Search: “models”

Clarification Is Not Enough: Post-Clarification Answering Remains the Bottleneck in Multi-Turn QA

arXiv:2605.25204v1 Announce Type: new Abstract: Pluralistic alignment requires systems to adapt to diverse user values, communication styles, and contextual assumptions. We believe that a foundational

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Research

Clarify, Abstain or Answer? Strategising in Conversation with Belief-Augmented Generation

DGX agent

arXiv:2605.25831v1 Announce Type: cross Abstract: Large language models (LLMs) define a distribution over text, which can be viewed as a probabilistic representation of uncertainty: sampling K respons

researcharxiv-cs-ai

26 May 2026

Complement Submodular Information Measures for Balanced and Robust Data Selection

arXiv:2605.24779v1 Announce Type: cross Abstract: Submodular optimization has become a fundamental paradigm for data selection, retrieval, summarization, and representation learning due to its ability

Applications

ConceptM^3oE: Concept-Guided Multimodal Mixture of Experts for Interpretable Computational Pathology

arXiv:2605.24399v1 Announce Type: new Abstract: Healthcare models are transitioning from unimodal prediction toward multimodal reasoning over heterogeneous diagnostic inputs. In computational patholog

applicationsarxiv-cs-ai

Critical Organization of Deep Neural Networks, and p-Adic Statistical Field Theories

arXiv:2601.19070v2 Announce Type: replace Abstract: We rigorously study the thermodynamic limit of deep neural networks (DNNS) and recurrent neural networks (RNNs), assuming that the activation functi

CSP-Atlas: Concept-Specific Neural Circuits in a Sparse Python Transformer

arXiv:2605.24603v1 Announce Type: new Abstract: A sparse 8-layer code transformer develops dedicated neural circuitry for every Python construct tested, and that circuitry is organised by a clean comp

CUA-Gym: Scaling Verifiable Training Environments and Tasks for Computer-Use Agents

arXiv:2605.25624v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) has driven breakthroughs in domains such as math, tool-use, and software engineering, yet its exte

CurveRL: Principled Distribution-Aware Context Reweighting for LLM Reasoning

arXiv:2605.24331v1 Announce Type: new Abstract: Context or prompt-level reweighting has emerged as a central algorithmic lever in Reinforcement Learning with Verified Rewards (RLVR) for improving the

Agents

DemoEvolve: Overcoming Sparse Feedback in Agentic Harness Evolution with Demonstrations

arXiv:2605.24539v1 Announce Type: new Abstract: Agent harness evolution improves frozen language-model agents by modifying the executable structures around them. We study this paradigm as a form of sa

agentsarxiv-cs-ai

Deployment-complete benchmarking

arXiv:2605.25997v1 Announce Type: new Abstract: Benchmarks increasingly guide deployment, procurement and scientific screening, yet a score supports only the response it records, not necessarily the d

Direct Preference Optimization for English-Mandarin Code-Switching Speech Recognition in Audio LLMs

arXiv:2605.23975v1 Announce Type: new Abstract: Audio large language models (Audio LLMs) exhibit systematic failures in transcribing code-switching speech despite strong multilingual capabilities. Foc

DisDop: Distillation with Domain Priors for Open-Vocabulary Aerial Object Detection

arXiv:2605.24639v1 Announce Type: cross Abstract: With the widespread application of drones in recent years, object detection of aerial images has attracted increasing attention, especially open-vocab

safetyarxiv-cs-ai

DVAO: Dynamic Variance-adaptive Advantage Optimization for Multi-reward Reinforcement Learning

arXiv:2605.25604v1 Announce Type: new Abstract: Reinforcement Learning has become a standard paradigm for aligning Large Language Models with human intent and task requirements. While Group Relative P

DynaPURLS: Dynamic Refinement of Part-Aware Representations for Skeleton-Based Zero-Shot Action Recognition

arXiv:2512.11941v2 Announce Type: replace-cross Abstract: Zero-shot skeleton-based action recognition (ZS-SAR) is fundamentally constrained by prevailing approaches that rely on aligning skeleton feat

Efficient Benchmarking Is Just Feature Selection and Multiple Regression

arXiv:2605.25773v1 Announce Type: cross Abstract: Efficient benchmarking techniques aim to lower the computational cost of evaluating LLMs by predicting full benchmark scores using only a subset of a

EMA-Nesterov: Stabilizing Nesterov's Lookahead for Accelerated Deep Learning Optimization

arXiv:2605.25395v1 Announce Type: new Abstract: Lookahead-based acceleration methods, such as Nesterov's momentum, are widely used in optimization, but they often become unreliable in deep learning tr

