Search: “reasoning”

EVL-MCoT: Enhanced Vision-Language Multi-CoT for Harmful Meme Detection

arXiv:2607.22016v1 Announce Type: new Abstract: MEMEs are widely used on the internet and often carry strong elements of sarcasm or irony. Understanding their hidden meanings typically requires a join

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Model Releases

IFCLoRA: Topology-Aware Rank Allocation for Parameter-Efficient Fine-Tuning

DGX agent

arXiv:2607.22251v1 Announce Type: new Abstract: Low-Rank Adaptation (LoRA) is a widely used parameter-efficient fine-tuning method for large language models, but its performance depends strongly on ho

model-releasesarxiv-cs-lg

27 Jul 2026

InteractComp: Evaluating Search Agents With Ambiguous Queries

arXiv:2510.24668v2 Announce Type: replace Abstract: Language agents have demonstrated remarkable potential in web search and information retrieval. However, many search-agent benchmarks assume that us

Interior interpretability with attention rollout: contraction and propagation profiles in Transformers

arXiv:2607.22367v1 Announce Type: new Abstract: Feature-attribution methods assign scores relating input variables to a model's output, but do not by themselves characterize how explicitly defined int

researcharxiv-cs-lg

LMEB: Long-horizon Memory Embedding Benchmark

arXiv:2603.12572v5 Announce Type: replace Abstract: Memory embeddings are crucial for memory-augmented systems, such as OpenClaw, but their evaluation is underexplored in current text embedding benchm

Molt: A Scalable PyTorch-Native Training Framework for Agentic Reinforcement Learning

arXiv:2607.21653v1 Announce Type: cross Abstract: Agentic reinforcement learning research is constant algorithm modification, new estimators, new pipeline stages, new rollout schemes, and in mainstrea

safetyarxiv-cs-cl

Moving Beyond Diversity: Visual Token Pruning as Subspace Reconstruction for Efficient VLMs

arXiv:2606.18681v2 Announce Type: replace Abstract: Despite their remarkable performance, Vision Language Models (VLMs) incur substantial computational overhead due to the large number of visual token

researcharxiv-cs-cv

Agents

Multi-Agent Debate and Visual Information Extraction for SeePhys Pro: A 1st-Place Technical Report from ICML 2026 AI4Math Track 3 Challenge

arXiv:2607.21946v1 Announce Type: new Abstract: This technical report presents our approach to Challenge Track~3: SeePhys Pro at the 3rd AI for Math Workshop, where the task is to answer college-level

agentsarxiv-cs-lg

On Improving Faithfulness of Podcasts from Documents

arXiv:2607.21961v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to generate long-form conversational content such as podcasts from textual sources. While these syste

researcharxiv-cs-cl

Opaque Epistemic Mediation: How LLM Deployment Configurations Shape the Validation of Pseudo-Science

arXiv:2607.22513v1 Announce Type: cross Abstract: Commercial large language models are increasingly used as knowledge references, yet their stance on contested scientific claims is neither stable nor

Procedural Knowledge Is Not Low-Rank: Why LoRA Fails to Internalize Multi-Step Procedures

model-releasesarxiv-cs-lg

arXiv:2607.21612v1 Announce Type: cross Abstract: Parameter-efficient fine-tuning methods like LoRA have become the default for adapting large language models, succeeding across instruction following,

Progress Reward Modeling for Robotic Learning: A Comprehensive Survey

arXiv:2607.21655v1 Announce Type: cross Abstract: Robotic learning takes place in dynamic environments with large behavior spaces. A terminal success signal only tells the robot whether the task is co

researcharxiv-cs-cl

Robot Learning to Communicate through Projected Visual Abstractions

arXiv:2607.22434v1 Announce Type: new Abstract: Humans routinely communicate through abstractions of their bodies, including shadows, silhouettes, and reflections. Yet robots remain largely confined t

researcharxiv-cs-ro

Local Ai

SCALE: Self-Supervised Constraint-Aware Layout GEneration for Local P&R DRV Fixing at Advanced Nodes

arXiv:2607.21850v1 Announce Type: new Abstract: As semiconductor manufacturing advances toward sub-2nm nodes, local place-and-route (P&R) design-rule violation (DRV) fixing is increasingly limited by

local-aiarxiv-cs-cv

SceneActBench: Can Agents Act on the 3D Scenes They See?

arXiv:2607.22393v1 Announce Type: cross Abstract: Vision-language model (VLM) agents increasingly use tools to act on 3D scenes rather than only describe them. Existing 3D benchmarks score textual res

Skill Self-Play: Pushing the Frontier of LLM Capability with Co-Evolving Skills

arXiv:2607.22529v1 Announce Type: new Abstract: LLM training is shifting from manual design and annotation to interaction-driven self-evolution. However, existing self-evolutionary methods face a fund

SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images

arXiv:2607.22332v1 Announce Type: new Abstract: Interactive deep image segmentation enables efficient medical image annotation by iteratively refining predictions from user prompts, such as positive a

researcharxiv-cs-cv

The Lift Spectrum: How Measurement-to-Space Adaptivity Shapes Robustness in Image-Free Single-Pixel Sensing

arXiv:2607.22077v1 Announce Type: cross Abstract: Single-pixel sensing encodes a scene as a short sequence of coded measurements, and image-free methods infer the task directly from that sequence. Rem

Time-Reversed Imaging: A Multimodal Benchmark and Framework for Reconstructing Past Human-Environment Interactions

arXiv:2607.22352v1 Announce Type: new Abstract: We introduce time-reversed imaging, a new paradigm that infers what just happened in a scene from fading multimodal traces. Instead of extrapolating or

Agents

VTM-Nav: Harnessing Cross-Episode Experience for Object-Goal Navigation with Hierarchical Visual-Topological Memory

arXiv:2607.14514v2 Announce Type: replace Abstract: Training-free ObjectNav agents increasingly use vision-language models (VLMs), yet typically discard acquired scene knowledge after each request. We

agentsarxiv-cs-cv

Applications

A Graph Neural Network approach to zero-shot Digital Twins

arXiv:2607.20535v1 Announce Type: cross Abstract: Traditional Predictive Digital Twins often remain geometrically rigid, requiring extensive retraining or fine-tuning whenever the underlying physical

applicationsarxiv-cs-ai

Achieving Text-based Person Retrieval with Any Granularity

arXiv:2607.21057v1 Announce Type: new Abstract: Text-based person retrieval faces a critical but under-explored challenge: the inherent uncertainty of query granularity in real-world scenarios. This p

Agents

Agent-Guided Relational Concept Discovery: Toward Interpretable Surgical Margin Assessment

arXiv:2607.21437v1 Announce Type: new Abstract: Deep learning models can effectively use Rapid Evaporative Ionization Mass Spectrometry (REIMS) data for surgical margin assessment. However, their clin

agentsarxiv-cs-ai

AISE-Bench: A Full-Cycle Curated Benchmark for Information Seeking on Academic Knowledge Graphs

arXiv:2607.20498v1 Announce Type: new Abstract: Large language models (LLMs) augmented with tools are emerging as autonomous agents capable of using Web engine, APIs, and code to solve complex, long-h

An Evaluation Framework for Structured Audio Captions Validated by Controlled Perturbations

arXiv:2607.21424v1 Announce Type: new Abstract: Recent advancements in automated audio captioning (AAC) have shifted from monolithic sentence generation toward structured formats that explicitly disen

researcharxiv-cs-cl

ArbiGraph: Arbitrarily Scalable Verifiable Task Graphs for Evaluating Context Management

arXiv:2607.20764v1 Announce Type: new Abstract: We introduce ARBIGRAPH, a benchmark generator for evaluating whether tool-assisted language agents can retain, update, compose, and discard task-relevan

AREX: Towards a Recursively Self-Improving Agent for Deep Research

arXiv:2607.21461v1 Announce Type: new Abstract: Deep research requires agents to find answers that jointly satisfy multiple constraints. Discovering such answers is costly, whereas verifying a candida

AttriMem: Attribution-Guided Process Feedback for Agent Memory Learning

arXiv:2607.21106v1 Announce Type: new Abstract: Effective memory is crucial for LLM agents, yet constructing it effectively remains challenging. A memory-construction policy decides what information t

safetyarxiv-cs-ai

Automated Synthesis and Adversarial Validation of Executable Causal Research Pipelines

model-releasesarxiv-cs-lg

arXiv:2607.21173v1 Announce Type: new Abstract: While automated research systems promise to accelerate empirical analysis, they are prone to silent failures: instances in which analysis code executes

Autonomous disproofs of the sum-product conjecture over mathbb R with GPT-5.5 Pro

arXiv:2607.20525v1 Announce Type: new Abstract: OpenAI's recent disproof of the Erdos unit distance conjecture marked a milestone for AI in mathematics. It also inspired another breakthrough: a human

Autonomous Topology Mutation: Safe Runtime Restructuring for Multi-Agent LLM Systems with Capability, State, and Shadow Invariants

arXiv:2607.20488v1 Announce Type: new Abstract: Multi-agent LLM frameworks typically fix their team topology at boot time. When an individual agent becomes overloaded at runtime, for example by mixing

