Search: “reasoning”

Schrodinger's Cat: Probabilistic Representation and Prediction of Potential Scene Kinematics

arXiv:2607.25984v1 Announce Type: new Abstract: Predicting how a scene may evolve from partial observations requires reasoning about multiple possible futures rather than committing to a single trajec

researcharxiv-cs-cv

29 Jul 2026

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Model Releases

Sharpness-aware Model Merging with Salience Recovery for LLM-based Cross-Domain Sequential Recommendation

DGX agent

arXiv:2607.25366v1 Announce Type: cross Abstract: LLM-based Cross-Domain Sequential Recommendation (CDSR) leverages LLMs to enhance target performance via deep semantic reasoning, alleviating the depe

model-releasesarxiv-cs-lg

29 Jul 2026

Untangling Co-Drift: Proactive Multi-Intent Failure Prediction and Root-Cause Disambiguation for Self-Driving Networks

model-releasesarxiv-cs-lg

arXiv:2607.25989v1 Announce Type: cross Abstract: The vision of self-driving networks that monitor, reason, and act upon themselves with minimal human intervention relies on tightly coupled monitoring

29 Jul 2026

A New Role for Relevance: Guiding Corpus Interaction in Agentic Search

arXiv:2607.24223v1 Announce Type: new Abstract: Relevance is a query-dependent estimate of whether a document or excerpt contains useful evidence. Existing retrieval agents use relevance to select top

agentsarxiv-cs-cl

ANSR-DT: A Neuro-Symbolic Framework for Adaptive and Explainable Digital Twins

arXiv:2501.08561v5 Announce Type: replace Abstract: Digital twins are increasingly used to monitor and optimize industrial systems, yet many existing frameworks remain difficult to interpret, slow to

CausAdv: A Causal-based Framework for Detecting Adversarial Examples

arXiv:2411.00839v4 Announce Type: replace-cross Abstract: Deep learning has led to tremendous success in computer vision, largely due to Convolutional Neural Networks (CNNs). However, CNNs have been s

CausalGate: Causal Importance Distillation for Transformer Module Pruning

arXiv:2607.22720v1 Announce Type: cross Abstract: Existing adaptive inference methods for Large Language Models rely on observational heuristics, such as hidden-state similarity or activation magnitud

ConsistencyGate: Preventing Memory Contamination in LLM Agents via Self-Consistency Admission Control

arXiv:2607.22962v1 Announce Type: new Abstract: LLM agents that operate over many turns accumulate facts in an external memory store and reuse them as premises for downstream reasoning. A hallucinated

Local Ai

CONSISTRE: A Unified Consistency-Aware Framework for Document-Level Relation Extraction with Large Language Models

arXiv:2607.24312v1 Announce Type: new Abstract: Document-level relation extraction (DocRE) aims to extract relations among multiple entities across extended contexts while maintaining consistency acro

local-aiarxiv-cs-cl

CRAFT: Learn the Schema, Execute the Plan

arXiv:2607.22642v1 Announce Type: new Abstract: Enterprise coding agents translate natural-language analytical requests into executable code over proprietary APIs, schemas, and metric definitions. Yet

DICA: Dual-Indicator Guided Contrastive Alignment in Multimodal Large Language Models

arXiv:2607.23944v1 Announce Type: new Abstract: Human visual reasoning typically follows a coarse-to-fine attention process, starting from global scene understanding and gradually focusing on question

Explaining BiomedCLIP with Weighted Banzhaf Interactions Supported by Tree-Gram Parsing

arXiv:2607.23368v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) are demonstrating significant capabilities in medical tasks like radiology analysis, yet providing faithful and interpre

Hybrid Advantage Estimation with Unified Critic for VLM Agentic Reinforcement Learning

arXiv:2607.23605v1 Announce Type: new Abstract: Large Vision-Language Models (VLMs) now act as agents in interactive environments, where success requires coherent reasoning and decision-making across

agentsarxiv-cs-ai

Language-Routed RAG and Direct Option Scoring for Multilingual Financial QA: DS@GT at FinMMEval

arXiv:2607.22841v1 Announce Type: cross Abstract: We present DS@GT's submission to FinMMEval 2026 Task 1, a multilingual financial exam question answering benchmark spanning English, Spanish, Greek, C

Making Mathematical Knowledge Explainable, Accessible and Interoperable Through Large Language Model Integration

arXiv:2607.24512v1 Announce Type: new Abstract: Mathematical models are central to formalizing research problems, yet their documentation often falls short of FAIR principles. Knowledge bases such as

Modeling Memory-Dependent Reliability of LLMs: A Hidden Markov Model

arXiv:2607.22951v1 Announce Type: cross Abstract: Reliability assessment of large language models (LLMs) seeks to estimate the probability that a model produces correct responses under a specified ope