Emission-Aware Reinforcement Learning for Sustainable Electric Vehicle Charging and Carbon Dioxide Reduction Under Varying Renewable Penetration

arXiv:2605.24543v1 Announce Type: new Abstract: The rapid growth of Electric Vehicle (EV) adoption challenges power distribution networks through peak load spikes, voltage instability, and transformer

End-to-End Intracortical Speech Decoding from Neural Activity

arXiv:2605.24313v1 Announce Type: new Abstract: Current high-performing intracortical speech neuroprostheses achieve low word error rates but typically rely on external language models during inferenc

researcharxiv-cs-cl

Applications

Equip Pre-ranking with Target Attention by Residual Quantization

arXiv:2509.16931v3 Announce Type: replace-cross Abstract: The pre-ranking stage in industrial recommendation systems faces a fundamental conflict between efficiency and effectiveness. While powerful m

applicationsarxiv-cs-ai

EVA: Accelerating LLM Decoding via an Efficient Vector Quantization Architecture

arXiv:2605.24144v1 Announce Type: cross Abstract: Large Language Models (LLMs) have achieved impressive performance across diverse domains but remain inefficient during the autoregressive decoding pha

researcharxiv-cs-lg

EvoEGF-Mol: Evolving Exponential Geodesic Flow for Structure-based Drug Design

arXiv:2601.22466v2 Announce Type: replace Abstract: Structure-Based Drug Design (SBDD) aims to discover bioactive ligands. Conventional approaches construct probability paths separately in Euclidean a

Explore Before You Solve: The Speed--Depth Trade-off in Epistemic Agents for ARC-AGI-3

arXiv:2605.25931v1 Announce Type: new Abstract: We systematically investigate all 25 public ARC-AGI-3 games and find that every one is reachable through non-intelligent strategies: 10 in a single blin

Extending Embodied Question Answering from Perception to Decision

model-releasesarxiv-cs-ro

arXiv:2605.25813v1 Announce Type: new Abstract: Embodied Question Answering (EQA) connects perception, reasoning, and interaction within embodied environments. However, existing datasets and benchmark

Tutorials

Factorize to Generalize: Retrieval-Guided Invariant-Dynamic Decomposition for Time Series Forecasting

arXiv:2605.24911v1 Announce Type: cross Abstract: Time series foundation models (TSFMs) have recently achieved strong zero-shot forecasting performance through large-scale pretraining and retrieval-au

tutorialsarxiv-cs-ai

Faithfulness as Information Flow: Evaluating and Training Faithful Chain-of-Thought Reasoning

arXiv:2605.24286v1 Announce Type: cross Abstract: Chain-of-thought (CoT) reasoning is useful for monitoring language models only when the reasoning trace faithfully reflects the computation that produ

False Fixed Points: Kantian Feedback, Stable Miscalibration, and Representational Compression in LLMs

arXiv:2510.14925v4 Announce Type: replace Abstract: High-confidence errors in large language models are often treated as fragile failures. We study an alternative: some errors may be false fixed point

local-aiarxiv-cs-ai

Feature Resemblance: Towards a Theoretical Understanding of Analogical Reasoning in Transformers

arXiv:2603.05143v3 Announce Type: replace Abstract: Understanding reasoning in large language models is complicated by evaluations that conflate multiple reasoning types. We isolate analogical reasoni

researcharxiv-cs-cl

FLOATBench: A Dataset and Benchmark for Floating Offshore Wind Turbine Tower Fatigue

arXiv:2605.25717v1 Announce Type: new Abstract: Most of the world's offshore wind resource lies in waters too deep for fixed-bottom foundations, making floating offshore wind turbines (FOWTs) essentia

From Automation to Collaboration: Human-in-the-Loop Methods for Safe and Trustworthy NLP

arXiv:2605.25226v1 Announce Type: new Abstract: Large language models are widely deployed in high-stakes NLP tasks, yet risks such as bias, hallucination, adversarial vulnerability and unreliable gene

From Facts to Insights: A Persona-Driven Dual Memory Framework and Dataset for Role-Playing Agents

arXiv:2605.25693v1 Announce Type: new Abstract: While role-playing agents excel in short-term interactions, long-term conversations overwhelm context windows, motivating external memory frameworks. Cu

Future-KL Regularized GRPO: Process-Level Credit Assignment from f-Divergence Regularization

arXiv:2601.10201v2 Announce Type: replace-cross Abstract: Group Relative Policy Optimization (GRPO) is widely used for critic-free Large Language Model (LLM) post-training, but its KL regularization i

local-aiarxiv-cs-ai

Geometric Evolution Maps: Extracting Stable Concept Probes from Transformer Residual Streams

arXiv:2605.25848v1 Announce Type: cross Abstract: Concept probes extracted from transformer residual streams are only as reliable as the layer from which they are extracted. The common practice of pro

researcharxiv-cs-ai

GeoSVG-RL: Geometry-Aware Reinforcement Learning for Layout-Constrained Text-to-SVG Diagram Generation

arXiv:2605.25447v1 Announce Type: new Abstract: Generating structured, editable diagrams remains a significant challenge for contemporary large language models, despite their proficiency in general-pu

