arXiv AI
Jul 29
Desktop-Delta Bench: Do Computer-Use Models Understand Desktop GUI Transitions?
arXiv:2607. 26041v1 Announce Type: new Abstract: Computer-use agents (CUAs) increasingly act through desktop GUIs to complete long-horizon tasks.
CausalCache: Conditional High-Fidelity Restoration for Long-Horizon GUI Agents
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arXiv Computer Vision
Sep 10
TRACE: Trajectory-robust Admission with Evidence Ordering for Efficient GUI Agents
arXiv:2609.10297v1 Announce Type: new Abstract: GUI agents accumulate high-resolution screenshots as the trajectory unfolds, increasing inference latency and memory usage. Training-free visual token...
arXiv Computation and Language
Sep 1
When History Is Multimodal: Rethinking Context Management for Long-Horizon Agents
arXiv:2608.29897v1 Announce Type: new Abstract: Long-horizon agents need a context manager to compress growing interaction histories into a bounded working context, via passive strategies or active s...
arXiv Machine Learning
Jul 20
Presentation, Not Mechanism: A Render Confound in Deprecation-Aware Memory Evaluation
arXiv:2607. 16019v1 Announce Type: new Abstract: AI systems increasingly retrieve from records that revise themselves: issue threads, encyclopedic histories, policy logs, and long conversations.
arXiv AI
Aug 14
Beyond Retrieval: Query-Conditioned Reuse of Long-Horizon Agent Trajectories
arXiv:2608. 12847v1 Announce Type: new Abstract: Retrieval can identify a past trajectory that may matter, yet it does not specify how an acting agent should use that trajectory after users, entities, constraints, or environment state have changed.
arXiv AI
Sep 17
Contiguity, Not Importance: Budgeted Repair of Stale KV Caches After Document Edits
The paper investigates how to efficiently repair stale key-value (KV) caches in retrieval‑augmented generation systems after document edits. It proposes a budgeted in‑place recomputation approach and evaluates training‑free position‑selection policies on a factual RAG benchmark. Across three model families, a contiguous edit‑local window consistently recovers most of the post‑edit answer quality while being 13–21 times faster than a full re‑prefill, though its effectiveness diminishes when answer‑bearing text moves downstream.
arXiv Machine Learning
Jul 31
Why Are GUI Agents Correct but Late? Decode on the Decision-Time Critical Path, Tested with Pre-Compiled Policy Trees
arXiv:2607. 28399v1 Announce Type: new Abstract: Computer-use agents often fail on transient GUI events because they produce the correct action only after the relevant window has already closed.
arXiv Computer Vision
Sep 14
Pixel Decodability Is Not a Compression Signal: Causally Evaluating Importance Proxies for Visual KV-Cache Eviction
arXiv:2609.13012v1 Announce Type: new Abstract: Vision-language models retain a substantial amount of pixel-decodable visual content in their visual key-value cache. We show, in our setting, that thi...
arXiv Computation and Language
6d ago
TRACE: Temporal Audit and Condition-aware Evaluation of Streaming Video Understanding
TRACE (Temporal Audit and Condition-aware Evaluation) is a new benchmark and evaluation framework for streaming video understanding that explicitly records when evidence becomes valid, how visual history is maintained, and how responses are triggered. It combines temporally audited visual tasks, evidence timing, instruction-dependent trigger annotations, a unified causal Core–Adapter protocol, and multidimensional reporting of answer quality, timeliness, response-selection behavior, workload, completion, and reliability. Using 1,240 records from 517 videos, TRACE evaluated eight publicly available models in eight configurations, revealing that similar QA accuracy can hide significant differences in completion, answer validity, generation workload, and proactive performance metrics such as response delay, false alarms, and missed target windows.
arXiv AI
Aug 11
Reading is not Reasoning: Bridging the Agentic Policy Gap in Vision-Text Compression
arXiv:2608. 08960v1 Announce Type: new Abstract: Multi-step language-model agents repeatedly process growing interaction histories, leading to substantial context costs.
arXiv Computation and Language
Aug 28
TwinKV: A Composable Repair Pass for KV Cache Eviction via Pairwise Key Redundancy
TwinKV is a training‑free, attention‑free repair pass that identifies and swaps orphaned and redundant tokens in a KV cache, improving long‑context inference for small models. It works by detecting near‑duplicate keys and can be composed with existing eviction policies without altering their scoring rules. Experiments on Qwen3‑4B and Llama‑3.2‑1B across LongBench, LooGLE, RULER, and MMLU‑Pro show that TwinKV consistently improves performance for most configurations, especially at tighter compression ratios.
arXiv AI
Jul 14
Memory-Conditioned Tool Calling for Camera-First Visual Agents
arXiv:2607. 09822v1 Announce Type: cross Abstract: Recognition tells an agent what is in an image; personal memory affects what is worth looking up next.