Novel Claim or Deja Vu? Rethinking 'Contamination-Free'' Dynamic Evaluation for Multimodal Automated Fact-Checking

arXiv:2607.23514v1 Announce Type: cross Abstract: Multimodal automated fact-checking (MAFC) verifies claims by retrieving and reasoning over external evidence. However, most existing static benchmarks

On the Impossibility of Unbiased and Length-Invariant Policy Optimization with Outcome Rewards

model-releasesarxiv-cs-lg

arXiv:2607.23364v1 Announce Type: new Abstract: Group Relative Policy Optimization (GRPO) is the dominant reinforcement learning algorithm for training reasoning capabilities in large language models,

SQBench: A Benchmark for Evaluating Task Delivery by Language-Model Agents in Production-Oriented Workflows

arXiv:2607.23123v1 Announce Type: new Abstract: Existing evaluations of large language models cover knowledge, reasoning, coding, and tool use, but they rarely treat a verifiable deliverable produced

Task-Conditional Faithfulness Auditing of Multimodal LLMs for Grid Diagnosis

arXiv:2607.24539v1 Announce Type: new Abstract: Multimodal large language models (LLMs) can combine topology, measurements, and incident text for grid diagnosis, yet answer accuracy does not establish

TextRich: A Multi-Domain Benchmark for Detecting AI-Generated Text-Rich Images from GPT-Image-2

arXiv:2606.19259v2 Announce Type: replace-cross Abstract: Text-rich images often contain privacy-sensitive, transactional, or decision-relevant information. As recent multimodal image generation model

The Gate Always Closes: On Injecting Auxiliary Signals into Frozen Vision-Language Models

model-releasesarxiv-cs-cv

arXiv:2607.23335v1 Announce Type: new Abstract: Auxiliary signal pathways in VLMs are routinely fitted with learnable gates so the optimiser can decide how much of the signal to admit. We find that th

Tokengeist: Multi-Turn Attribution Tracing in Agentic Conversations

arXiv:2607.22610v1 Announce Type: new Abstract: When a language model produces a response in a multi-turn conversation, which tokens from prior turns shaped that answer, and how did those dependencies

Analysing Self-Harm Representations in Language Models: a Cross-Architecture Study

arXiv:2607.21988v1 Announce Type: new Abstract: Self-harm content is particularly challenging to detect using NLP techniques, and is also a high-stakes task which requires the highest accuracy to enab

Enjoy Your Talk: A Human-Centered Benchmark for Multi-Turn Dialogue with Decoupled User Simulation, Target Modeling, and Judging

arXiv:2607.10428v2 Announce Type: replace Abstract: Evaluating large language models (LLMs) as multi-turn conversational partners requires probing capabilities that single-turn benchmarks miss: person

Tutorials

Humanly: A Configurable and Traceable Environment for Human-AI Collaborative Writing

arXiv:2607.21758v1 Announce Type: new Abstract: Teachers, conference chairs, and public readers all judge writing from limited evidence, seeing only a finished document and not the process that produc

tutorialsarxiv-cs-cl

Industrial Tokenization for LLM-Based Health Intelligence: A Federated Architecture for Industrial Evidence Integration

arXiv:2607.22153v1 Announce Type: cross Abstract: Industrial health management increasingly relies on heterogeneous information sources, including condition monitoring systems, supervisory control and

agentsarxiv-cs-lg

Looped Latent Attention: Cross-Loop KV Compression for Looped Transformers

arXiv:2607.15456v2 Announce Type: replace-cross Abstract: Looped, weight-tied Transformers reduce parameters by reusing a single block, but decoding still stores a separate K/V cache for every recurre

safetyarxiv-cs-cl

The Hard Decision Layer: Evidence for Committed Inference in Transformers

arXiv:2607.21613v1 Announce Type: cross Abstract: We investigate where and how transformer-based language models commit to predictions in multiple-choice question answering. We identify the _Hard Deci

3D-Aware VLMs with Implicit and Explicit Geometries

arXiv:2607.21595v1 Announce Type: cross Abstract: Despite rapid progress, most existing vision-language models (VLMs) built from 2D visual inputs often struggle when handling various 3D tasks that req

CRAG-MM-Diagnostics: Enabling Stage-Wise Analysis of Knowledge-Intensive VQA

arXiv:2607.21155v1 Announce Type: cross Abstract: Knowledge-Intensive Visual Question Answering (KI-VQA) benchmarks evaluate Vision-Language Models (VLMs) as multimodal knowledge assistants by requiri

EmoAgent-R1: Towards Multimodal Emotion Understanding with Reinforcement Learning-based Dynamic Agent Specialization

arXiv:2607.21013v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have achieved impressive performance in multimodal emotion recognition (MER) tasks and lifted MER to a new leve