Axolotl3D: a Unified Framework for Faithful 3D Shape Completion

arXiv:2607.20660v1 Announce Type: new Abstract: Recent 3D generative models produce high-quality geometry from a single image using large-scale priors and diffusion architectures. However, they assume

safetyarxiv-cs-cv

Can Valence Reflect Morality in Natural Language? A Preliminary Annotation Study

arXiv:2607.20461v1 Announce Type: cross Abstract: Present implementations of artificial intelligence (AI) ethics do not adequately take feelings, or affect, into account. If AI should be aligned with

researcharxiv-cs-ai

Capital Markets LLM Reliability Score (CM-LRS): From Plausible to Bankable

arXiv:2607.21340v1 Announce Type: new Abstract: In capital-markets workflows the question is rarely whether a large language model can produce a fluent draft, but whether the draft is bankable: defens

Cautious optimism for deep parameterized quantum circuits

arXiv:2607.21409v1 Announce Type: cross Abstract: A central challenge in quantum machine learning is understanding the scaling behavior of parameterized quantum circuits (PQCs). In particular, it rema

researcharxiv-cs-lg

Local Ai

Concept Concentration for Faithful Representation Intervention

arXiv:2505.18672v2 Announce Type: replace Abstract: Representation intervention aims to localize and modify the representations that encode the underlying concepts in large language models (LLMs) to e

local-aiarxiv-cs-lg

CultureTalk-ID: A Multi-Task Dialogue Benchmark for Cultural Commonsense in Indonesian Local Languages

arXiv:2607.21016v1 Announce Type: new Abstract: Culture is lived through conversation, yet existing Indonesian cultural commonsense benchmarks evaluate LLMs on short and isolated prompts, stripping aw

DFAH-Bench: Benchmarking Observable Agent Instability in Financial Decision-Making

arXiv:2607.20491v1 Announce Type: new Abstract: Standard evaluation benchmarks measure what a tool-using agent decides, not whether it arrives at that decision through the same process each time. We i

Explanation-Based Runtime Verification for Trustworthy ML-driven Optical Networks

arXiv:2607.20675v1 Announce Type: new Abstract: Machine learning (ML) models are increasingly integrated into optical network automation frameworks to support tasks such as failure management, perform

researcharxiv-cs-lg

GeoThreat: Transferable Targeted Adversarial Attacks on Large Vision-Language Models for Remote Sensing Image Interpretation

arXiv:2607.21036v1 Announce Type: new Abstract: Adversarial attacks against large vision-language models (LVLMs) serve as an effective means of assessing their robustness in cross-modal semantic under

researcharxiv-cs-cv

Hybrid MKNF with Classical Negation in the Rule Component

arXiv:2607.21202v1 Announce Type: cross Abstract: Hybrid MKNF knowledge bases under the well-founded semantics integrate Description Logics with Logic Programming. However, they do not support classic

safetyarxiv-cs-ai

HyWorldVLA: A Vision-Language-Action Model with Hybrid World Modeling for Autonomous Driving

arXiv:2607.20988v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models augmented with world modeling represent a promising paradigm for end-to-end autonomous driving. While pixel-level

ImplicitBBQ: Benchmarking Implicit Bias in Large Language Models through Characteristic Based Cues

arXiv:2604.01925v2 Announce Type: replace-cross Abstract: Large Language Models increasingly suppress biased outputs when demographic identity is stated explicitly, yet may still exhibit implicit bias

Is MoE Routing a Huffman Code? Discovering the Frequency-Diversity Law in Chain-of-Thought

arXiv:2607.20427v1 Announce Type: cross Abstract: Mixture-of-Experts architectures have revolutionized scaling, yet the underlying logic of their routing remains a black box. In this paper, we uncover

Learn2Zinc: Fine-tuning Small Language Models for Text-to-Model Translation in MiniZinc

arXiv:2607.20456v1 Announce Type: cross Abstract: Large language models excel at code generation for mainstream programming languages but struggle with rare, domain-specific languages such as MiniZinc

Applications

Learning to Detect UI Principle Violations via Reinforcement Learning

arXiv:2607.20690v1 Announce Type: new Abstract: Small language models and coding agents increasingly generate web front-end code, yet their outputs are typically evaluated primarily for functional cor

applicationsarxiv-cs-cl

MagicMakeup: A Region-Controllable Diffusion Transformer for High-Fidelity Makeup-Transfer

arXiv:2607.20924v1 Announce Type: new Abstract: Makeup-transfer applies the reference makeup to the source face while preserving the source identity. Despite advances in full-face editing by diffusion

Moir: Let the Model Direct Its Own Story for Robust Cross-Domain Knowledge Editing

arXiv:2607.20433v1 Announce Type: cross Abstract: While language models remain frozen at their training state, the world evolves continuously. Knowledge editing has emerged as a key alternative to ful