[Benchmark Backfill] Integrate EgoTempo into lmms-eval

[Luodian]

Summary

• Add egotempo benchmark task integration with YAML config and utility functions.
• Add optional local clip path resolution for EgoTempo videos via EGOTEMPO_VIDEO_DIR and EGOTEMPO_CACHE_DIR.
• Update video benchmark documentation list in docs/current_tasks.md.

Validation

• uv run pre-commit run --files docs/current_tasks.md lmms_eval/tasks/egotempo/egotempo.yaml lmms_eval/tasks/egotempo/utils.py
• uv run python -m lmms_eval --tasks list (includes egotempo)
• uv run python -m lmms_eval --model dummy_video_reader --model_args response=A,fail_on_missing=false --tasks egotempo --batch_size 1 --limit 2
• uv run python -m lmms_eval --model openai --model_args model_version=bytedance-seed/seed-1.6-flash,api_key=$OPENROUTER_API_KEY,base_url=https://openrouter.ai/api/v1 --tasks egotempo --batch_size 1 --limit 1

Smoke Validation (limit=8)

Status: PASS (LMM-290 / egotempo)

Output Table

Metric	Value
egotempo_anls	0.09375
egotempo_anls_pct	9.375

Sample Output

Sample 1 (doc_id: 0)

• Input: Which object does the person pick up after taking the bowl from the cupboard? ↵ Answer with a short phrase.
• Model Output: Spoon.
• Reference: A spoon.
• Scores: egotempo_anls = 0.75 (question_type: action-specific object)
• Tokens: output=242, reasoning=239

Sample 2 (doc_id: 1)

• Input: What does the person pick up before rubbing their hands together? ↵ Answer with a short phrase.
• Model Output: Soap.
• Reference: The oil remover spray.
• Scores: egotempo_anls = 0.0 (question_type: action-specific object)
• Tokens: output=477, reasoning=474

Test Params

uv run python -m lmms_eval --model openai_compatible --model_args "model_version=bytedance-seed/seed-1.6-flash" --tasks egotempo --batch_size 1 --limit 8.0 --log_samples