?

arXiv:2609.35868v1 Announce Type: new Abstract: Is human readability necessary for effective fine-tuning of large language models? We investigate whether model-conditioned training representations can

JointEdit3D: Feed-Forward 3D Scene Editing in a Unified Latent Space

model-releasesarxiv-cs-cv

arXiv:2606.13345v2 Announce Type: replace Abstract: Existing 3D scene editing methods typically rely on per-scene optimization over explicit 3D representations or cascaded edit-and-reconstruct pipelin

Tutorials

KernelOnet: An Interpretable Neural Operator Based on Kernel Functions

arXiv:2609.35938v1 Announce Type: new Abstract: This paper proposes an interpretable neural operator framework, the Kernel Operator Network (KernelOnet), which incorporates kernel functions explicitly

tutorialsarxiv-cs-lg

KT-EGO: A Knowledge Transfer Assisted Efficient Global Optimization Algorithm for Solving High-Dimensional Expensive Black-Box Problems

model-releasesarxiv-cs-lg

arXiv:2609.37473v1 Announce Type: cross Abstract: Many engineering problems involve optimizing a high-dimensional expensive black-box (HEB) design space. To solve such problems efficiently, we propose

Hardware

Label Less, Learn More: Resource-Efficient Active Semi-Supervised Learning for Onboard Satellite Image Annotation

arXiv:2609.37481v1 Announce Type: new Abstract: Large-scale pervasive sensing increasingly relies on high-resolution satellite imagery, yet task-specific onboard vision is constrained by costly annota

hardwarearxiv-cs-cv

LatCom: Cross-Agent Latent Compression for Efficient Multi-Agent Collaboration

arXiv:2609.37017v1 Announce Type: new Abstract: LLM-based multi-agent systems (MAS) increasingly use latent collaboration to avoid the information loss and repeated encoding-decoding overhead of natur

agentsarxiv-cs-cl

Layer-Informed Fine-Tuning via Three-Stage Functional Segmentation of LLMs

arXiv:2609.38027v1 Announce Type: new Abstract: In recent years, the performance of large language models (LLMs) on reasoning tasks has been remarkable, even surpassing human capabilities on various b

researcharxiv-cs-cl

LazySloth: Bounded LLM-based Lazy Tree Search for Fast Long Video Comprehension

arXiv:2609.37426v1 Announce Type: cross Abstract: Modern vision-language models (VLMs) have shown promising results in long-video understanding due to the rich semantic information they can capture. H

Learn from the Gap: Differential-Aware Advantage Pruning with Adaptive Rollout Sampling for GRPO

arXiv:2609.36932v1 Announce Type: new Abstract: Recently, Group Relative Policy Optimization (GRPO) and its variants have been developed for policy optimization and demonstrated notable performance ga

Learning Beyond What You Sample: Off-Policy-Aware Cross-Model Trajectory Exchange for RLVR

arXiv:2609.37868v1 Announce Type: cross Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) methods such as GRPO rely on successful self-generated trajectories, but finite rollout budgets

Learning Causal Normalizing Flows from Incomplete Data via Observed-Data Likelihood

arXiv:2609.37664v1 Announce Type: new Abstract: Causal Normalizing Flows (CNFs) enable causal inference from observational data given the causal structure, but they assume fully observed training data

researcharxiv-cs-lg

Learning Continuous Patient Trajectories from Electronic Health Records

arXiv:2609.36144v1 Announce Type: new Abstract: Electronic health records provide irregular observations of latent patient states that evolve continuously over time. Recent autoregressive models condi

applicationsarxiv-cs-lg

Learning Social Navigation from Internet Videos in the Policy State Space

model-releasesarxiv-cs-cv

arXiv:2609.37476v1 Announce Type: cross Abstract: Training robust social-navigation policies requires simulators with diverse scene layouts, terrain, and human motion, but constructing such environmen

Learning to Explore Hidden Kinematics for Articulated Object Manipulation

model-releasesarxiv-cs-ro

arXiv:2609.36553v1 Announce Type: new Abstract: The kinematics of an articulated object is often ambiguous from vision alone. Interaction resolves the ambiguity, and active perception methods exploit

Learning to Prove, Not Just to Answer: Reinforcement Learning from Formal Verification for Natural-Language Logical Reasoning

arXiv:2609.37203v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed for natural-language logical reasoning, where the final answer is easy to check but the proof beh

researcharxiv-cs-ai

Learning to Recorrupt: Noise Distribution Agnostic Self-Supervised Image Denoising

arXiv:2603.25869v2 Announce Type: replace-cross Abstract: Self-supervised image denoising methods have traditionally relied on architectural constraints, pseudo-pair constructions, or specialized loss

applicationsarxiv-cs-cv

LEGO-Anything: Coding Agents for 3D Scene Reconstruction

model-releasesarxiv-cs-cv

arXiv:2609.36380v1 Announce Type: new Abstract: A 3D scene reconstructed from a single image is most useful when represented not as a rendering or a fixed 3D output, but as an explicit scene program w

Tutorials

LeRF: Learning Reference Coordinate Frames for Perspective Taking Reasoning

arXiv:2609.36219v1 Announce Type: new Abstract: Perspective taking is a fundamental component of spatial intelligence, requiring models interpret spatial relations from a specified viewpoint, such as

tutorialsarxiv-cs-cv

LLMs Learn to Evade Latent Monitors from Prior Feedback Alone

arXiv:2609.36490v1 Announce Type: cross Abstract: Latent space monitors aim to detect undesired behaviors in LLM agents by inspecting an agent's internal activations rather than its outputs. However,

agentsarxiv-cs-ai

Lookahead-R: Budget-Aware Tool Retrieval via Execution-Centric Planning

arXiv:2609.35811v1 Announce Type: cross Abstract: Tool retrieval is a critical bottleneck for LLM-based agents operating over large, heterogeneous API ecosystems. Existing approaches face an inherent

