Search: “benchmark”

Explore More, Drift Less: Outcome-Only Reinforcement Learning Can Suffice for Long-Horizon Interactive Agents

arXiv:2609.01245v1 Announce Type: cross Abstract: Reinforcement learning is a natural way to post-train LLM agents for long-horizon interactive tasks judged only by end-of-task verification, yet a sha

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Exploring Collaboration between a language and a non-language agent

DGX agent

arXiv:2609.00474v1 Announce Type: cross Abstract: LLMs are increasingly deployed as orchestrators that coordinate specialized subagents to solve complex tasks through natural language. However, in man

model-releasesarxiv-cs-ai

2 Sept 2026

FaST: Feature-aware Sampling and Tuning for Personalized Preference Alignment with Limited Data

arXiv:2508.04698v2 Announce Type: replace Abstract: LLM-powered conversational assistants are often deployed in a one-size-fits-all manner, which fails to accommodate individual user preferences. Rece

From Confusion to Clarity: Confusion-Aware Retrieval and Knowledge Injection for Text Classification

arXiv:2609.01564v1 Announce Type: cross Abstract: Large language models (LLMs) struggle to classify text into taxonomies with many semantically similar labels, as the distinctions are domain-specific

From Detection to Refusal: Safer LLMs via Circuit-Guided Weight Scaling

arXiv:2609.00051v1 Announce Type: cross Abstract: Despite extensive alignment efforts, Large Language Models (LLMs) remain vulnerable to generating unsafe content under adversarial prompting, yet the

Applications

From Language to Behavior: Scaling Sequence Transformers for Industrial Recommendation Ranking with Rec-Native Designs

arXiv:2609.01240v1 Announce Type: cross Abstract: Scaling Transformers has driven large gains in language modeling, but transplanting this to behavior-sequence modeling in production ranking is challe

applicationsarxiv-cs-ai

From Saliency to Discriminability: Rank-Preserving Visual Token Pruning for VLM Rerankers

arXiv:2609.00667v1 Announce Type: cross Abstract: Large vision-language models used as listwise rerankers must jointly process visual tokens from tens of candidates per query, making token pruning ess

From Terminology to Diagrams: Visual-Instruction Generation for Scientific Diagram Understanding

arXiv:2609.00948v1 Announce Type: cross Abstract: Vision-language models (VLMs) have demonstrated strong performance in visual question answering with natural images. However, they continue to struggl

Geometry-aware Latent Autoregressive Generative Model for PDEs in Complex Domains

arXiv:2609.00297v1 Announce Type: cross Abstract: Solving multiphysics partial differential equations (PDEs) remains a major challenge in scientific computing, especially for highly complex mum-scale

Group Adaptive Clipping Policy Optimization

arXiv:2609.00444v1 Announce Type: cross Abstract: Group relative policy optimization for reinforcement learning with verifiable rewards (RLVR) typically uses a fixed importance-sampling (IS) ratio cli

HEAL: Hindsight Entropy-Assisted Learning for Reasoning Distillation

arXiv:2603.10359v2 Announce Type: replace Abstract: Distilling reasoning capabilities from Large Reasoning Models (LRMs) into smaller models is typically constrained by the limitations of rejection sa

HitMem: Hierarchical Temporal 3D Memory with Multi-Modal Context-Aware Retrieval for Dynamic Environments

model-releasesarxiv-cs-ro

arXiv:2609.00950v1 Announce Type: new Abstract: Executing long-term tasks in dynamic environments requires embodied agents to maintain robust and adaptive 3D scene representations. However, most exist

Human-AI Co-Interpretation for Responsible AI: A Hermeneutic Perspective

arXiv:2609.00334v1 Announce Type: new Abstract: Across law, education, policy analysis, and public moral argumentation, LLM outputs are being used often for work that requires interpretations to be ju

Hydra: Marker-Free RGB-D Hand-Eye Calibration

arXiv:2504.20584v2 Announce Type: replace-cross Abstract: This work presents an RGB-D imaging-based approach to marker-free hand-eye calibration using a novel implementation of the iterative closest p

I-CARE: Analysis of interference-related phenomena in a controllable, diverse and representative unlearning setting for text-to-image models

arXiv:2609.00003v1 Announce Type: new Abstract: Machine unlearning studies the removal of knowledge from an AI model, making the system forget a concept it previously learned. Despite rapid progress i

InComeS: Integrating Compression and Selection Mechanisms into LLMs for Efficient Model Editing

arXiv:2505.22156v4 Announce Type: replace Abstract: Although existing model editing methods perform well in recalling exact edit facts, they often struggle in complex scenarios that require deeper sem