GroupTravelBench: Benchmarking LLM Agents on Multi-Person Travel Planning

arXiv:2605.25200v1 Announce Type: new Abstract: Travel planning is a realistic task for evaluating the planning and tool-use abilities of LLM agents. However, existing benchmarks typically assume only

Guided Flow Matching for Forward and Inverse PDE Problems with Sparse Observations: Algorithm and Theory

arXiv:2605.25509v1 Announce Type: cross Abstract: Reconstructing PDE solutions from sparse observations is a core challenge in scientific computing. We present FM4PDE, a flow-matching generative frame

Hera: Learning Long-Horizon Coordination for Device-Cloud Collaborative LLM Agents

arXiv:2605.24598v1 Announce Type: new Abstract: Large language model (LLM) agents excel at solving complex long-horizon tasks through autonomous interaction with environments. However, their real-worl

local-aiarxiv-cs-ai

HiGraph: A Large-Scale Hierarchical Graph Dataset for Malware Analysis

arXiv:2509.02113v2 Announce Type: replace-cross Abstract: The advancement of graph-based malware analysis is critically limited by the absence of large-scale datasets that capture the inherent hierarc

How Many Tools Should an LLM Agent See? A Chance-Corrected Answer

arXiv:2605.24660v1 Announce Type: cross Abstract: Before an LLM agent can use a tool, a retrieval system must decide which candidate tools to show to the agent. How long should that shortlist be? Show

IterInject: Indirect Prompt Injection Against LLM Agents via Feedback-Guided Iterative Optimization

arXiv:2605.24659v1 Announce Type: new Abstract: LLM-based agents are increasingly deployed for complex tasks requiring planning, tool use, and interaction with external services. Their reliance on unt

Keep the Proof State Live: Snapshotting for Efficient Tactic Search in Lean 4

arXiv:2605.25556v1 Announce Type: cross Abstract: Automated theorem proving systems built on Lean 4 increasingly rely on parallel tactic search over partially specified proofs, such as those generated

Kolmogorov-Arnold Fourier Networks

arXiv:2502.06018v3 Announce Type: replace-cross Abstract: Although Kolmogorov-Arnold-based interpretable networks (KANs) possess strong theoretical expressiveness, they suffer from severe parameter ex

Lngram: N-gram Conditional Memory in Latent Space

arXiv:2605.24869v1 Announce Type: new Abstract: Sequence modeling requires both compositional reasoning and local static knowledge retrieval, yet standard Transformers handle both through dense comput

local-aiarxiv-cs-cl

Applications

LWM-CDE: A Representation Space for Wireless Data Reasoning and Transferability

arXiv:2605.24077v1 Announce Type: cross Abstract: Machine learning deployments in real-world wireless communication tasks face significant generalization challenges due to location and environment-spe

applicationsarxiv-cs-lg

Measuring Reasoning Quality in LLMs: A Multi-Dimensional Behavioral Framework

arXiv:2605.24661v1 Announce Type: new Abstract: LLMs have achieved remarkable success in complex reasoning tasks, yet current evaluation approaches predominantly rely on final-answer correctness, offe

Memory-Induced Tool-Drift in LLM Agents

arXiv:2605.24941v1 Announce Type: cross Abstract: Modern LLM agents combine long-term memory for personalization with tool-calling interfaces for taking actions in the world -- a combination underpinn

MIND: Multi-Scale Intent Diffusion for Text-Driven Physics-Based Humanoid Control

model-releasesarxiv-cs-ro

arXiv:2605.26006v1 Announce Type: cross Abstract: Enabling physics-based humanoids to execute diverse behaviors from high-level textual commands remains a significant challenge. Existing methods typic

MindAlign: Bridging EEG, Vision, and Language for Zero-Shot Visual Decoding

arXiv:2605.24523v1 Announce Type: cross Abstract: Visual decoding from brain signals is a key challenge at the intersection of computer vision and neuroscience, requiring methods that bridge neural re

Tutorials

Multitask learning with semiempirical orbital charges enables sample-efficient MLIPs

arXiv:2605.24073v1 Announce Type: cross Abstract: Machine learning interatomic potentials (MLIPs) require generating computationally expensive, large-scale training datasets to accurately simulate mat

tutorialsarxiv-cs-lg