Lost in Conversation or Lost in Translation? Diagnosing Multi-Turn Degradation in RAG

arXiv:2609.36700v1 Announce Type: cross Abstract: When conversing with large language models (LLMs), users often begin with a simple question and build towards a multi-hop question through follow-up t

researcharxiv-cs-ai

Making Duplicate Reimbursement Unrepresentable: A Verified Ethereum E-Invoice System for Humans and AI Agents

arXiv:2609.37819v1 Announce Type: cross Abstract: Electronic invoices are replacing paper invoices worldwide, but today's centralized architectures leave three problems unsolved on the consumption sid

MARCO: Multi-Round Agentic Reinforcement for Conditional Molecular Optimization

arXiv:2609.36683v1 Announce Type: cross Abstract: Molecular optimization is inherently iterative: a candidate is proposed, evaluated against several objectives, and revised while preserving a relation

Med-RADIO: Reducing All Medical Domains Into One via Multi-Teacher Distillation

arXiv:2609.37682v1 Announce Type: new Abstract: The rapid expansion of large-scale medical datasets and computational resources has driven significant progress in medical foundation models. Given the

researcharxiv-cs-cv

Memory Consolidation Flattens the Temporal Shape of User Facts

arXiv:2609.36457v1 Announce Type: new Abstract: Long-term memory systems turn conversations into short stored notes. A note can keep a user fact while losing evidence about whether the fact still hold

MERGE: Multi-LLM Ensemble for Retrieval via Generative Enrichment

arXiv:2609.37574v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly used to enrich user queries in information retrieval (IR) so that a standard retriever such as BM25 can

MERID: Multimodal Exploration via Recursive Self-Improvement Agents for Major Depression Analysis

arXiv:2609.36235v1 Announce Type: new Abstract: Major depressive disorder (MDD) severely impacts daily activities and quality of life. Detecting MDD involves multimodal data, such as interview recordi

agentsarxiv-cs-ai

Meta-SecAlign: Training LLMs against Prompt Injection for Robust Agents

arXiv:2507.02735v4 Announce Type: replace-cross Abstract: Prompt injection attacks, where untrusted data contains an injected prompt to manipulate the system, have been listed as the top security thre

MetaCtrl: Your Large Language Models Can Reason Better and More Concisely with a Metacognitive Controller

arXiv:2609.37304v1 Announce Type: new Abstract: Large reasoning models improve performance on challenging problems by allocating additional computation before answering, but longer reasoning does not

MG-Thinker: Bi-Axial Self-Reflection for Multi-Image Reasoning Grounding

arXiv:2609.37374v1 Announce Type: new Abstract: Reinforcement learning (RL) has recently delivered substantial gains in multimodal reasoning, opening a promising route for fine-grained visual percepti

applicationsarxiv-cs-cv

Mixture of Self-Improving Branches For Agent Harness Optimization

arXiv:2609.37834v1 Announce Type: new Abstract: Harness optimization provides a practical setting for recursive self-improvement (RSI), where agent-generated modifications inform subsequent changes th

MMSkillRisk: Can Agents Stay Safe When Multimodal Skills Become Traps?

arXiv:2609.35912v1 Announce Type: cross Abstract: Agent skills are shareable packages of procedural instructions, tools, and examples. Multimodal skills additionally include visual references that age

Momentum-Coupled Rubric Adaptation for Detailed Image Captioning

arXiv:2609.36893v1 Announce Type: new Abstract: Detailed image captioning requires accurate and comprehensive descriptions of fine-grained visual content, yet caption quality spans factual accuracy, i

Monocular 3D Occupancy Perception for Robots on Sidewalks via Hybrid 2D-3D Learning

arXiv:2606.19122v2 Announce Type: replace Abstract: Sidewalks in the real world are crowded, cluttered, and less structured than roads, making 3D occupancy prediction a key ingredient for the safe nav

agentsarxiv-cs-ro

MoRE: Scaling mixture of experts with hardware-aware low-rank routing

arXiv:2609.36301v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) layers are central to frontier language models, and recent architectures push toward more and smaller experts. In this regime

researcharxiv-cs-ai

MoTIF-X: A Multimodal Tokenized Framework for Interpretable and Extensible Molecular Representation Learning

arXiv:2609.37384v1 Announce Type: new Abstract: Molecular representation learning is central to computer-aided drug discovery. Molecular graphs, SMILES strings, and 3D conformations provide complement

researcharxiv-cs-lg

Multi-Site Real-World Performance of Commercial AI for Pulmonary and Incidental Pulmonary Embolism Detection

arXiv:2609.37750v1 Announce Type: cross Abstract: Pulmonary embolism (PE) is a leading cause of cardiovascular mortality, yet the real-world performance of FDA-cleared AI detection models remains inco

applicationsarxiv-cs-ai

Multi-Task Dynamic Pricing in Credit Market with Contextual Information

model-releasesarxiv-cs-lg

arXiv:2410.14839v5 Announce Type: replace-cross Abstract: We study the dynamic pricing problem faced by a broker seeking to learn prices for a large number of credit market securities, such as corpora

Mutual Information Constrained Chernoff Bottleneck

model-releasesarxiv-cs-lg

arXiv:2609.37994v1 Announce Type: cross Abstract: The classical information bottleneck (IB) measures the relevance of a representation U of X to a target Y by I(U;Y), which does not directly character