Intelligent Edge Computing

arXiv:2609.00181v1 Announce Type: cross Abstract: The number of edge devices in large-scale edge systems is rapidly increasing. Edge devices have limited processing power, memory, and network bandwidt

iPINN for Broadband CARS Phase Retrieval: A Framework for Function Approximation and Inverse Modeling Problems in Nonlinear Spectroscopy

arXiv:2609.00883v1 Announce Type: new Abstract: Phase retrieval in broadband coherent anti-Stokes Raman spectroscopy (BCARS) is an ill-posed inverse problem. The Raman-like signal is encoded in the im

ISO-RAG: Isoperimetric Noise Control for Retrieval-Augmented Generation

arXiv:2609.00513v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) mitigates large language models (LLMs) hallucinations, yet conventional dense retrieval struggles with the complex

It Takes Two to Match: Co-Evolving Generative Retriever with Reinforcement Learning

arXiv:2609.00638v1 Announce Type: cross Abstract: Retrieval is the first stage of modern search and advertising systems, selecting a candidate set from a large item universe for downstream ranking and

IT-TextFusion: Iterative Text-Image Interaction with Text-Guided Residual Refinement for Degradation-Aware Image Fusion

arXiv:2609.01092v1 Announce Type: new Abstract: Text-guided image fusion has recently emerged as an effective paradigm for integrating multi-modal information while enabling flexible and task-oriented

Latent Mechanisms of Language Control in Multilingual Language Models

arXiv:2609.00325v1 Announce Type: new Abstract: Multilingual large language models can exhibit unintended code-switching -- unnecessarily alternating between languages during generation. We present a

Learning What to Retain: Gated-Memory Routing for Efficient Collaboration in Multi-Agent LLM Systems

arXiv:2609.00237v1 Announce Type: new Abstract: Large language model (LLM)-based multi-agent systems tackle complex reasoning by orchestrating how multiple agents are configured and how they collabora

agentsarxiv-cs-ai

Lightweight Adaptation of EEG Foundation Models for Stroke Motor Imagery Decoding: Domain Shift and Subject-Level Robustness

arXiv:2609.00282v1 Announce Type: cross Abstract: Motor imagery (MI) electroencephalography (EEG) decoding could support post-stroke rehabilitation, but models developed on healthy cohorts may not tra

Lightweight Interpretable RGB-Guided Hyperspectral Super-Resolution under Real Cross-resolution Misalignment

arXiv:2609.01060v1 Announce Type: cross Abstract: Compact snapshot hyperspectral cameras provide rich instantaneous spectral measurements for ground-level machine vision, but at lower spatial resoluti

Local Reference Geometry Residual Augmentation for Imbalanced Time Series Classification

arXiv:2609.00093v1 Announce Type: new Abstract: Imbalanced time series classification is often addressed by changing the training distribution, objective, logits, or final threshold. These interventio

researcharxiv-cs-lg

Location-Aware Language Models via Secondary Embeddings

arXiv:2609.00454v1 Announce Type: new Abstract: Pretrained transformer-based language models achieve strong performance across a wide range of NLP tasks but remain limited in encoding geo-locational s

safetyarxiv-cs-cl

Long-Horizon State Tracking in LLMs: Executing MD5 through a Deep Sequence of Dependent Tool Calls

arXiv:2609.00012v1 Announce Type: new Abstract: Long-horizon tasks remain uncommon in large language model (LLM) evaluation, and for a reason: when each step depends on the last, per-step accuracy tha

agentsarxiv-cs-ai

LOOMSUM:Weaving Quantitative and Narrative Evidence for Faithful Long Text-Table Summarization

arXiv:2609.00241v1 Announce Type: new Abstract: Long documents often distribute important information across extensive narrative passages and multiple tables, making faithful summarization particularl

researcharxiv-cs-cl

Low-Quality Face Recognition using Center Aligned Representations and Local Margin Constraints

arXiv:2609.01014v1 Announce Type: new Abstract: Low-quality face recognition (LQFR) remains challenging due to the difficulty of matching degraded query (probe) images against low-quality (LQ) enrollm

