Search: “multi-hop”

Reasoning Jury: Multi-Model Consensus for Evaluating Reasoning Traces

arXiv:2608.12585v1 Announce Type: new Abstract: Improving reasoning LLMs requires the ability to judge the quality of long reasoning traces for effective reasoning data curation, strong training signa

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Agents

RippleMem: From Isolated Retrieval to Associative Recollection for Long-Term Agent Memory

DGX agent

arXiv:2608.13334v1 Announce Type: new Abstract: LLM-based agents increasingly rely on external memory to support long-horizon reasoning and interaction. However, the main bottleneck is not simply stor

agentsarxiv-cs-cl

14 Aug 2026

Unified Multi-Dimensional Benchmark for Complex Graph Reasoning in Large Language Models

arXiv:2608.12391v1 Announce Type: cross Abstract: Graph reasoning provides a promising testbed for evaluating the reasoning ability of large language models (LLMs), as graph instances can be programma

When Should Multi-Round RAG Stop? Structured Stopping Judgments and Retrieval Reduction in Search-R1

arXiv:2608.13237v1 Announce Type: cross Abstract: Multi-round retrieval-augmented generation (RAG) must decide when to stop searching as evidence accumulates. Because the deployed policy is determined

safetyarxiv-cs-cl

When Your Agent Opens the Chat App: Agent-Controlled Search over Raw Chat Logs Rivals Structured Memory

arXiv:2608.12888v1 Announce Type: new Abstract: Agent-memory systems increasingly buy retrieval quality with structure, transforming raw conversation histories into summaries, embeddings, trees, or kn

Hybrid-Policy Self-Editing for Composable Unstructured Knowledge Editing

arXiv:2608.11660v1 Announce Type: cross Abstract: Large language models (LLMs) achieve remarkable performance across natural language tasks, yet they are trained on static corpora and their knowledge

LoongReflect: Boosting Long-Horizon Reflection in Search Agents via Global Perspective Distillation

arXiv:2608.11967v1 Announce Type: cross Abstract: Large language model agents increasingly rely on long-horizon reasoning to solve complex tasks involving planning, tool use, and memory. A critical ca

MaSRead: Content-Addressed Reading of Replicated Latent Stores

arXiv:2608.11218v1 Announce Type: new Abstract: Independent agents that reason in latent space can share computed state as key-value cache fragments rather than text. Merged by a conflict-free replica

Agents

The Sleeping Agent: What Gist-Based Context Compression Loses and Why

arXiv:2608.11775v1 Announce Type: new Abstract: Gist-based context compression---summarising older conversation history into compact representations---is a common approach in long-horizon language mod

agentsarxiv-cs-ai

Hardware

EvoMem: Memory-Augmented Evolution for Code Optimization

arXiv:2608.10795v1 Announce Type: new Abstract: Successful mutation strategies in evolutionary code search may contain reusable knowledge that is useful beyond a single run, and in some cases may tran

hardwarearxiv-cs-ai

GraFine: Retrieval-Time Refinement for Efficient Graph RAG over Corpus Graphs

arXiv:2601.18579v2 Announce Type: replace-cross Abstract: Graph RAG on corpus graphs enhances retrieval by leveraging intermediate node content as contextual clues to uncover unretrieved oracle nodes.

Interpreting Language Model Hidden States at Scale

arXiv:2608.10260v1 Announce Type: new Abstract: Lens methods interpret large language models (LLMs) by mapping intermediate activations to the output vocabulary, revealing how next-token predictions d

Is This Your Final Answer? Cross-Contextual Consistency as a Measure of LLM Credibility

arXiv:2608.10315v1 Announce Type: cross Abstract: Large language models (LLMs) are powerful black-box systems, making it difficult to discern whether their answers reflect stable internal beliefs or s

Operationalising Relative Causal Knowledge: Backbone Identifiability from Private Reports on a Shared Outcome

arXiv:2608.10664v1 Announce Type: new Abstract: The Relativity of Causal Knowledge (RCK) explains how a network of agents with different structural causal models can exchange causal knowledge through

RLMOpt: Adaptive Prompt Optimization via Recursive Language Models

arXiv:2608.10471v1 Announce Type: new Abstract: Prompt optimizers automate the search for prompts that improve language-model performance, but existing methods rely on a predefined optimization proced

The Gaussian-Multinoulli Restricted Boltzmann Machine: A Potts Model Extension of the GRBM

arXiv:2505.11635v2 Announce Type: cross Abstract: Many real-world tasks, from associative memory to symbolic reasoning, benefit from discrete, structured representations that standard continuous laten

