👥 Multi-Agent

🧠 NeurIPS2026 · 4 paper notes

📌 Same area in other venues: 🎞️ ECCV2026 (6) · 📷 CVPR2026 (2) · 🔬 ICLR2026 (47) · 💬 ACL2026 (39) · 🧪 ICML2026 (24) · 🤖 AAAI2026 (26)

🔥 Top topics: Agents ×2 · LLM ×2

AgentGrad: Intervention-guided Prompt Optimization for Multi Agent Systems

AgentGrad identifies repairable prompts through single-agent interventions, extracts textual gradients from differences between original and intervention-adjusted intermediate outputs, and clusters and abstracts shared corrective patterns; with GPT-5-mini, it improves the five-task average over unoptimized prompts by 11.76 percentage points, although some performance and cost summaries require the exceptions in the tables.

DAGent: Evaluate-then-Grow Planning for Deep Research Agents

DAGent evaluates completed sub-tasks before incrementally growing a research DAG, combining hierarchical evidence propagation with DAGRPO structural rewards: training-free Qwen3-32B achieves 47.3 / 55.3 / 65.0 Pass@1 across three benchmarks, outperforming its same-architecture Plan-then-Patch variant by 5.3 / 4.8 / 4.0 percentage points.

Measuring Collapse and Correction in Homogeneous-Panel LLM Debate

The paper decomposes debate among three copies of one model into preservation, collapse, correction, and unrepaired transitions, using pre-debate screening and round-level traces to locate risk; however, an offline freeze replay prevents 29 collapses while losing 108 corrections, showing that a risk signal is not an effective controller.

XBridge: Entity-Grounded Latent Bridge for Heterogeneous LLM Communication

XBridge transfers the full context token sequence through deterministic lexical anchor mapping and reads sender hidden states through a pairwise-trained cross-attention bridge, outperforming 128-token text-summary communication on all seven tasks for three heterogeneous model pairs and reducing per-sample latency from 1.70 to 0.15 seconds in the specified H200 test.