Local Ai

Make Some Noise: Unsupervised Remote Sensing Change Detection Using Latent Space Perturbations

arXiv:2602.19881v2 Announce Type: replace-cross Abstract: Unsupervised remote sensing change detection (UCD) aims to localise changes between two images of the same region without relying on labelled

local-aiarxiv-cs-ai

MAS-ProVe: Understanding the Process Verification of Multi-Agent Systems

arXiv:2602.03053v2 Announce Type: replace Abstract: Multi-Agent Systems (MAS) built on Large Language Models (LLMs) often exhibit high variance in their reasoning trajectories. Process verification, w

agentsarxiv-cs-ai

MemoryWalker: Stop Training Agents on Contexts They Never Saw

arXiv:2609.00865v1 Announce Type: cross Abstract: Production agent harnesses such as Claude Code and Qwen-Agent compress context during rollout, but training under compression creates a conditioning p

Mind the Rift: Cross-Scale Coupling Mismatch for AI-Generated Video Detection

arXiv:2609.00742v1 Announce Type: new Abstract: As AI video generators achieve cinematic realism, reliable detection becomes essential for safeguarding digital trust. We identify cross-scale coupling

MobileOcc: A Human-Aware Semantic Occupancy Dataset for Mobile Robots

arXiv:2511.16949v2 Announce Type: replace-cross Abstract: Dense 3D semantic occupancy perception is critical for mobile robots operating in pedestrian-rich environments, yet it remains underexplored c

Modeling Information Blackouts in Missing Not-At-Random Time Series Data

arXiv:2601.01480v3 Announce Type: replace-cross Abstract: Traffic forecasting systems rely on fixed sensor networks that frequently exhibit contiguous blackouts. Such outages are usually treated as ig

Monocular Depth Estimation from a Single Image: Progress and Opportunities

arXiv:2609.01172v1 Announce Type: new Abstract: Monocular depth estimation has long stood as a fundamental challenge in computer vision, enabling a wide range of applications including 3D reconstructi

agentsarxiv-cs-cv

MUGEN: Generating Unlearnable Graph Examples for Multiple Learning Tasks

arXiv:2609.00696v1 Announce Type: new Abstract: Graph data across diverse domains can expose valuable relational information to unauthorized representation learning, creating a pressing need for prote

researcharxiv-cs-lg

Multilingual Medical Reasoning for Question Answering with Large Language Models

arXiv:2512.05658v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) with reasoning capabilities have recently demonstrated strong potential in medical Question Answering (QA). Exist

NashDreamer: Model-Based Reinforcement Learning for Zero-Sum Imperfect-Information Games

arXiv:2609.01549v1 Announce Type: new Abstract: Model-based reinforcement learning (MBRL) has achieved remarkable results in single-agent domains, yet its extension to competitive imperfect informatio

Neural means and kernel corrections for operator learning

arXiv:2609.00389v1 Announce Type: new Abstract: We combine neural network means with exact Matern kernel regressions of their residuals and of their learned features, and evaluate the pairing on two p

Neural Symbollic Regression Using Deep Learning and Sparse Modelling

arXiv:2609.01102v1 Announce Type: new Abstract: Symbolic Regression (SR) seeks to find succinct mathematical expressions that represent the fundamental relationships within data, providing interpretab

Neurosymbolics for Data Engineering: Achieving Long Context Token Reduction Without Finetuning

arXiv:2609.00367v1 Announce Type: cross Abstract: Large Language Models are increasingly deployed for sophisticated data engineering tasks such as generating structured queries from natural language,

NewsRECON: News Article Retrieval for Image Contextualization

arXiv:2601.14121v2 Announce Type: replace Abstract: Identifying when and where a news image was taken is crucial for journalists and forensic experts to produce credible stories and debunk misinformat

Nice paper with great insights on improving self-evolving agents. Self-evolving agents fail in three specific ways: 1. Terminal-only feedbac…

Nice paper with great insights on improving self-evolving agents. Self-evolving agents fail in three specific ways: 1. Terminal-only feedback makes it ambiguous which step caused the error. 2. Agents

agentsdair-ai--x

On Synthesis of Metric Interval Temporal Logics

arXiv:2609.01032v1 Announce Type: cross Abstract: Automated mining of formal specifications is vital for verifying real-time systems. However, existing passive learning approaches remain restricted to

On-the-Fly3R: Towards Robust Online 3D Reconstruction with Feed-Forward 3R Models for Large-Scale UAV Scenarios

arXiv:2609.00923v1 Announce Type: new Abstract: While feed-forward 3D reconstruction (3R) offers efficient end-to-end modeling, its application in large-scale UAV mapping is hindered by the prohibitiv

One Policy, Any Budget: Internalizing Budget-Aware Search via Reinforcement Learning

arXiv:2609.00813v1 Announce Type: new Abstract: While reinforcement learning has enabled LLM-based search agents to invoke external tools, existing methods train under fixed budgets and cannot adapt w