TRACE: Trustworthy Retrieval-Augmented Conversational Engine

arXiv:2608.10176v1 Announce Type: new Abstract: Public service chatbots are expected to deliver recommendations from an underlying public service directory, while also making sure that the recommendat

Counterfactual Benchmarking and Training for Factuality Consistency and Order-Robust Grounded Reasoning in LLMs over Heterogeneous Knowledge

arXiv:2608.07838v1 Announce Type: new Abstract: Large language models (LLMs) have increasingly supported response generation grounded in user-provided knowledge spanning heterogeneous structures. Howe

Hierarchical Multi-Task Federated Learning in VANETs

arXiv:2608.08111v1 Announce Type: cross Abstract: Vehicular Ad hoc Networks (VANETs) increasingly rely on federated learning (FL) to enable collaborative intelligence without sharing raw sensory data.

Agents

InfMem: Learning System-2 Memory Control for Long-Context Agent

arXiv:2602.02704v2 Announce Type: replace Abstract: Reasoning over ultra-long documents requires synthesizing sparse evidence scattered across distant segments under strict memory constraints. While s

agentsarxiv-cs-cl

SCOUT: Self-Checking and Recovery-Aware Tool-Thought Agents for Ultra-Long Egocentric Video Reasoning

arXiv:2608.07959v1 Announce Type: new Abstract: Ultra-long egocentric video understanding requires reasoning over temporally sparse evidence distributed across hours or days, challenging current multi

The Knowing-Saying Gap: When Probes See Errors that Confidence Misses

arXiv:2608.07528v1 Announce Type: new Abstract: Linear probes detect corrupted context in language models with near-perfect accuracy, yet this does not translate into reliable failure prediction. The

CoinRAG: Contextualized Information Nugget KV Cache Reuse for Long-Context RAG

arXiv:2608.07458v1 Announce Type: cross Abstract: Recent optimization studies on Retrieval-Augmented Generation (RAG) have exploited chunk-level KV cache reuse to avoid processing long retrieved conte

Does More Retrieved Evidence Help Visual Retrieval-Augmented Generation with Diffusion Language Models?

arXiv:2608.07006v1 Announce Type: new Abstract: Visual retrieval-augmented generation (RAG) commonly expands the retrieved evidence set to improve answer-page coverage, implicitly assuming that all av

researcharxiv-cs-cl

Factorized Hypothesis Search for Evidence-to-Taxonomy Retrieval

arXiv:2608.06614v1 Announce Type: cross Abstract: Large-taxonomy retrieval often assumes that the input already expresses the target concept. In many settings, however, the input is indirect evidence,

GPTKB 2.0: Browsing, Querying, and Auditing a Disambiguated LLM-Derived Knowledge Base

arXiv:2608.06992v1 Announce Type: cross Abstract: We present a web demo for exploring a large-scale disambiguated knowledge base (KB) materialized from a large language model (LLM). GPTKB 2.0 contains

Tutorials

Improving Attributed Long-form Question Answering with Intent Awareness

arXiv:2603.27435v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly being used to generate comprehensive, knowledge-intensive reports. However, while these models a

tutorialsarxiv-cs-ai

Retrieval-Constrained Policy Optimization for Attack Technique Extraction from Cyber Threat Intelligence

arXiv:2608.06778v1 Announce Type: cross Abstract: Mapping cyber threat intelligence (CTI) text to MITRE ATT&CK techniques is essential for structured threat analysis, yet manual annotation is costly a

TEPA: Revoking Stale Memories for Conflict-Robust Language Agents

arXiv:2608.07429v1 Announce Type: new Abstract: Long-term memory enables language agents to reuse past facts, preferences, and task experience. Persistence also creates a central falsifiability proble

When History Lies: Evaluating and Improving Tool Use under Misleading Multi-Turn Histories

arXiv:2608.06057v1 Announce Type: new Abstract: Tool-calling agents infer task state from accumulated dialogue and tool traces. In persistent interactions, however, historical traces may remain struct

7 Aug 2026

Chained Recursive Language Models for Multi-Iteration Reasoning

arXiv:2608.05124v1 Announce Type: cross Abstract: Long context reasoning in large language models (LLMs) is usually constrained by the fact that a single inference trajectory has to simultaneously exp

Hierarchical Graph Memory for LLM Agents with Path-level Localization and Rewrite

arXiv:2608.05095v1 Announce Type: new Abstract: Agents for long term reasoning require a memory that can be efficiently and effectively updated over time, as new facts and external feedback continue t

MemFly: On-the-Fly Memory Optimization via Information Bottleneck

arXiv:2602.07885v2 Announce Type: replace Abstract: Long-term memory enables large language model agents to tackle complex tasks through historical interactions. However, existing frameworks encounter

