AI Coding Live News

As LLM agents are deployed on long-horizon, end-to-end open web tasks such as deep research, multi-vendor comparison, and cross-site navigation, existing web access paradigms suffer severe fragmentation: search-augmented agents discard interactive controls, browser-based agents incur prohibitive context token consumption, and filesystem-based tools (Fetch-then-Explore) lose crucial interaction contexts when selectively grepping text. Researchers from Yonsei University introduce Web$hell (arXiv:2610.13416), a unified interface standardizing web access. Anchored by WebContract (establishing consistent schemas for addresses, values, and associations), WebCompiler (deterministically transforming HTML semantics into operable information and action objects without LLM inference overhead), and WebCache (maintaining persistent, stateful page revision trees), Web$hell unifies passive discovery with active interaction. Evaluated across six benchmarks spanning Web Search (WideSearch, SealQA), Web Navigation (WebArena-Verified, WebWalkerQA), and Deep Research (DeepResearchBench, DeepWeb-Bench), Web$hell achieves state-of-the-art performance across all tasks. Crucially, it slashes Deep Research turns from 52.4 and 30.9 down to 17.6 (-43% to -66%), maintaining flat cost curves even when subjected to 400 injected distractor pages.

Autonomous deep research agents are expanding beyond text-centric search toward multimodal discovery across high-resolution imagery, complex charts, and long-horizon video. However, existing multimodal models struggle to ground fine-grained visual anchors and bridge perceptual evidence with external search verification. Researchers from Fudan University and collaborating institutions introduce OneSearch-VL (arXiv:2610.12419), a unified multimodal deep research agent for single-image, multi-image, and video environments. OneSearch-VL centers on the Visually Grounded Evidence Graph (VGEG), which explicitly encodes localized visual anchors, entity relationships, source-supported facts, and research operations into a shared dependency topology. Leveraging VGEG, the authors construct OneSearch-VL-SFT-110K and OneSearch-VL-RL-10K datasets alongside an Evidence-aware Visual-Grounded Rubric reward (EVGR) to supervise visual traceability during reinforcement learning. On the newly introduced OneSearch-MI-Bench and OneSearch-Video-Bench, OneSearch-VL-8B outperforms tool-augmented Qwen3-VL-8B by 20.2 and 17.6 percentage points respectively, while setting new state-of-the-art results across seven established image benchmarks and VideoDR, with code fully open-sourced.

Autonomous deep research agents (such as OpenAI Deep Research and Perplexity) represent a powerful leap toward automated knowledge synthesis. However, on open-ended and comprehensive inquiries, existing agents rely primarily on unconstrained search-and-generate loops. This leads to three systemic failures: redundant query loops, conflicting claims across sections, and runaway token expansion. Researchers from Tsinghua University and Renmin University of China unveil IOEDR (arXiv:2610.11566), a framework for Incremental Open-Ended Deep Research with a Structured Harness. IOEDR models the evolving research report as a dynamic hierarchical state graph coupled with a persistent, deduplicated evidence pool. Rather than executing open-ended browsing, the agent uses structured harness constraints to incrementally plan sections, identify specific evidential gaps, and trigger precision queries with dynamic termination conditions. On DeepResearch Bench, IOEDR achieves superior report coherence and verifiable fact density while reducing total token consumption by 33.2% and slashing search API requests by 61.4%.

Anthropic expanded dynamic workflows in Claude Managed Agents to public beta. With workflows enabled in an agent's multiagent block, Claude writes a workflow program that runs many agents in background phases and combines their results, aimed at audits, migrations, deep research and cross-checking.

Elon Musk amplified a Grok Bot update for sales teams. Bots can now connect to Salesforce, HubSpot, Gong, Clay, Granola, and other GTM tools to track accounts, complete follow-ups, and run deep research.