EvoSQL: Memory-Augmented Critic-Generator Co-Evolution for Text-to-SQL

arXiv:2607.20489v1 Announce Type: new Abstract: Text-to-SQL has advanced rapidly with large language models, but complex database queries still require reasoning beyond one-shot generation, including

Tutorials

Leveraging Biokinetic Knowledge Priors for Data-Scarce Bioprocess Modeling

arXiv:2607.20539v1 Announce Type: cross Abstract: While deep learning has accelerated drug discovery, its impact on biomanufacturing has been considerably more limited. The reason is data scarcity. Bi

tutorialsarxiv-cs-ai

MiniCache: Reusable Program Caching with Small Model Interfaces for Efficient LLM Inference

arXiv:2607.20507v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for program-aided reasoning, agentic decision making, and structured task execution, but these applic

agentsarxiv-cs-ai

Multi-turn RL with Structural and Performance Aware Rewards for CUDA Kernel Generation

arXiv:2607.20908v1 Announce Type: cross Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has emerged as a powerful technique to enhance the reasoning capacity of LLMs for optimized code

Multimodal CoLRAG-TF: Triple-Filtered Retrieval for Complex PDFs

model-releasesarxiv-cs-lg

arXiv:2607.20517v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) over heterogeneous PDF collections remains challenging due to multimodal content, domain-specific terminology, and

OpenForgeRL: Train Harness-native Agents in Any Environment

arXiv:2607.21557v1 Announce Type: new Abstract: Modern AI agents rely on elaborate inference harnesses such as Claude Code, Codex, and OpenClaw to drive multi-turn reasoning, tool use, and access to e

Optimizing Hypergraph-Based RAG: Toward Better Fact Extraction and Chunk Retrieval

arXiv:2607.20506v1 Announce Type: new Abstract: GraphRAG enables deeper reasoning by structuring knowledge as graphs but struggles with n-ary facts. HyperGraphRAG uses hypergraphs for richer semantics

Out of Sight, Still in Mind: Token Compression for Omni-LLMs

arXiv:2607.21179v1 Announce Type: new Abstract: The goal of this paper is to reduce the input token cost of Omni-modal large language models (Omni-LLMs) at inference time. Omni-LLMs reason jointly ove

researcharxiv-cs-cv

Representing Entity Importance in AI Knowledge Systems: A Dual-Signal Framework of Audience Evaluation and Structural Authority

arXiv:2607.20925v1 Announce Type: new Abstract: AI knowledge systems require representations of entity importance for retrieval, recommendation, evidence selection, and knowledge-intensive reasoning.

RUMBA: Russian User Memory Benchmark

arXiv:2607.21447v1 Announce Type: cross Abstract: The ability to handle long-term memory in LLMs is becoming increasingly critical, yet existing benchmarks remain English-centric and rely on aggregate

SAGE: A Socially-Aware Generative Engine for Heterogeneous Multi-Agent Navigation

arXiv:2607.16619v2 Announce Type: replace Abstract: Safe and socially compliant navigation in open human-robot environments requires robots to reason about heterogeneous participants with different dy

safetyarxiv-cs-ro

Applications

Scaling Up Formal Representation of Clinical Trial Protocols in Ensemble Logic Using LLMs: A Preliminary Study

arXiv:2607.21307v1 Announce Type: cross Abstract: The reliance on unstructured free text for documenting clinical trial protocols creates a significant barrier to automated reasoning, cohort discovery

applicationsarxiv-cs-ai

Show, Don't Tell: Evaluating Spatial Cognition in Generative Pixels Rather Than LLM Text

model-releasesarxiv-cs-cv

arXiv:2607.21072v1 Announce Type: new Abstract: Spatial intelligence is essential for agents to move from static semantic understanding toward interacting with the physical world. Many spatial tasks a

Vision-Language-Policy Model for Dynamic Robot Task Planning

arXiv:2512.19178v2 Announce Type: replace-cross Abstract: Bridging the gap between natural language commands and autonomous execution in unstructured environments remains an open challenge for robotic

Local Ai

AdaHome: An Adaptive Smart Home Assistant using Local Small Language Models

arXiv:2607.18034v2 Announce Type: replace Abstract: Smart home assistants interpret a wide range of user commands, from explicit device control to underspecified and preference dependent requests. Whi

local-aiarxiv-cs-ai

23 Jul 2026

Euclean: Automated Geometry Problem Formalization with Unified Verification in Lean

arXiv:2607.19374v1 Announce Type: new Abstract: Recent formal reasoning systems have reached IMO-level performance, yet they leave a fragmented landscape: algebra and number theory are handled in Lean