PriDyG: Privacy-preserving Dynamic Graph Inference with LLM-GNN Collaboration

arXiv:2608.04255v1 Announce Type: cross Abstract: Graph inference over relational data can expose sensitive edge information, and this risk becomes more severe in dynamic graphs, where repeated model

researcharxiv-cs-lg

Relevant but Incomplete: Referential Dangling as a Paradigm-Level Failure Mode in Hard Prompt Compression

arXiv:2608.04569v1 Announce Type: new Abstract: Hard prompt compression reduces long-context inference cost by independently scoring tokens, sentences, or chunks and retaining the highest-scoring unit

Tutorials

The RAIL Principles for Neurosymbolic AI: Reasoning, Assurances, Interfacing and Learning

arXiv:2608.04285v1 Announce Type: new Abstract: Neurosymbolic AI systems that integrate machine learning and symbolic reasoning are rapidly gaining attention. They complement the data-intensive statis

tutorialsarxiv-cs-ai

Does Forgetting Transfer Across Modalities? A Real-World Benchmark for Cross-Modal Knowledge Unlearning Evaluation

arXiv:2608.03791v1 Announce Type: new Abstract: Vision-Language Models (VLMs), like Large Language Models (LLMs), may memorize sensitive, copyrighted, or harmful knowledge from their pretraining corpo

PI-Mem: Pushing Long-Context Reasoning to 3.6M Tokens with Parallel-Iterative Memory

arXiv:2608.03048v1 Announce Type: cross Abstract: Long-context reasoning remains a critical bottleneck for large language models, as recent recurrent-memory approaches face two inherent challenges: se

Applications

ProPRL: Property-Aware Prerequisite Relation Learning in Educational Knowledge Graphs

arXiv:2608.03006v1 Announce Type: new Abstract: Prerequisite relation learning is central to adaptive instruction, yet existing methods often formulate it as conventional link prediction, limiting the

applicationsarxiv-cs-ai

Video-DeepResearch: Towards the Next-Generation Multimodal Deepresearch Agent

arXiv:2608.03979v1 Announce Type: cross Abstract: We introduce Video-DeepResearch (Video-DR), extending multimodal agents from static images to continuous video streams, a setting that demands dense s

Evaluating VLMs on Multimodal Aristotelian Persuasion Tasks

arXiv:2608.01238v1 Announce Type: new Abstract: Vision Language Models (VLMs) have demonstrated exceptional performance across various tasks. However, they have not yet been thoroughly evaluated on mo

4 Aug 2026

Global Optimization and Inference-Time Region Grafting for Agentic Workflows

arXiv:2608.02353v1 Announce Type: new Abstract: Recent advances in agentic workflow optimization automate workflow design through task-specific workflow search or input-conditioned architecture select

4 Aug 2026

ScrambleToolBench: Agents Search Exhaustively Even When Their Own Map Points to the Next Step

arXiv:2608.02358v1 Announce Type: new Abstract: To operate robustly in open-world environments, autonomous agents should be able to infer the behavior of unfamiliar systems through interaction alone,

4 Aug 2026

BLADE: Boundary-Expanded and Layer-Adaptive Dynamic Exit for Efficient LLM Reasoning

arXiv:2607.28966v1 Announce Type: new Abstract: Large language models often improve task performance by generating long reasoning traces, but the resulting computation is frequently wasted on redundan

researcharxiv-cs-cl

3 Aug 2026

Agents

HarnessBank: Semantic Gene-Bank Search with Gated Verification for Agent-Harness Self-Evolution

arXiv:2607.13683v2 Announce Type: replace Abstract: Large Language Models (LLMs) have enabled capable agents across diverse applications. Beyond the foundation model, the performance of an agent is go

agentsarxiv-cs-cl

3 Aug 2026

Self-Play Meets Skill Evolution: Self-Evolving Search Agents that Pose, Solve, and Remember

arXiv:2607.29468v1 Announce Type: new Abstract: Self-play agents can generate training problems without questions from target benchmarks, but their curricula lack persistent state: failures affect gra

3 Aug 2026

From Single- to Cross-Document: Benchmarking Multi-Granularity Event Analysis of Large Language Models

arXiv:2607.27654v1 Announce Type: new Abstract: Event analysis is an essential and fundamental direction of information extraction, involving various event-centric tasks at different granularity of do

31 Jul 2026

Same Evidence, Different Target: Decoding How Diagnostic Evidence Bears on Causal Questions from Language-Model States

arXiv:2607.26929v1 Announce Type: new Abstract: The same diagnostic result can support or challenge one causal claim yet fail to address another when the claims concern different populations, outcomes